Messy Sensor Data - A Programmer's Cleaning Guide.ipynb

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    "# Note to presentation mode: run the first two cells before presenting.\n",
    "# Render our plots inline\n",
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Make the graphs a bit prettier\n",
    "matplotlib.style.use('ggplot')\n",
    "plt.rcParams['figure.figsize'] = (18, 5)"
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   "source": [
    "# Messy Sensor Data:\n",
    "## A Programmer's Cleaning Guide\n",
    "* * *\n",
    "*@Xavier_Ho*, #pyconau\n",
    "\n",
    "<small>*Feel free to tag me on Twitter for questions and comments.*</small>"
   ]
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   "source": [
    "# Related #pyconau talks\n",
    "\n",
    "This talk is a tutorial (thanks @evildmp!) for cleaning up messy data with `pandas`. You might also find these other ones useful:\n",
    "\n",
    " * [**Using Python in a Data Hackathon**](https://www.youtube.com/watch?v=Ck1Ns6D3rZc&list=PLs4CJRBY5F1KsK4AbFaPsUT8X8iXc7X84&index=21) - Tennessee Leeuwenburg\n",
    " * [**Visualising data with Python**](https://www.youtube.com/watch?v=6d3Yk7a2qYI&list=PLs4CJRBY5F1KsK4AbFaPsUT8X8iXc7X84&index=35) - Clare Sloggett\n",
    "\n",
    "Slides will be available online.\n",
    " \n",
    "There will be time for questions at the end - happy to navigate specific problems you may have."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Motivation: healthy water"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "* Aquatic microorganisms thrive and die with seasonal temperatures."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "* Cyanobacteria, or \"blue-green algae\", produces oxygen in water."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "* Too much cyanobacteria in water is harmful to consume."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "* We model cyanobacteria in water with weather data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "*In short: we can predict and track cyanobacteria, and keep our water healthy.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let's take a look at our weather sensor data..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "In this talk, we use `pandas` for data wrangling.\n",
    "\n",
    "You can install it with your favourite package manager ([instructions](http://pandas.pydata.org/pandas-docs/stable/install.html)).\n",
    "\n",
    "```$ conda install pandas```\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "To begin:\n",
    " * `pandas.read_csv()`: Opens a CSV file as a **DataFrame**, like a table.\n",
    " * `DataFrame.head()`: Displays the first 5 entries."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Read a CSV file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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       "      <th></th>\n",
       "      <th>Date\\tTime\\tWind dir\\tWind spd\\tWind gust\\tTmp\\tDew pt\\tFeels like\\trh\\tFire\\tRain\\tRain 10'\\tPres</th>\n",
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       "      <td>01/01/2013\\tWed 00:00 EDT\\tWNW\\t9\\t9\\t19.6\\t0....</td>\n",
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       "    <tr>\n",
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       "      <td>01/01/2013\\tTue 23:30 EDT\\tWNW\\t-\\t13\\t20.7\\t0...</td>\n",
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       "  Date\\tTime\\tWind dir\\tWind spd\\tWind gust\\tTmp\\tDew pt\\tFeels like\\trh\\tFire\\tRain\\tRain 10'\\tPres\n",
       "0  01/01/2013\\tWed 00:00 EDT\\tWNW\\t9\\t9\\t19.6\\t0....                                                \n",
       "1  01/01/2013\\tTue 23:30 EDT\\tWNW\\t-\\t13\\t20.7\\t0...                                                \n",
       "2  01/01/2013\\tTue 23:00 EDT\\tW\\t9\\t11\\t22.8\\t0.9...                                                \n",
       "3  01/01/2013\\tTue 22:30 EDT\\tWNW\\t11\\t13\\t22.6\\t...                                                \n",
       "4  01/01/2013\\tTue 22:00 EDT\\tWNW\\t15\\t19\\t23.9\\t...                                                "
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   "source": [
    "import pandas as pd\n",
    "\n",
    "# Open a comma-separated values (CSV) file as a DataFrame\n",
    "weather_observations = pd.read_csv('observations/Canberra_observations.csv')\n",
    "\n",
    "# Print the first 5 entries\n",
    "weather_observations.head()"
   ]
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  {
   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "fragment"
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   "source": [
    "The file seems to be tab seperated. There are dates, and some empty items. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Can we read it more clearly?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "[`pandas.read_csv()`](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html?highlight=read_csv#pandas.read_csv) is very versatile with keyword arguments."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "fragment"
