02-index-slice-subset.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# Indexing, Slicing and Subsetting DataFrames in Python\n",
    "\n",
    "## Loading our data\n",
    "We will continue to use the surveys dataset that we worked with in the last\n",
    "lesson. Let's reopen and read in the data again:"
   ]
  },
  {
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   "source": [
    "# Make sure pandas is loaded\n",
    "import pandas as pd\n",
    "\n",
    "# read in the survey csv\n",
    "surveys_df = pd.read_csv(\"data/surveys.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Indexing and Slicing in Python\n",
    "We often want to work with subsets of a **DataFrame** object. There are\n",
    "different ways to accomplish this including: using labels (column headings),\n",
    "numeric ranges, or specific x,y index locations.\n",
    "\n",
    "\n",
    "## Selecting data using Labels (Column Headings)\n",
    "We use square brackets `[]` to select a subset of an Python object. For example,\n",
    "we can select all data from a column named `species_id` from the `surveys_df`\n",
    "DataFrame by name. There are two ways to do this:"
   ]
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       "Name: species_id, Length: 35549, dtype: object"
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   "source": [
    "# TIP: use the .head() method we saw earlier to make output shorter\n",
    "# Method 1: select a 'subset' of the data using the column name\n",
    "surveys_df['species_id']\n",
    "\n",
    "# Method 2: use the column name as an 'attribute'; gives the same output\n",
    "surveys_df.species_id"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also create a new object that contains only the data within the\n",
    "`species_id` column as follows:"
   ]
  },
  {
   "cell_type": "code",
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   "outputs": [],
   "source": [
    "# creates an object, surveys_species, that only contains the `species_id` column\n",
    "surveys_species = surveys_df['species_id']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can pass a list of column names too, as an index to select columns in that\n",
    "order. This is useful when we need to reorganize our data."
   ]
  },
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       "      species_id  plot_id\n",
       "0             NL        2\n",
       "1             NL        3\n",
       "2             DM        2\n",
       "3             DM        7\n",
       "4             DM        3\n",
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       "8             DM        1\n",
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       "13            DM        8\n",
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       "15            DM        4\n",
       "16            DS        3\n",
       "17            PP        2\n",
       "18            PF        4\n",
       "19            DS       11\n",
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       "25            DM       15\n",
       "26            DM       15\n",
       "27            DM       11\n",
       "28            PP       11\n",
       "29            DS       10\n",
       "...          ...      ...\n",
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       "35521         DM        9\n",
       "35522         DM        9\n",
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       "35532         DM       14\n",
       "35533         DM       14\n",
       "35534         DM       14\n",
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       "35548        NaN        5\n",
       "\n",
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   "source": [
    "# select the species and plot columns from the DataFrame\n",
    "surveys_df[['species_id', 'plot_id']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
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       "      <th>17</th>\n",
       "      <td>2</td>\n",
       "      <td>PP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>4</td>\n",
       "      <td>PF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>11</td>\n",
       "      <td>DS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>15</td>\n",
       "      <td>NL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>13</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>13</td>\n",
       "      <td>SH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>15</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>15</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>11</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>11</td>\n",
       "      <td>PP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>10</td>\n",
       "      <td>DS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35519</th>\n",
       "      <td>9</td>\n",
       "      <td>SF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35520</th>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35521</th>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35522</th>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35523</th>\n",
       "      <td>9</td>\n",
       "      <td>PB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35524</th>\n",
       "      <td>9</td>\n",
       "      <td>OL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35525</th>\n",
       "      <td>8</td>\n",
       "      <td>OT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35526</th>\n",
       "      <td>13</td>\n",
       "      <td>DO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35527</th>\n",
       "      <td>13</td>\n",
       "      <td>US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35528</th>\n",
       "      <td>13</td>\n",
       "      <td>PB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35529</th>\n",
       "      <td>13</td>\n",
       "      <td>OT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35530</th>\n",
       "      <td>13</td>\n",
       "      <td>PB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35531</th>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35532</th>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35533</th>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35534</th>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35535</th>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35536</th>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35537</th>\n",
       "      <td>15</td>\n",
       "      <td>PB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35538</th>\n",
       "      <td>15</td>\n",
       "      <td>SF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35539</th>\n",
       "      <td>15</td>\n",
       "      <td>PB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35540</th>\n",
       "      <td>15</td>\n",
       "      <td>PB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35541</th>\n",
       "      <td>15</td>\n",
       "      <td>PB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35542</th>\n",
       "      <td>15</td>\n",
       "      <td>PB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35543</th>\n",
       "      <td>15</td>\n",
       "      <td>US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35544</th>\n",
       "      <td>15</td>\n",
       "      <td>AH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35545</th>\n",
       "      <td>15</td>\n",
       "      <td>AH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35546</th>\n",
       "      <td>10</td>\n",
       "      <td>RM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35547</th>\n",
       "      <td>7</td>\n",
       "      <td>DO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35548</th>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35549 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       plot_id species_id\n",
       "0            2         NL\n",
       "1            3         NL\n",
       "2            2         DM\n",
       "3            7         DM\n",
       "4            3         DM\n",
       "5            1         PF\n",
       "6            2         PE\n",
       "7            1         DM\n",
       "8            1         DM\n",
       "9            6         PF\n",
       "10           5         DS\n",
       "11           7         DM\n",
       "12           3         DM\n",
       "13           8         DM\n",
       "14           6         DM\n",
       "15           4         DM\n",
       "16           3         DS\n",
       "17           2         PP\n",
       "18           4         PF\n",
       "19          11         DS\n",
       "20          14         DM\n",
       "21          15         NL\n",
       "22          13         DM\n",
       "23          13         SH\n",
       "24           9         DM\n",
       "25          15         DM\n",
       "26          15         DM\n",
       "27          11         DM\n",
       "28          11         PP\n",
       "29          10         DS\n",
       "...        ...        ...\n",
       "35519        9         SF\n",
       "35520        9         DM\n",
       "35521        9         DM\n",
       "35522        9         DM\n",
       "35523        9         PB\n",
       "35524        9         OL\n",
       "35525        8         OT\n",
       "35526       13         DO\n",
       "35527       13         US\n",
       "35528       13         PB\n",
       "35529       13         OT\n",
       "35530       13         PB\n",
       "35531       14         DM\n",
       "35532       14         DM\n",
       "35533       14         DM\n",
       "35534       14         DM\n",
       "35535       14         DM\n",
       "35536       14         DM\n",
       "35537       15         PB\n",
       "35538       15         SF\n",
       "35539       15         PB\n",
       "35540       15         PB\n",
       "35541       15         PB\n",
       "35542       15         PB\n",
       "35543       15         US\n",
       "35544       15         AH\n",
       "35545       15         AH\n",
       "35546       10         RM\n",
       "35547        7         DO\n",
       "35548        5        NaN\n",
       "\n",
       "[35549 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# what happens when you flip the order?\n",
    "surveys_df[['plot_id', 'species_id']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'speciess'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2524\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2525\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2526\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'speciess'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-6-f243803dd961>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m#what happens if you ask for a column that doesn't exist?\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0msurveys_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'speciess'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2137\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2138\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2139\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2140\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2141\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2144\u001b[0m         \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2145\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2146\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2147\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2148\u001b[0m         \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m   1840\u001b[0m         \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1841\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1842\u001b[0;31m             \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1843\u001b[0m             \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_box_item_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1844\u001b[0m             \u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/internals.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, item, fastpath)\u001b[0m\n\u001b[1;32m   3841\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3842\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3843\u001b[0;31m                 \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3844\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3845\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2525\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2526\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2527\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2528\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2529\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'speciess'"
     ]
    }
   ],
   "source": [
    "#what happens if you ask for a column that doesn't exist?\n",
    "surveys_df['speciess']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Python tells us what type of error it is in the traceback, at the bottom it says `KeyError: 'speciess'` which means that `speciess` is not a column name (or Key in the related python data type dictionary).\n",
    "\n",
    "## Extracting Range based Subsets: Slicing\n",
    "\n",
    "**REMINDER**: Python Uses 0-based Indexing\n",
    "\n",
    "Let's remind ourselves that Python uses 0-based\n",
    "indexing. This means that the first element in an object is located at position 0. This is different from other tools like R and Matlab that index elements within objects starting at 1. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Create a list of numbers:\n",
    "a = [1, 2, 3, 4, 5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"fig/slicing-indexing.svg\">\n",
    "<img src=\"fig/slicing-slicing.svg\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> ## Challenge - Extracting data\n",
    ">\n",
    "> 1. What value does the code below return?\n",
    ">\n",
    ">    ```python\n",
    ">    a[0]\n",
    ">    ```\n",
    ">\n",
    "> 2. How about this:\n",
    ">\n",
    ">    ```python\n",
    ">    a[5]\n",
    ">    ```\n",
    ">\n",