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   },
   "source": [
    " * `sep`: The separator between columns."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    " * `parse_dates`: Treat one or more columns like dates.\n",
    " * `dayfirst`: Use DD.MM.YYYY format, not month first.\n",
    " * `infer_datetime_format`: Tell pandas to guess the date format."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    " * `na_values`: Specify values to be treated as empty."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Read a CSV file the 🐼🐼 way"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
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       "  Date\\tTime\\tWind dir\\tWind spd\\tWind gust\\tTmp\\tDew pt\\tFeels like\\trh\\tFire\\tRain\\tRain 10'\\tPres\n",
       "0  01/01/2013\\tWed 00:00 EDT\\tWNW\\t9\\t9\\t19.6\\t0....                                                \n",
       "1  01/01/2013\\tTue 23:30 EDT\\tWNW\\t-\\t13\\t20.7\\t0...                                                \n",
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   "source": [
    "# Supply pandas with some hints about the file to read\n",
    "weather_observations = pd.read_csv('observations/Canberra_observations.csv',\n",
    "#                                    sep='\\t',\n",
    "#                                    parse_dates={'Datetime': ['Date', 'Time']},\n",
    "#                                    dayfirst=True,\n",
    "#                                    infer_datetime_format=True,\n",
    "#                                    na_values=['-'],\n",
    "                                  )\n",
    "# Display some entries\n",
    "weather_observations.head()"
   ]
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    "Note: `NaN` in the table above means **empty**, *not the floating-point number value*."
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      "c:\\users\\conta\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\dateutil\\parser\\_parser.py:1213: UnknownTimezoneWarning: tzname EDT identified but not understood.  Pass `tzinfos` argument in order to correctly return a timezone-aware datetime.  In a future version, this will raise an exception.\n",
      "  warnings.warn(\"tzname {tzname} identified but not understood.  \"\n",
      "c:\\users\\conta\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\dateutil\\parser\\_parser.py:1213: UnknownTimezoneWarning: tzname EST identified but not understood.  Pass `tzinfos` argument in order to correctly return a timezone-aware datetime.  In a future version, this will raise an exception.\n",
      "  warnings.warn(\"tzname {tzname} identified but not understood.  \"\n"
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       "      <th>0</th>\n",
       "      <td>2013-01-01 00:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>19.6</td>\n",
       "      <td>0.1</td>\n",
       "      <td>19.6</td>\n",
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       "      <td>12.0</td>\n",
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       "      <td>13.0</td>\n",
       "      <td>20.7</td>\n",
       "      <td>0.7</td>\n",
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       "      <td>26.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>2013-01-01 23:00:00</td>\n",
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       "      <td>9.0</td>\n",
       "      <td>11.0</td>\n",
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       "      <td>11.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>22.6</td>\n",
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       "      <td>22.6</td>\n",
       "      <td>21.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>2013-01-01 22:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>15.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>23.9</td>\n",
       "      <td>-2.2</td>\n",
       "      <td>23.9</td>\n",
       "      <td>18.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1011.1</td>\n",
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      "text/plain": [
       "             Datetime Wind dir  Wind spd  Wind gust   Tmp  Dew pt  Feels like  \\\n",
       "0 2013-01-01 00:00:00      WNW       9.0        9.0  19.6     0.1        19.6   \n",
       "1 2013-01-01 23:30:00      WNW       NaN       13.0  20.7     0.7        20.7   \n",
       "2 2013-01-01 23:00:00        W       9.0       11.0  22.8     0.9        22.8   \n",
       "3 2013-01-01 22:30:00      WNW      11.0       13.0  22.6    -1.0        22.6   \n",
       "4 2013-01-01 22:00:00      WNW      15.0       19.0  23.9    -2.2        23.9   \n",
       "\n",
       "     rh  Fire  Rain  Rain 10'    Pres  \n",
       "0  27.0  12.0   0.0       0.0  1011.4  \n",
       "1  26.0  13.0   0.0       0.0  1011.1  \n",
       "2  23.0  15.0   0.0       0.0  1011.0  \n",
       "3  21.0  17.0   0.0       0.0  1011.0  \n",
       "4  18.0  21.0   0.0       0.0  1011.1  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# For consistency between slides\n",