    "> 3. In the example above, calling `a[5]` returns an error. Why is that?\n",
    ">\n",
    "> 4. What about?\n",
    ">\n",
    ">    ```python\n",
    ">    a[len(a)]\n",
    ">    ```\n",
    "\n",
    "## Slicing Subsets of Rows in Python\n",
    "\n",
    "Slicing using the `[]` operator selects a set of rows and/or columns from a\n",
    "DataFrame. To slice out a set of rows, you use the following syntax:\n",
    "`data[start:stop]`. When slicing in pandas the start bound is included in the\n",
    "output. The stop bound is one step BEYOND the row you want to select. So if you\n",
    "want to select rows 0, 1 and 2 your code would look like this:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "   record_id  month  day  year  plot_id species_id sex  hindfoot_length  \\\n",
       "0          1      7   16  1977        2         NL   M             32.0   \n",
       "1          2      7   16  1977        3         NL   M             33.0   \n",
       "2          3      7   16  1977        2         DM   F             37.0   \n",
       "\n",
       "   weight  \n",
       "0     NaN  \n",
       "1     NaN  \n",
       "2     NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select rows 0, 1, 2 (row 3 is not selected)\n",
    "surveys_df[0:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The stop bound in Python is different from what you might be used to in\n",
    "languages like Matlab and R.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
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      "text/plain": [
       "   record_id  month  day  year  plot_id species_id sex  hindfoot_length  \\\n",
       "0          1      7   16  1977        2         NL   M             32.0   \n",
       "1          2      7   16  1977        3         NL   M             33.0   \n",
       "2          3      7   16  1977        2         DM   F             37.0   \n",
       "3          4      7   16  1977        7         DM   M             36.0   \n",
       "4          5      7   16  1977        3         DM   M             35.0   \n",
       "\n",
       "   weight  \n",
       "0     NaN  \n",
       "1     NaN  \n",
       "2     NaN  \n",
       "3     NaN  \n",
       "4     NaN  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select the first 5 rows (rows 0, 1, 2, 3, 4)\n",
    "surveys_df[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>35548</th>\n",
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      "text/plain": [
       "       record_id  month  day  year  plot_id species_id  sex  hindfoot_length  \\\n",
       "35548      35549     12   31  2002        5        NaN  NaN              NaN   \n",
       "\n",
       "       weight  \n",
       "35548     NaN  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select the last element in the list\n",
    "# (the slice starts at the last element,\n",
    "# and ends at the end of the list)\n",
    "surveys_df[-1:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also reassign values within subsets of our DataFrame.\n",
    "\n",
    "But before we do that, let's look at the difference between the concept of\n",
    "copying objects and the concept of referencing objects in Python.\n",
    "\n",
    "## Copying Objects vs Referencing Objects in Python\n",
    "\n",
    "Let's start with an example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# using the 'copy() method'\n",
    "true_copy_surveys_df = surveys_df.copy()\n",
    "\n",
    "# using '=' operator\n",
    "ref_surveys_df = surveys_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You might think that the code `ref_surveys_df = surveys_df` creates a fresh\n",
    "distinct copy of the `surveys_df` DataFrame object. However, using the `=`\n",
    "operator in the simple statement `y = x` does **not** create a copy of our\n",
    "DataFrame. Instead, `y = x` creates a new variable `y` that references the\n",
    "**same** object that `x` refers to. To state this another way, there is only\n",
    "**one** object (the DataFrame), and both `x` and `y` refer to it.\n",
    "\n",
    "In contrast, the `copy()` method for a DataFrame creates a true copy of the\n",
    "DataFrame.\n",
    "\n",
    "Let's look at what happens when we reassign the values within a subset of the\n",
    "DataFrame that references another DataFrame object:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Assign the value `0` to the first three rows of data in the DataFrame\n",
    "ref_surveys_df[0:3] = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's try the following code:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>record_id</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>year</th>\n",
       "      <th>plot_id</th>\n",
       "      <th>species_id</th>\n",
       "      <th>sex</th>\n",
       "      <th>hindfoot_length</th>\n",
       "      <th>weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>7</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>3</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>35.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   record_id  month  day  year  plot_id species_id sex  hindfoot_length  \\\n",
       "0          0      0    0     0        0          0   0              0.0   \n",
       "1          0      0    0     0        0          0   0              0.0   \n",
       "2          0      0    0     0        0          0   0              0.0   \n",
       "3          4      7   16  1977        7         DM   M             36.0   \n",
       "4          5      7   16  1977        3         DM   M             35.0   \n",
       "\n",
       "   weight  \n",
       "0     0.0  \n",
       "1     0.0  \n",
       "2     0.0  \n",
       "3     NaN  \n",
       "4     NaN  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# ref_surveys_df was created using the '=' operator\n",
    "ref_surveys_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>record_id</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>year</th>\n",
       "      <th>plot_id</th>\n",
       "      <th>species_id</th>\n",
       "      <th>sex</th>\n",
       "      <th>hindfoot_length</th>\n",
       "      <th>weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
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       "      <th>1</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>7</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>3</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>35.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   record_id  month  day  year  plot_id species_id sex  hindfoot_length  \\\n",
       "0          0      0    0     0        0          0   0              0.0   \n",
       "1          0      0    0     0        0          0   0              0.0   \n",
       "2          0      0    0     0        0          0   0              0.0   \n",
       "3          4      7   16  1977        7         DM   M             36.0   \n",
       "4          5      7   16  1977        3         DM   M             35.0   \n",
       "\n",
       "   weight  \n",
       "0     0.0  \n",
       "1     0.0  \n",
       "2     0.0  \n",
       "3     NaN  \n",
       "4     NaN  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# surveys_df is the original dataframe\n",
    "surveys_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What is the difference between these two dataframes?\n",
    "\n",
    "When we assigned the first 3 columns the value of `0` using the\n",
    "`ref_surveys_df` DataFrame, the `surveys_df` DataFrame is modified too.\n",
    "Remember we created the reference `ref_survey_df` object above when we did\n",
    "`ref_survey_df = surveys_df`. Remember `surveys_df` and `ref_surveys_df`\n",
    "refer to the same exact DataFrame object. If either one changes the object,\n",
    "the other will see the same changes to the reference object.\n",
    "\n",
    "**To review and recap**:\n",
    "\n",
    "- **Copy** uses the dataframe's `copy()` method\n",
    "\n",
    "  ```python\n",
    "  true_copy_surveys_df = surveys_df.copy()\n",
    "  ```\n",
    "- A **Reference** is created using the `=` operator\n",
    "\n",
    "  ```python\n",
    "  ref_surveys_df = surveys_df\n",
    "  ```\n",
    "\n",
    "Okay, that's enough of that. Let's create a brand new clean dataframe from\n",
    "the original data CSV file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "surveys_df = pd.read_csv(\"data/surveys.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Slicing Subsets of Rows and Columns in Python\n",
    "We can select specific ranges of our data in both the row and column directions\n",
    "using either label or integer-based indexing.\n",
    "\n",
    "- `loc` is primarily *label* based indexing. *Integers* may be used but\n",
    "  they are interpreted as a *label*.\n",
    "- `iloc` is primarily *integer* based indexing\n",
    "\n",
    "To select a subset of rows **and** columns from our DataFrame, we can use the\n",
    "`iloc` method. For example, we can select month, day and year (columns 2, 3\n",
    "and 4 if we start counting at 1), like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   month  day  year\n",
       "0      7   16  1977\n",
       "1      7   16  1977\n",
       "2      7   16  1977"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# iloc[row slicing, column slicing]\n",
    "surveys_df.iloc[0:3, 1:4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that we asked for a slice from 0:3. This yielded 3 rows of data. When you\n",
    "ask for 0:3, you are actually telling Python to start at index 0 and select rows\n",
    "0, 1, 2 **up to but not including 3**.\n",
    "\n",
    "Let's explore some other ways to index and select subsets of data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>record_id</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>year</th>\n",
       "      <th>plot_id</th>\n",
       "      <th>species_id</th>\n",
       "      <th>sex</th>\n",
       "      <th>hindfoot_length</th>\n",
       "      <th>weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>2</td>\n",
       "      <td>NL</td>\n",
       "      <td>M</td>\n",
       "      <td>32.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>5</td>\n",
       "      <td>DS</td>\n",
       "      <td>F</td>\n",
       "      <td>53.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    record_id  month  day  year  plot_id species_id sex  hindfoot_length  \\\n",
       "0           1      7   16  1977        2         NL   M             32.0   \n",
       "10         11      7   16  1977        5         DS   F             53.0   \n",
       "\n",
       "    weight  \n",
       "0      NaN  \n",
       "10     NaN  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select all columns for rows of index values 0 and 10\n",
    "surveys_df.loc[[0, 10], :]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "species_id     NL\n",
       "plot_id         2\n",
       "weight        NaN\n",
       "Name: 0, dtype: object"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# what does this do?\n",
    "surveys_df.loc[0, ['species_id', 'plot_id', 'weight']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# What happens when you type the code below?\n",
    "surveys_df.loc[[0, 10, 35549], :]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**NOTE**: Labels must be found in the DataFrame or you will get a KeyError."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Indexing by labels `loc` differs from indexing by integers `iloc`.\n",
    "With `loc`, the both start bound and the stop bound are **inclusive**. When using\n",
    "`loc`, integers *can* be used, but the integers refer to the\n",
    "index label and not the position. For example, using `loc` and select 1:4\n",
    "will get a different result than using `iloc` to select rows 1:4.\n",
    "\n",
    "We can also select a specific data value using a row and\n",
    "column location within the DataFrame and `iloc` indexing:\n",
    "```python\n",
    "# Syntax for iloc indexing to finding a specific data element\n",
    "dat.iloc[row, column]\n",
    "```\n",
    "In this `iloc` example,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'F'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "surveys_df.iloc[2, 6]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remember that Python indexing begins at 0. So, the index location [2, 6]\n",
    "selects the element that is 3 rows down and 7 columns over in the DataFrame.\n",
    "> ## Challenge - Range\n",
    ">\n",
    "> 1. What happens when you execute:\n",
    ">\n",
    ">    - `surveys_df[0:1]`\n",
    ">    - `surveys_df[:4]`\n",
    ">    - `surveys_df[:-1]`\n",
    ">\n",
    "> 2. What happens when you call:\n",
    ">\n",
    ">    - `dat.iloc[0:4, 1:4]`\n",
    ">    - `dat.loc[0:4, 1:4]`\n",
    ">\n",
    "> - How are the two commands different?\n",
    "\n",
    "## Subsetting Data using Criteria\n",
    "\n",
    "We can also select a subset of our data using criteria. For example, we can\n",
    "select all rows that have a year value of 2002:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>record_id</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>year</th>\n",
       "      <th>plot_id</th>\n",
       "      <th>species_id</th>\n",
       "      <th>sex</th>\n",
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       "      <th>33320</th>\n",
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       "      <td>38.0</td>\n",
       "      <td>44.0</td>\n",
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       "    <tr>\n",
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       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>1</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>58.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33322</th>\n",
       "      <td>33323</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>1</td>\n",
       "      <td>PB</td>\n",
       "      <td>M</td>\n",
       "      <td>28.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33323</th>\n",
       "      <td>33324</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>1</td>\n",
       "      <td>AB</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33324</th>\n",
       "      <td>33325</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>1</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>35.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33325</th>\n",
       "      <td>33326</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>OT</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33326</th>\n",
       "      <td>33327</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>OT</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33327</th>\n",
       "      <td>33328</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>OT</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33328</th>\n",
       "      <td>33329</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33329</th>\n",
       "      <td>33330</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>35.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33330</th>\n",
       "      <td>33331</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>PE</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33331</th>\n",
       "      <td>33332</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>OT</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33332</th>\n",
       "      <td>33333</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>OT</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33333</th>\n",
       "      <td>33334</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>OT</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33334</th>\n",
       "      <td>33335</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>DO</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33335</th>\n",
       "      <td>33336</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>35.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33336</th>\n",
       "      <td>33337</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>PB</td>\n",
       "      <td>M</td>\n",
       "      <td>28.0</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33337</th>\n",
       "      <td>33338</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>26.0</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33338</th>\n",
       "      <td>33339</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>NL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33339</th>\n",
       "      <td>33340</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>12</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>34.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33340</th>\n",
       "      <td>33341</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>12</td>\n",
       "      <td>PE</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33341</th>\n",
       "      <td>33342</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>12</td>\n",
       "      <td>DO</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33342</th>\n",
       "      <td>33343</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>12</td>\n",
       "      <td>DO</td>\n",
       "      <td>F</td>\n",
       "      <td>37.0</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33343</th>\n",
       "      <td>33344</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>12</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>36.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33344</th>\n",
       "      <td>33345</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>12</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33345</th>\n",
       "      <td>33346</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>12</td>\n",
       "      <td>PE</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33346</th>\n",
       "      <td>33347</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>12</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>37.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33347</th>\n",
       "      <td>33348</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>19</td>\n",
       "      <td>PB</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33348</th>\n",
       "      <td>33349</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>19</td>\n",
       "      <td>PB</td>\n",
       "      <td>M</td>\n",
       "      <td>27.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33349</th>\n",
       "      <td>33350</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>2002</td>\n",
       "      <td>19</td>\n",
       "      <td>PP</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35519</th>\n",
       "      <td>35520</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>9</td>\n",
       "      <td>SF</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35520</th>\n",
       "      <td>35521</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35521</th>\n",
       "      <td>35522</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>35.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35522</th>\n",
       "      <td>35523</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35523</th>\n",
       "      <td>35524</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>9</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35524</th>\n",
       "      <td>35525</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>9</td>\n",
       "      <td>OL</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>26.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35525</th>\n",
       "      <td>35526</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>8</td>\n",
       "      <td>OT</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35526</th>\n",
       "      <td>35527</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>13</td>\n",
       "      <td>DO</td>\n",
       "      <td>F</td>\n",
       "      <td>33.0</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35527</th>\n",
       "      <td>35528</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>13</td>\n",
       "      <td>US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35528</th>\n",
       "      <td>35529</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>13</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35529</th>\n",
       "      <td>35530</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>13</td>\n",
       "      <td>OT</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35530</th>\n",
       "      <td>35531</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>13</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35531</th>\n",
       "      <td>35532</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>34.0</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35532</th>\n",
       "      <td>35533</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35533</th>\n",
       "      <td>35534</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>56.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35534</th>\n",
       "      <td>35535</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35535</th>\n",
       "      <td>35536</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>35.0</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35536</th>\n",
       "      <td>35537</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35537</th>\n",
       "      <td>35538</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>26.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35538</th>\n",
       "      <td>35539</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>SF</td>\n",
       "      <td>M</td>\n",
       "      <td>26.0</td>\n",
       "      <td>68.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35539</th>\n",
       "      <td>35540</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>26.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35540</th>\n",
       "      <td>35541</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>24.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35541</th>\n",
       "      <td>35542</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>26.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35542</th>\n",
       "      <td>35543</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35543</th>\n",
       "      <td>35544</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35544</th>\n",
       "      <td>35545</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>AH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35545</th>\n",
       "      <td>35546</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>AH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35546</th>\n",
       "      <td>35547</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>10</td>\n",
       "      <td>RM</td>\n",
       "      <td>F</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35547</th>\n",
       "      <td>35548</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>7</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>36.0</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35548</th>\n",
       "      <td>35549</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2229 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       record_id  month  day  year  plot_id species_id  sex  hindfoot_length  \\\n",
       "33320      33321      1   12  2002        1         DM    M             38.0   \n",
       "33321      33322      1   12  2002        1         DO    M             37.0   \n",
       "33322      33323      1   12  2002        1         PB    M             28.0   \n",
       "33323      33324      1   12  2002        1         AB  NaN              NaN   \n",
       "33324      33325      1   12  2002        1         DO    M             35.0   \n",
       "33325      33326      1   12  2002        2         OT    F             20.0   \n",
       "33326      33327      1   12  2002        2         OT    M             20.0   \n",
       "33327      33328      1   12  2002        2         OT    F             21.0   \n",
       "33328      33329      1   12  2002        2         DM    M             37.0   \n",
       "33329      33330      1   12  2002        2         DO    M             35.0   \n",
       "33330      33331      1   12  2002        2         PE    F             21.0   \n",
       "33331      33332      1   12  2002        2         OT    F             20.0   \n",
       "33332      33333      1   12  2002        2         OT    M             20.0   \n",
       "33333      33334      1   12  2002        2         OT    F             20.0   \n",
       "33334      33335      1   12  2002        2         DO    F             36.0   \n",
       "33335      33336      1   12  2002        2         DM    F             35.0   \n",
       "33336      33337      1   12  2002        2         PB    M             28.0   \n",
       "33337      33338      1   12  2002        2         PB    F             26.0   \n",
       "33338      33339      1   12  2002        2         NL  NaN              NaN   \n",
       "33339      33340      1   12  2002       12         DO    M             34.0   \n",
       "33340      33341      1   12  2002       12         PE    F             20.0   \n",
       "33341      33342      1   12  2002       12         DO    F             36.0   \n",
       "33342      33343      1   12  2002       12         DO    F             37.0   \n",
       "33343      33344      1   12  2002       12         DM    M             36.0   \n",
       "33344      33345      1   12  2002       12         DO    M             37.0   \n",
       "33345      33346      1   12  2002       12         PE    M             21.0   \n",
       "33346      33347      1   12  2002       12         DM    F             37.0   \n",
       "33347      33348      1   12  2002       19         PB    M             29.0   \n",
       "33348      33349      1   12  2002       19         PB    M             27.0   \n",
       "33349      33350      1   12  2002       19         PP    F             20.0   \n",
       "...          ...    ...  ...   ...      ...        ...  ...              ...   \n",
       "35519      35520     12   31  2002        9         SF  NaN             24.0   \n",
       "35520      35521     12   31  2002        9         DM    M             37.0   \n",
       "35521      35522     12   31  2002        9         DM    F             35.0   \n",
       "35522      35523     12   31  2002        9         DM    F             36.0   \n",
       "35523      35524     12   31  2002        9         PB    F             25.0   \n",
       "35524      35525     12   31  2002        9         OL    M             21.0   \n",
       "35525      35526     12   31  2002        8         OT    F             20.0   \n",
       "35526      35527     12   31  2002       13         DO    F             33.0   \n",
       "35527      35528     12   31  2002       13         US  NaN              NaN   \n",
       "35528      35529     12   31  2002       13         PB    F             25.0   \n",
       "35529      35530     12   31  2002       13         OT    F             20.0   \n",
       "35530      35531     12   31  2002       13         PB    F             27.0   \n",
       "35531      35532     12   31  2002       14         DM    F             34.0   \n",
       "35532      35533     12   31  2002       14         DM    F             36.0   \n",
       "35533      35534     12   31  2002       14         DM    M             37.0   \n",
       "35534      35535     12   31  2002       14         DM    M             37.0   \n",
       "35535      35536     12   31  2002       14         DM    F             35.0   \n",
       "35536      35537     12   31  2002       14         DM    F             36.0   \n",
       "35537      35538     12   31  2002       15         PB    F             26.0   \n",
       "35538      35539     12   31  2002       15         SF    M             26.0   \n",
       "35539      35540     12   31  2002       15         PB    F             26.0   \n",
       "35540      35541     12   31  2002       15         PB    F             24.0   \n",