    "weather_observations = pd.read_csv('observations/Canberra_observations.csv',\n",
    "                                   sep='\\t',\n",
    "                                   parse_dates={'Datetime': ['Date', 'Time']},\n",
    "                                   dayfirst=True,\n",
    "                                   infer_datetime_format=True,\n",
    "                                   na_values=['-']\n",
    "                                  )\n",
    "weather_observations.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Small steps in data cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The data seems complete, but still has some issues:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "* Each day includes midnight, and another midnight next day.\n",
    "* Order starts at end of day and goes backwards in time."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "`pandas` offers some functions to help us out:\n",
    " * `DataFrame.drop_duplicates()`: Delete duplicated items.\n",
    " * `DataFrame.sort_values()`: Rearrange in order.\n",
    " * `DataFrame.set_index()`: Specify a column to use as index."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Keep order in our data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Datetime</th>\n",
       "      <th>Wind dir</th>\n",
       "      <th>Wind spd</th>\n",
       "      <th>Wind gust</th>\n",
       "      <th>Tmp</th>\n",
       "      <th>Dew pt</th>\n",
       "      <th>Feels like</th>\n",
       "      <th>rh</th>\n",
       "      <th>Fire</th>\n",
       "      <th>Rain</th>\n",
       "      <th>Rain 10'</th>\n",
       "      <th>Pres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-01-01 00:00:00</td>\n",
       "      <td>WNW</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>19.6</td>\n",
       "      <td>0.1</td>\n",
       "      <td>19.6</td>\n",
       "      <td>27.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2013-01-01 00:00:00</td>\n",
       "      <td>ENE</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>15.9</td>\n",
       "      <td>3.7</td>\n",
       "      <td>15.9</td>\n",
       "      <td>44.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1014.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2013-01-01 00:30:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.5</td>\n",
       "      <td>4.7</td>\n",
       "      <td>14.5</td>\n",
       "      <td>52.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1014.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2013-01-01 01:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.8</td>\n",
       "      <td>4.6</td>\n",
       "      <td>12.8</td>\n",
       "      <td>57.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1013.5</td>\n",
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       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2013-01-01 01:30:00</td>\n",
       "      <td>SSW</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.3</td>\n",
       "      <td>5.9</td>\n",
       "      <td>13.3</td>\n",
       "      <td>61.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1013.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Datetime Wind dir  Wind spd  Wind gust   Tmp  Dew pt  \\\n",
       "0  2013-01-01 00:00:00      WNW       9.0        9.0  19.6     0.1   \n",
       "50 2013-01-01 00:00:00      ENE       2.0        6.0  15.9     3.7   \n",
       "49 2013-01-01 00:30:00      NaN       0.0        0.0  14.5     4.7   \n",
       "48 2013-01-01 01:00:00      NaN       0.0        0.0  12.8     4.6   \n",
       "47 2013-01-01 01:30:00      SSW       6.0        9.0  13.3     5.9   \n",
       "\n",
       "    Feels like    rh  Fire  Rain  Rain 10'    Pres  \n",
       "0         19.6  27.0  12.0   0.0       0.0  1011.4  \n",
       "50        15.9  44.0   5.0   0.0       0.0  1014.1  \n",
       "49        14.5  52.0   3.0   0.0       0.0  1014.0  \n",
       "48        12.8  57.0   3.0   0.0       0.0  1013.5  \n",
       "47        13.3  61.0   3.0   0.0       0.0  1013.4  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove duplicated items with the same date and time\n",
    "# no_duplicates = weather_observations.drop_duplicates('Datetime', keep='last')\n",
    "\n",
    "# Sorting is ascending by default, or chronological order\n",
    "sorted_dataframe = weather_observations.sort_values('Datetime')\n",
    "\n",
    "# Use `Datetime` as our DataFrame index\n",
    "indexed_weather_observations = sorted_dataframe.set_index('Datetime')\n",
    "\n",
    "# Display some entries\n",
    "sorted_dataframe.head()\n",
    "# no_duplicates.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# For consistency\n",
    "no_duplicates = weather_observations.drop_duplicates('Datetime', keep='last')\n",
    "sorted_dataframe = no_duplicates.sort_values('Datetime')\n",
    "indexed_weather_observations = sorted_dataframe.set_index('Datetime')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Let wind be numbers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "To process wind direction, we need them in numbers.\n",