       "35541      35542     12   31  2002       15         PB    F             26.0   \n",
       "35542      35543     12   31  2002       15         PB    F             27.0   \n",
       "35543      35544     12   31  2002       15         US  NaN              NaN   \n",
       "35544      35545     12   31  2002       15         AH  NaN              NaN   \n",
       "35545      35546     12   31  2002       15         AH  NaN              NaN   \n",
       "35546      35547     12   31  2002       10         RM    F             15.0   \n",
       "35547      35548     12   31  2002        7         DO    M             36.0   \n",
       "35548      35549     12   31  2002        5        NaN  NaN              NaN   \n",
       "\n",
       "       weight  \n",
       "33320    44.0  \n",
       "33321    58.0  \n",
       "33322    45.0  \n",
       "33323     NaN  \n",
       "33324    29.0  \n",
       "33325    26.0  \n",
       "33326    24.0  \n",
       "33327    22.0  \n",
       "33328    47.0  \n",
       "33329    51.0  \n",
       "33330    23.0  \n",
       "33331    18.0  \n",
       "33332    25.0  \n",
       "33333    22.0  \n",
       "33334    46.0  \n",
       "33335    45.0  \n",
       "33336    47.0  \n",
       "33337    30.0  \n",
       "33338     NaN  \n",
       "33339    24.0  \n",
       "33340    15.0  \n",
       "33341    26.0  \n",
       "33342    47.0  \n",
       "33343    40.0  \n",
       "33344    55.0  \n",
       "33345    23.0  \n",
       "33346    45.0  \n",
       "33347    51.0  \n",
       "33348    46.0  \n",
       "33349    13.0  \n",
       "...       ...  \n",
       "35519    36.0  \n",
       "35520    48.0  \n",
       "35521    45.0  \n",
       "35522    44.0  \n",
       "35523    27.0  \n",
       "35524    26.0  \n",
       "35525    24.0  \n",
       "35526    43.0  \n",
       "35527     NaN  \n",
       "35528    25.0  \n",
       "35529     NaN  \n",
       "35530     NaN  \n",
       "35531    43.0  \n",
       "35532    48.0  \n",
       "35533    56.0  \n",
       "35534    53.0  \n",
       "35535    42.0  \n",
       "35536    46.0  \n",
       "35537    31.0  \n",
       "35538    68.0  \n",
       "35539    23.0  \n",
       "35540    31.0  \n",
       "35541    29.0  \n",
       "35542    34.0  \n",
       "35543     NaN  \n",
       "35544     NaN  \n",
       "35545     NaN  \n",
       "35546    14.0  \n",
       "35547    51.0  \n",
       "35548     NaN  \n",
       "\n",
       "[2229 rows x 9 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "surveys_df[surveys_df.year == 2002]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or we can select all rows that do not contain the year 2002:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>record_id</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>year</th>\n",
       "      <th>plot_id</th>\n",
       "      <th>species_id</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
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       "      <td>M</td>\n",
       "      <td>32.0</td>\n",
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       "      <td>M</td>\n",
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       "      <th>2</th>\n",
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       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>2</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>37.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>7</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>3</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>35.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>1</td>\n",
       "      <td>PF</td>\n",
       "      <td>M</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>2</td>\n",
       "      <td>PE</td>\n",
       "      <td>F</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>1</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>1</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>6</td>\n",
       "      <td>PF</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>5</td>\n",
       "      <td>DS</td>\n",
       "      <td>F</td>\n",
       "      <td>53.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>7</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>3</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>35.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>8</td>\n",
       "      <td>DM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>6</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>4</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>3</td>\n",
       "      <td>DS</td>\n",
       "      <td>F</td>\n",
       "      <td>48.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>2</td>\n",
       "      <td>PP</td>\n",
       "      <td>M</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>7</td>\n",
       "      <td>16</td>\n",
       "      <td>1977</td>\n",
       "      <td>4</td>\n",
       "      <td>PF</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>11</td>\n",
       "      <td>DS</td>\n",
       "      <td>F</td>\n",
       "      <td>48.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>14</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>34.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>15</td>\n",
       "      <td>NL</td>\n",
       "      <td>F</td>\n",
       "      <td>31.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>13</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>13</td>\n",
       "      <td>SH</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>35.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>15</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>31.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>15</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>11</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>11</td>\n",
       "      <td>PP</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>10</td>\n",
       "      <td>DS</td>\n",
       "      <td>F</td>\n",
       "      <td>52.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33290</th>\n",
       "      <td>33291</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>23</td>\n",
       "      <td>PE</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33291</th>\n",
       "      <td>33292</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>23</td>\n",
       "      <td>RM</td>\n",
       "      <td>F</td>\n",
       "      <td>16.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33292</th>\n",
       "      <td>33293</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>20</td>\n",
       "      <td>PE</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33293</th>\n",
       "      <td>33294</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>20</td>\n",
       "      <td>SH</td>\n",
       "      <td>M</td>\n",
       "      <td>25.0</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33294</th>\n",
       "      <td>33295</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>20</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33295</th>\n",
       "      <td>33296</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>20</td>\n",
       "      <td>PB</td>\n",
       "      <td>M</td>\n",
       "      <td>25.0</td>\n",
       "      <td>35.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33296</th>\n",
       "      <td>33297</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>20</td>\n",
       "      <td>RM</td>\n",
       "      <td>M</td>\n",
       "      <td>16.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33297</th>\n",
       "      <td>33298</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>20</td>\n",
       "      <td>RM</td>\n",
       "      <td>F</td>\n",
       "      <td>16.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33298</th>\n",
       "      <td>33299</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>20</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>25.0</td>\n",
       "      <td>28.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33299</th>\n",
       "      <td>33300</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>20</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>26.0</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33300</th>\n",
       "      <td>33301</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>20</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33301</th>\n",
       "      <td>33302</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>24</td>\n",
       "      <td>PE</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33302</th>\n",
       "      <td>33303</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>24</td>\n",
       "      <td>PE</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33303</th>\n",
       "      <td>33304</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>24</td>\n",
       "      <td>RM</td>\n",
       "      <td>M</td>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33304</th>\n",
       "      <td>33305</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>7</td>\n",
       "      <td>PB</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33305</th>\n",
       "      <td>33306</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>7</td>\n",
       "      <td>OT</td>\n",
       "      <td>M</td>\n",
       "      <td>19.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33306</th>\n",
       "      <td>33307</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>7</td>\n",
       "      <td>OT</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33307</th>\n",
       "      <td>33308</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2001</td>\n",
       "      <td>7</td>\n",
       "      <td>PP</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33308</th>\n",
       "      <td>33309</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33309</th>\n",
       "      <td>33310</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33310</th>\n",
       "      <td>33311</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33311</th>\n",
       "      <td>33312</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33312</th>\n",
       "      <td>33313</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33313</th>\n",
       "      <td>33314</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33314</th>\n",
       "      <td>33315</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33315</th>\n",
       "      <td>33316</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33316</th>\n",
       "      <td>33317</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33317</th>\n",
       "      <td>33318</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33318</th>\n",
       "      <td>33319</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33319</th>\n",
       "      <td>33320</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2001</td>\n",
       "      <td>16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>33320 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       record_id  month  day  year  plot_id species_id  sex  hindfoot_length  \\\n",
       "0              1      7   16  1977        2         NL    M             32.0   \n",
       "1              2      7   16  1977        3         NL    M             33.0   \n",
       "2              3      7   16  1977        2         DM    F             37.0   \n",
       "3              4      7   16  1977        7         DM    M             36.0   \n",
       "4              5      7   16  1977        3         DM    M             35.0   \n",
       "5              6      7   16  1977        1         PF    M             14.0   \n",
       "6              7      7   16  1977        2         PE    F              NaN   \n",
       "7              8      7   16  1977        1         DM    M             37.0   \n",
       "8              9      7   16  1977        1         DM    F             34.0   \n",
       "9             10      7   16  1977        6         PF    F             20.0   \n",
       "10            11      7   16  1977        5         DS    F             53.0   \n",
       "11            12      7   16  1977        7         DM    M             38.0   \n",
       "12            13      7   16  1977        3         DM    M             35.0   \n",
       "13            14      7   16  1977        8         DM  NaN              NaN   \n",
       "14            15      7   16  1977        6         DM    F             36.0   \n",
       "15            16      7   16  1977        4         DM    F             36.0   \n",
       "16            17      7   16  1977        3         DS    F             48.0   \n",
       "17            18      7   16  1977        2         PP    M             22.0   \n",
       "18            19      7   16  1977        4         PF  NaN              NaN   \n",
       "19            20      7   17  1977       11         DS    F             48.0   \n",
       "20            21      7   17  1977       14         DM    F             34.0   \n",
       "21            22      7   17  1977       15         NL    F             31.0   \n",
       "22            23      7   17  1977       13         DM    M             36.0   \n",
       "23            24      7   17  1977       13         SH    M             21.0   \n",
       "24            25      7   17  1977        9         DM    M             35.0   \n",
       "25            26      7   17  1977       15         DM    M             31.0   \n",
       "26            27      7   17  1977       15         DM    M             36.0   \n",
       "27            28      7   17  1977       11         DM    M             38.0   \n",
       "28            29      7   17  1977       11         PP    M              NaN   \n",
       "29            30      7   17  1977       10         DS    F             52.0   \n",
       "...          ...    ...  ...   ...      ...        ...  ...              ...   \n",
       "33290      33291     12   15  2001       23         PE    M             20.0   \n",
       "33291      33292     12   15  2001       23         RM    F             16.0   \n",
       "33292      33293     12   15  2001       20         PE    F             20.0   \n",
       "33293      33294     12   15  2001       20         SH    M             25.0   \n",
       "33294      33295     12   15  2001       20         PB    F             27.0   \n",
       "33295      33296     12   15  2001       20         PB    M             25.0   \n",
       "33296      33297     12   15  2001       20         RM    M             16.0   \n",
       "33297      33298     12   15  2001       20         RM    F             16.0   \n",
       "33298      33299     12   15  2001       20         PB    F             25.0   \n",
       "33299      33300     12   15  2001       20         PB    F             26.0   \n",
       "33300      33301     12   15  2001       20         PB    F             27.0   \n",
       "33301      33302     12   15  2001       24         PE    M             20.0   \n",
       "33302      33303     12   15  2001       24         PE    M             20.0   \n",
       "33303      33304     12   15  2001       24         RM    M             16.0   \n",
       "33304      33305     12   15  2001        7         PB    M             29.0   \n",
       "33305      33306     12   15  2001        7         OT    M             19.0   \n",
       "33306      33307     12   15  2001        7         OT    M             20.0   \n",
       "33307      33308     12   15  2001        7         PP    M             24.0   \n",
       "33308      33309     12   16  2001        3        NaN  NaN              NaN   \n",
       "33309      33310     12   16  2001        4        NaN  NaN              NaN   \n",
       "33310      33311     12   16  2001        5        NaN  NaN              NaN   \n",
       "33311      33312     12   16  2001        6        NaN  NaN              NaN   \n",
       "33312      33313     12   16  2001        8        NaN  NaN              NaN   \n",
       "33313      33314     12   16  2001        9        NaN  NaN              NaN   \n",
       "33314      33315     12   16  2001       10        NaN  NaN              NaN   \n",
       "33315      33316     12   16  2001       11        NaN  NaN              NaN   \n",
       "33316      33317     12   16  2001       13        NaN  NaN              NaN   \n",
       "33317      33318     12   16  2001       14        NaN  NaN              NaN   \n",
       "33318      33319     12   16  2001       15        NaN  NaN              NaN   \n",
       "33319      33320     12   16  2001       16        NaN  NaN              NaN   \n",
       "\n",
       "       weight  \n",
       "0         NaN  \n",
       "1         NaN  \n",
       "2         NaN  \n",
       "3         NaN  \n",
       "4         NaN  \n",
       "5         NaN  \n",
       "6         NaN  \n",
       "7         NaN  \n",
       "8         NaN  \n",
       "9         NaN  \n",
       "10        NaN  \n",
       "11        NaN  \n",
       "12        NaN  \n",
       "13        NaN  \n",
       "14        NaN  \n",
       "15        NaN  \n",
       "16        NaN  \n",
       "17        NaN  \n",
       "18        NaN  \n",
       "19        NaN  \n",
       "20        NaN  \n",
       "21        NaN  \n",
       "22        NaN  \n",
       "23        NaN  \n",
       "24        NaN  \n",
       "25        NaN  \n",
       "26        NaN  \n",
       "27        NaN  \n",
       "28        NaN  \n",
       "29        NaN  \n",
       "...       ...  \n",
       "33290    18.0  \n",
       "33291     8.0  \n",
       "33292    22.0  \n",
       "33293    43.0  \n",
       "33294    33.0  \n",
       "33295    35.0  \n",
       "33296    11.0  \n",
       "33297     8.0  \n",
       "33298    28.0  \n",
       "33299    30.0  \n",
       "33300    31.0  \n",
       "33301    24.0  \n",
       "33302    23.0  \n",
       "33303    10.0  \n",
       "33304    44.0  \n",
       "33305    21.0  \n",
       "33306    19.0  \n",
       "33307    16.0  \n",
       "33308     NaN  \n",
       "33309     NaN  \n",
       "33310     NaN  \n",
       "33311     NaN  \n",
       "33312     NaN  \n",
       "33313     NaN  \n",
       "33314     NaN  \n",
       "33315     NaN  \n",
       "33316     NaN  \n",
       "33317     NaN  \n",
       "33318     NaN  \n",
       "33319     NaN  \n",
       "\n",
       "[33320 rows x 9 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "surveys_df[surveys_df.year != 2002]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can define sets of criteria too:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>record_id</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>year</th>\n",
       "      <th>plot_id</th>\n",
       "      <th>species_id</th>\n",
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       "      <th>weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2270</th>\n",
       "      <td>2271</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>8</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>35.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2271</th>\n",
       "      <td>2272</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>11</td>\n",
       "      <td>PF</td>\n",
       "      <td>F</td>\n",
       "      <td>16.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2272</th>\n",
       "      <td>2273</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>18</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>34.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2273</th>\n",
       "      <td>2274</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>11</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>38.0</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2274</th>\n",
       "      <td>2275</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>8</td>\n",
       "      <td>DO</td>\n",
       "      <td>F</td>\n",
       "      <td>33.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2275</th>\n",
       "      <td>2276</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>11</td>\n",
       "      <td>DS</td>\n",
       "      <td>M</td>\n",
       "      <td>47.0</td>\n",
       "      <td>132.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2276</th>\n",
       "      <td>2277</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>8</td>\n",
       "      <td>PF</td>\n",
       "      <td>M</td>\n",
       "      <td>15.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2277</th>\n",
       "      <td>2278</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>9</td>\n",
       "      <td>OT</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2278</th>\n",
       "      <td>2279</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>11</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2279</th>\n",
       "      <td>2280</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>21</td>\n",
       "      <td>OT</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2280</th>\n",
       "      <td>2281</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>11</td>\n",
       "      <td>OL</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2281</th>\n",
       "      <td>2282</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>17</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2282</th>\n",
       "      <td>2283</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>11</td>\n",
       "      <td>OL</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2283</th>\n",
       "      <td>2284</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>9</td>\n",
       "      <td>OL</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2284</th>\n",
       "      <td>2285</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>10</td>\n",
       "      <td>OL</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>24.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2285</th>\n",
       "      <td>2286</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>11</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>38.0</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2286</th>\n",
       "      <td>2287</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>21</td>\n",
       "      <td>OT</td>\n",
       "      <td>M</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2287</th>\n",
       "      <td>2288</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>19</td>\n",
       "      <td>RM</td>\n",
       "      <td>F</td>\n",
       "      <td>17.0</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2288</th>\n",
       "      <td>2289</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>20</td>\n",
       "      <td>DS</td>\n",
       "      <td>F</td>\n",
       "      <td>52.0</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2289</th>\n",
       "      <td>2290</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>11</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2290</th>\n",
       "      <td>2291</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>9</td>\n",
       "      <td>OL</td>\n",
       "      <td>F</td>\n",
       "      <td>21.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2291</th>\n",
       "      <td>2292</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>12</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>35.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2292</th>\n",
       "      <td>2293</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>18</td>\n",
       "      <td>DS</td>\n",
       "      <td>F</td>\n",
       "      <td>51.0</td>\n",
       "      <td>132.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2293</th>\n",
       "      <td>2294</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>22</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>34.0</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2294</th>\n",
       "      <td>2295</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>9</td>\n",
       "      <td>OL</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2295</th>\n",
       "      <td>2296</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>8</td>\n",
       "      <td>DO</td>\n",
       "      <td>F</td>\n",
       "      <td>34.0</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2296</th>\n",
       "      <td>2297</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>11</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2297</th>\n",
       "      <td>2298</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>17</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>35.0</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2298</th>\n",
       "      <td>2299</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>38.0</td>\n",
       "      <td>46.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2299</th>\n",
       "      <td>2300</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>1980</td>\n",
       "      <td>18</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>32.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11197</th>\n",
       "      <td>11198</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>4</td>\n",
       "      <td>DS</td>\n",
       "      <td>M</td>\n",
       "      <td>45.0</td>\n",
       "      <td>129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11198</th>\n",
       "      <td>11199</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>8</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>38.0</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11199</th>\n",
       "      <td>11200</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>7</td>\n",
       "      <td>AB</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11200</th>\n",
       "      <td>11201</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>5</td>\n",
       "      <td>OL</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11201</th>\n",
       "      <td>11202</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>35.0</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11202</th>\n",
       "      <td>11203</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>7</td>\n",
       "      <td>PE</td>\n",
       "      <td>F</td>\n",
       "      <td>17.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11203</th>\n",
       "      <td>11204</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>3</td>\n",
       "      <td>PP</td>\n",
       "      <td>F</td>\n",
       "      <td>22.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11204</th>\n",
       "      <td>11205</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>5</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>56.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11205</th>\n",
       "      <td>11206</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>11</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>38.0</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11206</th>\n",
       "      <td>11207</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>2</td>\n",
       "      <td>PE</td>\n",
       "      <td>M</td>\n",
       "      <td>18.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11207</th>\n",
       "      <td>11208</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>8</td>\n",
       "      <td>DS</td>\n",
       "      <td>F</td>\n",
       "      <td>50.0</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11208</th>\n",
       "      <td>11209</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>2</td>\n",
       "      <td>DO</td>\n",
       "      <td>F</td>\n",
       "      <td>37.0</td>\n",
       "      <td>52.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11209</th>\n",
       "      <td>11210</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>2</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>35.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11210</th>\n",
       "      <td>11211</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>13</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11211</th>\n",
       "      <td>11212</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>4</td>\n",
       "      <td>DS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>121.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11212</th>\n",