    " * North wind (↓) is 0 degrees, going clockwise ⟳.\n",
    " * East wind (←) is 90 degrees."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "We need to transform each direction label \"N\", \"NNE\", \"NE\", \"ENE\", \"E\", etc., to numbers on the column.\n",
    "\n",
    "`Series.apply()`: Transforms each entry with a function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Transforming DataFrames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "# Translate wind direction to degrees\n",
    "wind_directions = {\n",
    "     'N':   0. , 'NNE':  22.5, 'NE':  45. , 'ENE':  67.5 ,\n",
    "     'E':  90. , 'ESE': 112.5, 'SE': 135. , 'SSE': 157.5 ,\n",
    "     'S': 180. , 'SSW': 202.5, 'SW': 225. , 'WSW': 247.5 ,\n",
    "     'W': 270. , 'WNW': 292.5, 'NW': 315. , 'NNW': 337.5 }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
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       "      <th>Wind spd</th>\n",
       "      <th>Wind gust</th>\n",
       "      <th>Tmp</th>\n",
       "      <th>Dew pt</th>\n",
       "      <th>Feels like</th>\n",
       "      <th>rh</th>\n",
       "      <th>Fire</th>\n",
       "      <th>Rain</th>\n",
       "      <th>Rain 10'</th>\n",
       "      <th>Pres</th>\n",
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       "      <td>12.8</td>\n",
       "      <td>4.6</td>\n",
       "      <td>12.8</td>\n",
       "      <td>57.0</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <th>2013-01-01 01:30:00</th>\n",
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       "      <td>9.0</td>\n",
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       "      <td>5.9</td>\n",
       "      <td>13.3</td>\n",
       "      <td>61.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1013.4</td>\n",
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       "    <tr>\n",
       "      <th>2013-01-01 02:00:00</th>\n",
       "      <td>225.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>4.7</td>\n",
       "      <td>12.5</td>\n",
       "      <td>59.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1013.2</td>\n",
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      ],
      "text/plain": [
       "                     Wind dir  Wind spd  Wind gust   Tmp  Dew pt  Feels like  \\\n",
       "Datetime                                                                       \n",
       "2013-01-01 00:00:00      67.5       2.0        6.0  15.9     3.7        15.9   \n",
       "2013-01-01 00:30:00       NaN       0.0        0.0  14.5     4.7        14.5   \n",
       "2013-01-01 01:00:00       NaN       0.0        0.0  12.8     4.6        12.8   \n",
       "2013-01-01 01:30:00     202.5       6.0        9.0  13.3     5.9        13.3   \n",
       "2013-01-01 02:00:00     225.0       2.0        7.0  12.5     4.7        12.5   \n",
       "\n",
       "                       rh  Fire  Rain  Rain 10'    Pres  \n",
       "Datetime                                                 \n",
       "2013-01-01 00:00:00  44.0   5.0   0.0       0.0  1014.1  \n",
       "2013-01-01 00:30:00  52.0   3.0   0.0       0.0  1014.0  \n",
       "2013-01-01 01:00:00  57.0   3.0   0.0       0.0  1013.5  \n",
       "2013-01-01 01:30:00  61.0   3.0   0.0       0.0  1013.4  \n",
       "2013-01-01 02:00:00  59.0   3.0   0.0       0.0  1013.2  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Replace wind directions column with a new number column\n",
    "# `get()` accesses values safely from dictionary\n",
    "indexed_weather_observations['Wind dir'] = \\\n",
    "    indexed_weather_observations['Wind dir'].apply(wind_directions.get)\n",
    "    \n",
    "# Display some entries\n",
    "indexed_weather_observations.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Irregular data frequency"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Our data has odd timestamps from time to time, For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
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       "      <td>67.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>15.4</td>\n",
       "      <td>12.9</td>\n",
       "      <td>15.4</td>\n",
       "      <td>85.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-04 02:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.7</td>\n",
       "      <td>13.1</td>\n",
       "      <td>14.7</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1019.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Wind dir  Wind spd  Wind gust   Tmp  Dew pt  Feels like  \\\n",
       "Datetime                                                                       \n",
       "2013-02-04 00:30:00      67.5       9.0       15.0  15.1    12.6        15.1   \n",
       "2013-02-04 00:33:00      67.5       7.0       11.0  15.0    12.7        15.0   \n",
       "2013-02-04 01:00:00      67.5       6.0        9.0  14.9    12.8        14.9   \n",
       "2013-02-04 01:11:00      45.0       4.0        7.0  15.0    12.9        15.0   \n",
       "2013-02-04 01:30:00      67.5       6.0        7.0  15.4    12.9        15.4   \n",