       "      <td>11213</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>13</td>\n",
       "      <td>AH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11213</th>\n",
       "      <td>11214</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>1</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>37.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11214</th>\n",
       "      <td>11215</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>2</td>\n",
       "      <td>NL</td>\n",
       "      <td>F</td>\n",
       "      <td>32.0</td>\n",
       "      <td>160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11215</th>\n",
       "      <td>11216</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>3</td>\n",
       "      <td>RM</td>\n",
       "      <td>M</td>\n",
       "      <td>17.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11216</th>\n",
       "      <td>11217</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>4</td>\n",
       "      <td>OL</td>\n",
       "      <td>M</td>\n",
       "      <td>24.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11217</th>\n",
       "      <td>11218</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>36.0</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11218</th>\n",
       "      <td>11219</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>8</td>\n",
       "      <td>DM</td>\n",
       "      <td>F</td>\n",
       "      <td>38.0</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11219</th>\n",
       "      <td>11220</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>5</td>\n",
       "      <td>DO</td>\n",
       "      <td>F</td>\n",
       "      <td>37.0</td>\n",
       "      <td>56.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11220</th>\n",
       "      <td>11221</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>13</td>\n",
       "      <td>AH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11221</th>\n",
       "      <td>11222</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>7</td>\n",
       "      <td>AB</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11222</th>\n",
       "      <td>11223</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>4</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>36.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11223</th>\n",
       "      <td>11224</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>11</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11224</th>\n",
       "      <td>11225</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>7</td>\n",
       "      <td>PE</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11225</th>\n",
       "      <td>11226</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>1</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>38.0</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11226</th>\n",
       "      <td>11227</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>1985</td>\n",
       "      <td>15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8957 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       record_id  month  day  year  plot_id species_id  sex  hindfoot_length  \\\n",
       "2270        2271      1   15  1980        8         DO    M             35.0   \n",
       "2271        2272      1   15  1980       11         PF    F             16.0   \n",
       "2272        2273      1   15  1980       18         DM    F             34.0   \n",
       "2273        2274      1   15  1980       11         DM    M             38.0   \n",
       "2274        2275      1   15  1980        8         DO    F             33.0   \n",
       "2275        2276      1   15  1980       11         DS    M             47.0   \n",
       "2276        2277      1   15  1980        8         PF    M             15.0   \n",
       "2277        2278      1   15  1980        9         OT    M             21.0   \n",
       "2278        2279      1   15  1980       11         DM    F             36.0   \n",
       "2279        2280      1   15  1980       21         OT    F             20.0   \n",
       "2280        2281      1   15  1980       11         OL    M             20.0   \n",
       "2281        2282      1   15  1980       17         DM    F             36.0   \n",
       "2282        2283      1   15  1980       11         OL    M             21.0   \n",
       "2283        2284      1   15  1980        9         OL    M             20.0   \n",
       "2284        2285      1   15  1980       10         OL    F             20.0   \n",
       "2285        2286      1   15  1980       11         DM    M             38.0   \n",
       "2286        2287      1   15  1980       21         OT    M             19.0   \n",
       "2287        2288      1   15  1980       19         RM    F             17.0   \n",
       "2288        2289      1   15  1980       20         DS    F             52.0   \n",
       "2289        2290      1   15  1980       11         DM    M             37.0   \n",
       "2290        2291      1   15  1980        9         OL    F             21.0   \n",
       "2291        2292      1   15  1980       12         DM    F             35.0   \n",
       "2292        2293      1   15  1980       18         DS    F             51.0   \n",
       "2293        2294      1   15  1980       22         DM    F             34.0   \n",
       "2294        2295      1   15  1980        9         OL    M             21.0   \n",
       "2295        2296      1   15  1980        8         DO    F             34.0   \n",
       "2296        2297      1   15  1980       11         DM    M             37.0   \n",
       "2297        2298      1   15  1980       17         DM    M             35.0   \n",
       "2298        2299      1   15  1980        9         DM    M             38.0   \n",
       "2299        2300      1   15  1980       18         DM    F             32.0   \n",
       "...          ...    ...  ...   ...      ...        ...  ...              ...   \n",
       "11197      11198     12    8  1985        4         DS    M             45.0   \n",
       "11198      11199     12    8  1985        8         DM    F             38.0   \n",
       "11199      11200     12    8  1985        7         AB  NaN              NaN   \n",
       "11200      11201     12    8  1985        5         OL    M             21.0   \n",
       "11201      11202     12    8  1985        9         DM    F             35.0   \n",
       "11202      11203     12    8  1985        7         PE    F             17.0   \n",
       "11203      11204     12    8  1985        3         PP    F             22.0   \n",
       "11204      11205     12    8  1985        5         DO    M             37.0   \n",
       "11205      11206     12    8  1985       11         DM    F             38.0   \n",
       "11206      11207     12    8  1985        2         PE    M             18.0   \n",
       "11207      11208     12    8  1985        8         DS    F             50.0   \n",
       "11208      11209     12    8  1985        2         DO    F             37.0   \n",
       "11209      11210     12    8  1985        2         DM    F             35.0   \n",
       "11210      11211     12    8  1985       13         DM    M             37.0   \n",
       "11211      11212     12    8  1985        4         DS  NaN              NaN   \n",
       "11212      11213     12    8  1985       13         AH  NaN              NaN   \n",
       "11213      11214     12    8  1985        1         DM    F             37.0   \n",
       "11214      11215     12    8  1985        2         NL    F             32.0   \n",
       "11215      11216     12    8  1985        3         RM    M             17.0   \n",
       "11216      11217     12    8  1985        4         OL    M             24.0   \n",
       "11217      11218     12    8  1985        9         DM    F             36.0   \n",
       "11218      11219     12    8  1985        8         DM    F             38.0   \n",
       "11219      11220     12    8  1985        5         DO    F             37.0   \n",
       "11220      11221     12    8  1985       13         AH  NaN              NaN   \n",
       "11221      11222     12    8  1985        7         AB  NaN              NaN   \n",
       "11222      11223     12    8  1985        4         DM    M             36.0   \n",
       "11223      11224     12    8  1985       11         DM    M             37.0   \n",
       "11224      11225     12    8  1985        7         PE    M             20.0   \n",
       "11225      11226     12    8  1985        1         DM    M             38.0   \n",
       "11226      11227     12    8  1985       15        NaN  NaN              NaN   \n",
       "\n",
       "       weight  \n",
       "2270     53.0  \n",
       "2271     10.0  \n",
       "2272     33.0  \n",
       "2273     37.0  \n",
       "2274     29.0  \n",
       "2275    132.0  \n",
       "2276      8.0  \n",
       "2277     23.0  \n",
       "2278     36.0  \n",
       "2279     21.0  \n",
       "2280     29.0  \n",
       "2281     49.0  \n",
       "2282     23.0  \n",
       "2283     32.0  \n",
       "2284     24.0  \n",
       "2285     47.0  \n",
       "2286     22.0  \n",
       "2287     12.0  \n",
       "2288    150.0  \n",
       "2289     49.0  \n",
       "2290     34.0  \n",
       "2291     40.0  \n",
       "2292    132.0  \n",
       "2293     25.0  \n",
       "2294     36.0  \n",
       "2295     50.0  \n",
       "2296     45.0  \n",
       "2297     47.0  \n",
       "2298     46.0  \n",
       "2299     29.0  \n",
       "...       ...  \n",
       "11197   129.0  \n",
       "11198    42.0  \n",
       "11199     NaN  \n",
       "11200    29.0  \n",
       "11201    39.0  \n",
       "11202    19.0  \n",
       "11203    16.0  \n",
       "11204    56.0  \n",
       "11205    38.0  \n",
       "11206    19.0  \n",
       "11207   120.0  \n",
       "11208    52.0  \n",
       "11209    40.0  \n",
       "11210    45.0  \n",
       "11211   121.0  \n",
       "11212     NaN  \n",
       "11213    44.0  \n",
       "11214   160.0  \n",
       "11215     9.0  \n",
       "11216    34.0  \n",
       "11217    39.0  \n",
       "11218    41.0  \n",
       "11219    56.0  \n",
       "11220     NaN  \n",
       "11221     NaN  \n",
       "11222    40.0  \n",
       "11223    49.0  \n",
       "11224    18.0  \n",
       "11225    47.0  \n",
       "11226     NaN  \n",
       "\n",
       "[8957 rows x 9 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "surveys_df[(surveys_df.year >= 1980) & (surveys_df.year <= 1985)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Python Syntax Cheat Sheet\n",
    "\n",
    "Use can use the syntax below when querying data by criteria from a DataFrame.\n",
    "Experiment with selecting various subsets of the \"surveys\" data.\n",
    "\n",
    "* Equals: `==`\n",
    "* Not equals: `!=`\n",
    "* Greater than, less than: `>` or `<`\n",
    "* Greater than or equal to `>=`\n",
    "* Less than or equal to `<=`\n",
    "\n",
    "\n",
    "> ## Challenge - Queries\n",
    ">\n",
    "> 1. Select a subset of rows in the `surveys_df` DataFrame that contain data from\n",
    ">   the year 1999 and that contain weight values less than or equal to 8. How\n",
    ">   many rows did you end up with? What did your neighbor get?\n",
    ">\n",
    "> 2. You can use the `isin` command in Python to query a DataFrame based upon a\n",
    ">   list of values as follows:\n",
    ">\n",
    ">    ```python\n",
    ">    surveys_df[surveys_df['species_id'].isin([listGoesHere])]\n",
    ">    ```\n",
    ">\n",
    ">   Use the `isin` function to find all plots that contain particular species\n",
    ">   in the \"surveys\" DataFrame. How many records contain these values?\n",
    ">\n",
    "> 3. Experiment with other queries. Create a query that finds all rows with a\n",
    ">   weight value > or equal to 0.\n",
    ">\n",
    "> 4. The `~` symbol in Python can be used to return the OPPOSITE of the\n",
    ">   selection that you specify in Python. It is equivalent to **is not in**.\n",
    ">   Write a query that selects all rows with sex NOT equal to 'M' or 'F' in\n",
    ">   the \"surveys\" data.\n",
    "\n",
    "# Using masks to identify a specific condition\n",
    "\n",
    "A **mask** can be useful to locate where a particular subset of values exist or\n",
    "don't exist - for example,  NaN, or \"Not a Number\" values. To understand masks,\n",
    "we also need to understand `BOOLEAN` objects in Python.\n",
    "\n",
    "Boolean values include `True` or `False`. For example,\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set x to 5\n",
    "x = 5\n",
    "\n",
    "# what does the code below return?\n",
    "x > 5\n",
    "\n",
    "# how about this?\n",
    "x == 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we ask Python what the value of `x > 5` is, we get `False`. This is\n",
    "because the condition,`x` is not greater than 5, is not met since `x` is equal\n",
    "to 5.\n",
    "\n",
    "To create a boolean mask:\n",
    "\n",
    "- Set the True / False criteria (e.g. `values > 5 = True`)\n",
    "- Python will then assess each value in the object to determine whether the\n",
    "  value meets the criteria (True) or not (False).\n",
    "- Python creates an output object that is the same shape as the original\n",
    "  object, but with a `True` or `False` value for each index location.\n",
    "\n",
    "Let's try this out. Let's identify all locations in the survey data that have\n",
    "null (missing or NaN) data values. We can use the `isnull` method to do this.\n",
    "The `isnull` method will compare each cell with a null value. If an element\n",
    "has a null value, it will be assigned a value of  `True` in the output object.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>record_id</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>year</th>\n",
       "      <th>plot_id</th>\n",
       "      <th>species_id</th>\n",
       "      <th>sex</th>\n",
       "      <th>hindfoot_length</th>\n",