       "2013-02-04 02:00:00       NaN       0.0        0.0  14.7    13.1        14.7   \n",
       "\n",
       "                       rh  Fire  Rain  Rain 10'    Pres  \n",
       "Datetime                                                 \n",
       "2013-02-04 00:30:00  85.0   1.0   0.0       0.0  1020.2  \n",
       "2013-02-04 00:33:00  86.0   1.0   0.0       0.0  1020.2  \n",
       "2013-02-04 01:00:00  87.0   1.0   0.0       0.0  1020.2  \n",
       "2013-02-04 01:11:00  87.0   1.0   0.0       0.0  1020.1  \n",
       "2013-02-04 01:30:00  85.0   1.0   0.0       0.0  1020.0  \n",
       "2013-02-04 02:00:00  90.0   1.0   0.0       0.0  1019.9  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# One section where the data has weird timestamps ...\n",
    "indexed_weather_observations[1800:1806]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "We can solve this. [`DataFrame.asfreq()`](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.asfreq.html?highlight=asfreq#pandas.DataFrame.asfreq) forces a specific frequency on the index, discarding and filling the rest."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Setting data frequency"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's set each data point to be every 30 minutes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "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>Wind dir</th>\n",
       "      <th>Wind spd</th>\n",
       "      <th>Wind gust</th>\n",
       "      <th>Tmp</th>\n",
       "      <th>Dew pt</th>\n",
       "      <th>Feels like</th>\n",
       "      <th>rh</th>\n",
       "      <th>Fire</th>\n",
       "      <th>Rain</th>\n",
       "      <th>Rain 10'</th>\n",
       "      <th>Pres</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-02-04 00:30:00</th>\n",
       "      <td>67.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.1</td>\n",
       "      <td>12.6</td>\n",
       "      <td>15.1</td>\n",
       "      <td>85.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1020.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-04 01:00:00</th>\n",
       "      <td>67.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>14.9</td>\n",
       "      <td>12.8</td>\n",
       "      <td>14.9</td>\n",
       "      <td>87.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1020.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-04 01:30:00</th>\n",
       "      <td>67.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>15.4</td>\n",
       "      <td>12.9</td>\n",
       "      <td>15.4</td>\n",
       "      <td>85.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-04 02:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.7</td>\n",
       "      <td>13.1</td>\n",
       "      <td>14.7</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1019.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-04 02:30:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.6</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.6</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1019.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Wind dir  Wind spd  Wind gust   Tmp  Dew pt  Feels like  \\\n",
       "Datetime                                                                       \n",
       "2013-02-04 00:30:00      67.5       9.0       15.0  15.1    12.6        15.1   \n",
       "2013-02-04 01:00:00      67.5       6.0        9.0  14.9    12.8        14.9   \n",
       "2013-02-04 01:30:00      67.5       6.0        7.0  15.4    12.9        15.4   \n",
       "2013-02-04 02:00:00       NaN       0.0        0.0  14.7    13.1        14.7   \n",
       "2013-02-04 02:30:00       NaN       0.0        0.0  14.6    13.0        14.6   \n",
       "\n",
       "                       rh  Fire  Rain  Rain 10'    Pres  \n",
       "Datetime                                                 \n",
       "2013-02-04 00:30:00  85.0   1.0   0.0       0.0  1020.2  \n",
       "2013-02-04 01:00:00  87.0   1.0   0.0       0.0  1020.2  \n",
       "2013-02-04 01:30:00  85.0   1.0   0.0       0.0  1020.0  \n",
       "2013-02-04 02:00:00  90.0   1.0   0.0       0.0  1019.9  \n",
       "2013-02-04 02:30:00  90.0   1.0   0.0       0.0  1019.9  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Force the index to be every 30 minutes\n",
    "regular_observations = indexed_weather_observations.asfreq('30min')\n",
    "    \n",
    "# Same section at different indices since setting its frequency :)\n",
    "regular_observations[1633:1638]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Plotting some data for a better picture"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Datetime'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the first 500 entries with selected columns\n",