       "      <th>weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35519</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35520</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35521</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35522</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35523</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35524</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35525</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35526</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35527</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35528</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35529</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35530</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35531</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35532</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35533</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35534</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35535</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35536</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35537</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35538</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>35540</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>35541</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>35543</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>True</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>35546</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>35547</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <th>35548</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>35549 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       record_id  month    day   year  plot_id  species_id    sex  \\\n",
       "0          False  False  False  False    False       False  False   \n",
       "1          False  False  False  False    False       False  False   \n",
       "2          False  False  False  False    False       False  False   \n",
       "3          False  False  False  False    False       False  False   \n",
       "4          False  False  False  False    False       False  False   \n",
       "5          False  False  False  False    False       False  False   \n",
       "6          False  False  False  False    False       False  False   \n",
       "7          False  False  False  False    False       False  False   \n",
       "8          False  False  False  False    False       False  False   \n",
       "9          False  False  False  False    False       False  False   \n",
       "10         False  False  False  False    False       False  False   \n",
       "11         False  False  False  False    False       False  False   \n",
       "12         False  False  False  False    False       False  False   \n",
       "13         False  False  False  False    False       False   True   \n",
       "14         False  False  False  False    False       False  False   \n",
       "15         False  False  False  False    False       False  False   \n",
       "16         False  False  False  False    False       False  False   \n",
       "17         False  False  False  False    False       False  False   \n",
       "18         False  False  False  False    False       False   True   \n",
       "19         False  False  False  False    False       False  False   \n",
       "20         False  False  False  False    False       False  False   \n",
       "21         False  False  False  False    False       False  False   \n",
       "22         False  False  False  False    False       False  False   \n",
       "23         False  False  False  False    False       False  False   \n",
       "24         False  False  False  False    False       False  False   \n",
       "25         False  False  False  False    False       False  False   \n",
       "26         False  False  False  False    False       False  False   \n",
       "27         False  False  False  False    False       False  False   \n",
       "28         False  False  False  False    False       False  False   \n",
       "29         False  False  False  False    False       False  False   \n",
       "...          ...    ...    ...    ...      ...         ...    ...   \n",
       "35519      False  False  False  False    False       False   True   \n",
       "35520      False  False  False  False    False       False  False   \n",
       "35521      False  False  False  False    False       False  False   \n",
       "35522      False  False  False  False    False       False  False   \n",
       "35523      False  False  False  False    False       False  False   \n",
       "35524      False  False  False  False    False       False  False   \n",
       "35525      False  False  False  False    False       False  False   \n",
       "35526      False  False  False  False    False       False  False   \n",
       "35527      False  False  False  False    False       False   True   \n",
       "35528      False  False  False  False    False       False  False   \n",
       "35529      False  False  False  False    False       False  False   \n",
       "35530      False  False  False  False    False       False  False   \n",
       "35531      False  False  False  False    False       False  False   \n",
       "35532      False  False  False  False    False       False  False   \n",
       "35533      False  False  False  False    False       False  False   \n",
       "35534      False  False  False  False    False       False  False   \n",
       "35535      False  False  False  False    False       False  False   \n",
       "35536      False  False  False  False    False       False  False   \n",
       "35537      False  False  False  False    False       False  False   \n",
       "35538      False  False  False  False    False       False  False   \n",
       "35539      False  False  False  False    False       False  False   \n",
       "35540      False  False  False  False    False       False  False   \n",
       "35541      False  False  False  False    False       False  False   \n",
       "35542      False  False  False  False    False       False  False   \n",
       "35543      False  False  False  False    False       False   True   \n",
       "35544      False  False  False  False    False       False   True   \n",
       "35545      False  False  False  False    False       False   True   \n",
       "35546      False  False  False  False    False       False  False   \n",
       "35547      False  False  False  False    False       False  False   \n",
       "35548      False  False  False  False    False        True   True   \n",
       "\n",
       "       hindfoot_length  weight  \n",
       "0                False    True  \n",
       "1                False    True  \n",
       "2                False    True  \n",
       "3                False    True  \n",
       "4                False    True  \n",
       "5                False    True  \n",
       "6                 True    True  \n",
       "7                False    True  \n",
       "8                False    True  \n",
       "9                False    True  \n",
       "10               False    True  \n",
       "11               False    True  \n",
       "12               False    True  \n",
       "13                True    True  \n",
       "14               False    True  \n",
       "15               False    True  \n",
       "16               False    True  \n",
       "17               False    True  \n",
       "18                True    True  \n",
       "19               False    True  \n",
       "20               False    True  \n",
       "21               False    True  \n",
       "22               False    True  \n",
       "23               False    True  \n",
       "24               False    True  \n",
       "25               False    True  \n",
       "26               False    True  \n",
       "27               False    True  \n",
       "28                True    True  \n",
       "29               False    True  \n",
       "...                ...     ...  \n",
       "35519            False   False  \n",
       "35520            False   False  \n",
       "35521            False   False  \n",
       "35522            False   False  \n",
       "35523            False   False  \n",
       "35524            False   False  \n",
       "35525            False   False  \n",
       "35526            False   False  \n",
       "35527             True    True  \n",
       "35528            False   False  \n",
       "35529            False    True  \n",
       "35530            False    True  \n",
       "35531            False   False  \n",
       "35532            False   False  \n",
       "35533            False   False  \n",
       "35534            False   False  \n",
       "35535            False   False  \n",
       "35536            False   False  \n",
       "35537            False   False  \n",
       "35538            False   False  \n",
       "35539            False   False  \n",
       "35540            False   False  \n",
       "35541            False   False  \n",
       "35542            False   False  \n",
       "35543             True    True  \n",
       "35544             True    True  \n",
       "35545             True    True  \n",
       "35546            False   False  \n",
       "35547            False   False  \n",
       "35548             True    True  \n",
       "\n",
       "[35549 rows x 9 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.isnull(surveys_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To select the rows where there are null values, we can use\n",
    "the mask as an index to subset our data as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>record_id</th>\n",
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       "      <td>1</td>\n",
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       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>15</td>\n",
       "      <td>NL</td>\n",
       "      <td>F</td>\n",
       "      <td>31.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>13</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>13</td>\n",
       "      <td>SH</td>\n",
       "      <td>M</td>\n",
       "      <td>21.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>9</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>35.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>15</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>31.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>15</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>36.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>11</td>\n",
       "      <td>DM</td>\n",
       "      <td>M</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>11</td>\n",
       "      <td>PP</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>7</td>\n",
       "      <td>17</td>\n",
       "      <td>1977</td>\n",
       "      <td>10</td>\n",
       "      <td>DS</td>\n",
       "      <td>F</td>\n",
       "      <td>52.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35187</th>\n",
       "      <td>35188</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>2002</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35256</th>\n",
       "      <td>35257</td>\n",
       "      <td>12</td>\n",
       "      <td>7</td>\n",
       "      <td>2002</td>\n",
       "      <td>22</td>\n",
       "      <td>PB</td>\n",
       "      <td>M</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35259</th>\n",
       "      <td>35260</td>\n",
       "      <td>12</td>\n",
       "      <td>7</td>\n",
       "      <td>2002</td>\n",
       "      <td>21</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>24.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35277</th>\n",
       "      <td>35278</td>\n",
       "      <td>12</td>\n",
       "      <td>7</td>\n",
       "      <td>2002</td>\n",
       "      <td>20</td>\n",
       "      <td>AH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35279</th>\n",
       "      <td>35280</td>\n",
       "      <td>12</td>\n",
       "      <td>7</td>\n",
       "      <td>2002</td>\n",
       "      <td>16</td>\n",
       "      <td>PB</td>\n",
       "      <td>M</td>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35322</th>\n",
       "      <td>35323</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>2002</td>\n",
       "      <td>11</td>\n",
       "      <td>AH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35328</th>\n",
       "      <td>35329</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>2002</td>\n",
       "      <td>11</td>\n",
       "      <td>PP</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35370</th>\n",
       "      <td>35371</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>2002</td>\n",
       "      <td>14</td>\n",
       "      <td>AH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35378</th>\n",
       "      <td>35379</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>26.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35384</th>\n",
       "      <td>35385</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>2002</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35387</th>\n",
       "      <td>35388</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "      <td>2002</td>\n",
       "      <td>1</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>35.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35403</th>\n",
       "      <td>35404</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>NL</td>\n",
       "      <td>F</td>\n",
       "      <td>30.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35448</th>\n",
       "      <td>35449</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "      <td>2002</td>\n",
       "      <td>20</td>\n",
       "      <td>OT</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35452</th>\n",
       "      <td>35453</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "      <td>2002</td>\n",
       "      <td>20</td>\n",
       "      <td>PB</td>\n",
       "      <td>M</td>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35457</th>\n",
       "      <td>35458</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "      <td>2002</td>\n",
       "      <td>20</td>\n",
       "      <td>AH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35477</th>\n",
       "      <td>35478</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "      <td>2002</td>\n",
       "      <td>24</td>\n",
       "      <td>AH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35485</th>\n",
       "      <td>35486</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "      <td>2002</td>\n",
       "      <td>16</td>\n",
       "      <td>DO</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35495</th>\n",
       "      <td>35496</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>4</td>\n",
       "      <td>PB</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35510</th>\n",
       "      <td>35511</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>11</td>\n",
       "      <td>DX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35511</th>\n",
       "      <td>35512</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>11</td>\n",
       "      <td>US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35512</th>\n",
       "      <td>35513</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>11</td>\n",
       "      <td>US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35514</th>\n",
       "      <td>35515</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>11</td>\n",
       "      <td>SF</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35519</th>\n",
       "      <td>35520</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>9</td>\n",
       "      <td>SF</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.0</td>\n",
       "      <td>36.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35527</th>\n",
       "      <td>35528</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>13</td>\n",
       "      <td>US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35529</th>\n",
       "      <td>35530</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>13</td>\n",
       "      <td>OT</td>\n",
       "      <td>F</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35530</th>\n",
       "      <td>35531</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>13</td>\n",
       "      <td>PB</td>\n",
       "      <td>F</td>\n",
       "      <td>27.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35543</th>\n",
       "      <td>35544</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35544</th>\n",
       "      <td>35545</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>AH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35545</th>\n",
       "      <td>35546</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>15</td>\n",
       "      <td>AH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35548</th>\n",
       "      <td>35549</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>2002</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4873 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       record_id  month  day  year  plot_id species_id  sex  hindfoot_length  \\\n",
       "0              1      7   16  1977        2         NL    M             32.0   \n",
       "1              2      7   16  1977        3         NL    M             33.0   \n",
       "2              3      7   16  1977        2         DM    F             37.0   \n",
       "3              4      7   16  1977        7         DM    M             36.0   \n",
       "4              5      7   16  1977        3         DM    M             35.0   \n",
       "5              6      7   16  1977        1         PF    M             14.0   \n",
       "6              7      7   16  1977        2         PE    F              NaN   \n",
       "7              8      7   16  1977        1         DM    M             37.0   \n",
       "8              9      7   16  1977        1         DM    F             34.0   \n",
       "9             10      7   16  1977        6         PF    F             20.0   \n",
       "10            11      7   16  1977        5         DS    F             53.0   \n",
       "11            12      7   16  1977        7         DM    M             38.0   \n",
       "12            13      7   16  1977        3         DM    M             35.0   \n",
       "13            14      7   16  1977        8         DM  NaN              NaN   \n",
       "14            15      7   16  1977        6         DM    F             36.0   \n",
       "15            16      7   16  1977        4         DM    F             36.0   \n",
       "16            17      7   16  1977        3         DS    F             48.0   \n",
       "17            18      7   16  1977        2         PP    M             22.0   \n",
       "18            19      7   16  1977        4         PF  NaN              NaN   \n",
       "19            20      7   17  1977       11         DS    F             48.0   \n",
       "20            21      7   17  1977       14         DM    F             34.0   \n",
       "21            22      7   17  1977       15         NL    F             31.0   \n",
       "22            23      7   17  1977       13         DM    M             36.0   \n",
       "23            24      7   17  1977       13         SH    M             21.0   \n",
       "24            25      7   17  1977        9         DM    M             35.0   \n",
       "25            26      7   17  1977       15         DM    M             31.0   \n",
       "26            27      7   17  1977       15         DM    M             36.0   \n",
       "27            28      7   17  1977       11         DM    M             38.0   \n",
       "28            29      7   17  1977       11         PP    M              NaN   \n",
       "29            30      7   17  1977       10         DS    F             52.0   \n",
       "...          ...    ...  ...   ...      ...        ...  ...              ...   \n",
       "35187      35188     11   10  2002       10        NaN  NaN              NaN   \n",
       "35256      35257     12    7  2002       22         PB    M             26.0   \n",
       "35259      35260     12    7  2002       21         PB    F             24.0   \n",
       "35277      35278     12    7  2002       20         AH  NaN              NaN   \n",
       "35279      35280     12    7  2002       16         PB    M             28.0   \n",
       "35322      35323     12    8  2002       11         AH  NaN              NaN   \n",
       "35328      35329     12    8  2002       11         PP    M              NaN   \n",
       "35370      35371     12    8  2002       14         AH  NaN              NaN   \n",
       "35378      35379     12    8  2002       15         PB    F             26.0   \n",
       "35384      35385     12    8  2002       10        NaN  NaN              NaN   \n",
       "35387      35388     12   29  2002        1         DO    M             35.0   \n",
       "35403      35404     12   29  2002        2         NL    F             30.0   \n",
       "35448      35449     12   29  2002       20         OT    F             20.0   \n",
       "35452      35453     12   29  2002       20         PB    M             28.0   \n",
       "35457      35458     12   29  2002       20         AH  NaN              NaN   \n",
       "35477      35478     12   29  2002       24         AH  NaN              NaN   \n",
       "35485      35486     12   29  2002       16         DO    M             37.0   \n",
       "35495      35496     12   31  2002        4         PB  NaN              NaN   \n",
       "35510      35511     12   31  2002       11         DX  NaN              NaN   \n",
       "35511      35512     12   31  2002       11         US  NaN              NaN   \n",
       "35512      35513     12   31  2002       11         US  NaN              NaN   \n",
       "35514      35515     12   31  2002       11         SF    F             27.0   \n",
       "35519      35520     12   31  2002        9         SF  NaN             24.0   \n",
       "35527      35528     12   31  2002       13         US  NaN              NaN   \n",
       "35529      35530     12   31  2002       13         OT    F             20.0   \n",
       "35530      35531     12   31  2002       13         PB    F             27.0   \n",
       "35543      35544     12   31  2002       15         US  NaN              NaN   \n",
       "35544      35545     12   31  2002       15         AH  NaN              NaN   \n",
       "35545      35546     12   31  2002       15         AH  NaN              NaN   \n",
       "35548      35549     12   31  2002        5        NaN  NaN              NaN   \n",
       "\n",
       "       weight  \n",
       "0         NaN  \n",
       "1         NaN  \n",
       "2         NaN  \n",
       "3         NaN  \n",
       "4         NaN  \n",
       "5         NaN  \n",
       "6         NaN  \n",
       "7         NaN  \n",
       "8         NaN  \n",
       "9         NaN  \n",
       "10        NaN  \n",
       "11        NaN  \n",
       "12        NaN  \n",
       "13        NaN  \n",
       "14        NaN  \n",
       "15        NaN  \n",
       "16        NaN  \n",
       "17        NaN  \n",
       "18        NaN  \n",
       "19        NaN  \n",
       "20        NaN  \n",
       "21        NaN  \n",
       "22        NaN  \n",
       "23        NaN  \n",
       "24        NaN  \n",
       "25        NaN  \n",
       "26        NaN  \n",
       "27        NaN  \n",
       "28        NaN  \n",
       "29        NaN  \n",
       "...       ...  \n",
       "35187     NaN  \n",
       "35256     NaN  \n",
       "35259     NaN  \n",
       "35277     NaN  \n",
       "35279     NaN  \n",
       "35322     NaN  \n",
       "35328    16.0  \n",
       "35370     NaN  \n",
       "35378     NaN  \n",
       "35384     NaN  \n",
       "35387     NaN  \n",
       "35403     NaN  \n",
       "35448     NaN  \n",
       "35452     NaN  \n",
       "35457     NaN  \n",
       "35477     NaN  \n",
       "35485     NaN  \n",
       "35495     NaN  \n",
       "35510     NaN  \n",
       "35511     NaN  \n",
       "35512     NaN  \n",
       "35514     NaN  \n",
       "35519    36.0  \n",
       "35527     NaN  \n",
       "35529     NaN  \n",
       "35530     NaN  \n",
       "35543     NaN  \n",
       "35544     NaN  \n",
       "35545     NaN  \n",
       "35548     NaN  \n",
       "\n",
       "[4873 rows x 9 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To select just the rows with NaN values, we can use the 'any()' method\n",
    "surveys_df[pd.isnull(surveys_df).any(axis=1)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the `weight` column of our DataFrame contains many `null` or `NaN`\n",
    "values. We will explore ways of dealing with this in Lesson 03.\n",
    "\n",
    "We can run `isnull` on a particular column too. What does the code below do?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0       NaN\n",
      "1       NaN\n",
      "2       NaN\n",
      "3       NaN\n",
      "4       NaN\n",
      "5       NaN\n",
      "6       NaN\n",
      "7       NaN\n",
      "8       NaN\n",
      "9       NaN\n",
      "10      NaN\n",
      "11      NaN\n",
      "12      NaN\n",
      "13      NaN\n",
      "14      NaN\n",
      "15      NaN\n",
      "16      NaN\n",
      "17      NaN\n",
      "18      NaN\n",
      "19      NaN\n",
      "20      NaN\n",
      "21      NaN\n",
      "22      NaN\n",
      "23      NaN\n",
      "24      NaN\n",
      "25      NaN\n",
      "26      NaN\n",
      "27      NaN\n",
      "28      NaN\n",
      "29      NaN\n",
      "         ..\n",
      "35138   NaN\n",
      "35168   NaN\n",
      "35187   NaN\n",
      "35256   NaN\n",
      "35259   NaN\n",
      "35277   NaN\n",
      "35279   NaN\n",
      "35322   NaN\n",
      "35370   NaN\n",
      "35378   NaN\n",
      "35384   NaN\n",
      "35387   NaN\n",
      "35403   NaN\n",
      "35448   NaN\n",
      "35452   NaN\n",
      "35457   NaN\n",
      "35477   NaN\n",
      "35485   NaN\n",
      "35495   NaN\n",
      "35510   NaN\n",
      "35511   NaN\n",
      "35512   NaN\n",
      "35514   NaN\n",
      "35527   NaN\n",
      "35529   NaN\n",
      "35530   NaN\n",
      "35543   NaN\n",
      "35544   NaN\n",
      "35545   NaN\n",
      "35548   NaN\n",
      "Name: weight, Length: 3266, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# what does this do?\n",
    "empty_weights = surveys_df[pd.isnull(surveys_df['weight'])]['weight']\n",
    "print(empty_weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a minute to look at the statement above. We are using the Boolean\n",
    "object `pd.isnull(surveys_df['weight'])` as an index to `surveys_df`. We are\n",
    "asking Python to select rows that have a `NaN` value of weight.\n",
    "\n",
    "\n",
    "> ## Challenge - Putting it all together\n",
    ">\n",
    "> 1. Create a new DataFrame that only contains observations with sex values that\n",
    ">   are **not** female or male. Assign each sex value in the new DataFrame to a\n",
    ">   new value of 'x'. Determine the number of null values in the subset.\n",
    ">   \n",
    "> 2. Create a new DataFrame that contains only observations that are of sex male\n",
    ">   or female and where weight values are greater than 0. Create a stacked bar\n",
    ">   plot of average weight by plot with male vs female values stacked for each\n",
    ">   plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nosex_df = surveys_df[~surveys_df['sex'].isin(['M', 'F'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sex_df = surveys_df[surveys_df['sex'].isin(['M', 'F']) \\\n",
    "                    & surveys_df['weight']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped = sex_df.groupby(['plot_id', 'sex'])['weight']\n",
    "grouped.mean().unstack().plot(kind='bar', stacked='True')"
   ]
  }
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