    "regular_observations[['Wind spd', 'Wind gust', 'Tmp', 'Feels like']][:500].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "There seems to be gaps in our dataset between 4th Jan and 9th Jan."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Gaps in the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Weather sensors sometimes drop out. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "But for modelling purposes, we need a gap-free dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "`Series.interpolate()`: Fill in empty values based on index. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Interpolate and fill empty rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "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>Wind dir</th>\n",
       "      <th>Wind spd</th>\n",
       "      <th>Wind gust</th>\n",
       "      <th>Tmp</th>\n",
       "      <th>Dew pt</th>\n",
       "      <th>Feels like</th>\n",
       "      <th>rh</th>\n",
       "      <th>Fire</th>\n",
       "      <th>Rain</th>\n",
       "      <th>Rain 10'</th>\n",
       "      <th>Pres</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-02-04 00:30:00</th>\n",
       "      <td>67.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.1</td>\n",
       "      <td>12.6</td>\n",
       "      <td>15.1</td>\n",
       "      <td>85.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1020.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-04 01:00:00</th>\n",
       "      <td>67.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>14.9</td>\n",
       "      <td>12.8</td>\n",
       "      <td>14.9</td>\n",
       "      <td>87.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1020.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-04 01:30:00</th>\n",
       "      <td>67.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>15.4</td>\n",
       "      <td>12.9</td>\n",
       "      <td>15.4</td>\n",
       "      <td>85.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-04 02:00:00</th>\n",
       "      <td>67.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.7</td>\n",
       "      <td>13.1</td>\n",
       "      <td>14.7</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1019.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-04 02:30:00</th>\n",
       "      <td>67.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.6</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.6</td>\n",
       "      <td>90.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1019.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Wind dir  Wind spd  Wind gust   Tmp  Dew pt  Feels like  \\\n",
       "Datetime                                                                       \n",
       "2013-02-04 00:30:00      67.5       9.0       15.0  15.1    12.6        15.1   \n",
       "2013-02-04 01:00:00      67.5       6.0        9.0  14.9    12.8        14.9   \n",
       "2013-02-04 01:30:00      67.5       6.0        7.0  15.4    12.9        15.4   \n",
       "2013-02-04 02:00:00      67.5       0.0        0.0  14.7    13.1        14.7   \n",
       "2013-02-04 02:30:00      67.5       0.0        0.0  14.6    13.0        14.6   \n",
       "\n",
       "                       rh  Fire  Rain  Rain 10'    Pres  \n",
       "Datetime                                                 \n",
       "2013-02-04 00:30:00  85.0   1.0   0.0       0.0  1020.2  \n",
       "2013-02-04 01:00:00  87.0   1.0   0.0       0.0  1020.2  \n",
       "2013-02-04 01:30:00  85.0   1.0   0.0       0.0  1020.0  \n",
       "2013-02-04 02:00:00  90.0   1.0   0.0       0.0  1019.9  \n",
       "2013-02-04 02:30:00  90.0   1.0   0.0       0.0  1019.9  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Interpolate data to fill empty values\n",
    "for column in regular_observations.columns:\n",
    "    regular_observations[column].interpolate('time', inplace=True)\n",
    "\n",
    "# Display some interpolated entries    \n",
    "regular_observations[1633:1638]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Plotting to be sure!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Datetime'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot it again - gap free!\n",
    "regular_observations[['Wind spd', 'Wind gust', 'Tmp', 'Feels like']][:500].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Now the dataset is ready to be used for modelling! 🎉"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# You too can keep our water healthy 🐹 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Today you learned how to use `pandas` to in many ways:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    " * Reading a CSV file with proper structures\n",
    " * Sorting your dataset\n",
    " * Transforming columns by applying a function\n",
    " * Regulate data frequency from odd ones\n",
    " * Interpolate and fill missing data\n",
    " * Plotting your dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "`pandas` is much more powerful than what we covered today. [Check out the documentation](http://pandas.pydata.org/pandas-docs/stable/index.html)! You might find some gems."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Messy Sensor Data: A Programmer's Cleaning Guide\n",
    "\n",
    "Slides available at [github.com/Spaxe/pyconau2017-messy-sensor-data](https://github.com/Spaxe/pyconau2017-messy-sensor-data)\n",
    "\n",
    "There is a bonus section on combining two DataFrames with different frequencies in the notebook.\n",
    "\n",
    "🐹 Let's be friends on Twitter: [@Xavier_Ho](https://twitter.com/Xavier_Ho)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\conta\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\dateutil\\parser\\_parser.py:1213: UnknownTimezoneWarning: tzname EDT identified but not understood.  Pass `tzinfos` argument in order to correctly return a timezone-aware datetime.  In a future version, this will raise an exception.\n",
      "  warnings.warn(\"tzname {tzname} identified but not understood.  \"\n",
      "c:\\users\\conta\\appdata\\local\\programs\\python\\python38\\lib\\site-packages\\dateutil\\parser\\_parser.py:1213: UnknownTimezoneWarning: tzname EST identified but not understood.  Pass `tzinfos` argument in order to correctly return a timezone-aware datetime.  In a future version, this will raise an exception.\n",
      "  warnings.warn(\"tzname {tzname} identified but not understood.  \"\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Datetime</th>\n",
       "      <th>Vis</th>\n",
       "      <th>Cloud</th>\n",
       "      <th>Current weather</th>\n",
       "      <th>Past weather</th>\n",
       "      <th>?</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-01-01 00:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-01-01 23:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-01-01 21:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-01-01 20:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-01-01 18:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Datetime  Vis Cloud  Current weather  Past weather   ?\n",
       "0 2013-01-01 00:00:00  NaN   NaN              NaN           NaN NaN\n",
       "1 2013-01-01 23:00:00  NaN   NaN              NaN           NaN NaN\n",
       "2 2013-01-01 21:00:00  NaN   NaN              NaN           NaN NaN\n",
       "3 2013-01-01 20:00:00  NaN   NaN              NaN           NaN NaN\n",
       "4 2013-01-01 18:00:00  NaN   NaN              NaN           NaN NaN"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# BONUS SECTION\n",
    "# Similarly, for sky observations\n",
    "sky_observations = pd.read_csv('observations/Canberra_sky.csv',\n",
    "                                   sep='\\t',\n",
    "                                   parse_dates={'Datetime': ['Date', 'Time']},\n",
    "                                   dayfirst=True,\n",
    "                                   infer_datetime_format=True,\n",
    "                                   na_values=['-', 'obscured'])\n",
    "sky_observations.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <th>Cloud</th>\n",
       "      <th>Current weather</th>\n",
       "      <th>Past weather</th>\n",
       "      <th>?</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01 00:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01 02:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01 03:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01 05:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01 06:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Vis Cloud  Current weather  Past weather   ?\n",
       "Datetime                                                         \n",
       "2013-01-01 00:00:00  NaN   NaN              NaN           NaN NaN\n",
       "2013-01-01 02:00:00  NaN   NaN              NaN           NaN NaN\n",
       "2013-01-01 03:00:00  NaN   NaN              NaN           NaN NaN\n",
       "2013-01-01 05:00:00  NaN   NaN              NaN           NaN NaN\n",
       "2013-01-01 06:00:00  NaN   NaN              NaN           NaN NaN"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# As before, remove duplicates and set index to datetime.\n",
    "sky_observations.drop_duplicates('Datetime', keep='last', inplace=True)\n",
    "sky_observations.sort_values('Datetime', inplace=True)\n",
    "sky_observations.set_index('Datetime', inplace=True)\n",
    "\n",
    "sky_observations.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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>Vis</th>\n",
       "      <th>Cloud</th>\n",
       "      <th>Current weather</th>\n",
       "      <th>Past weather</th>\n",
       "      <th>?</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-03 03:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8/8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03 06:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8/8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03 09:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1/8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05 09:00:00</th>\n",
       "      <td>25000.0</td>\n",
       "      <td>clear</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05 18:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4/8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Vis  Cloud  Current weather  Past weather   ?\n",
       "Datetime                                                              \n",
       "2013-01-03 03:00:00      NaN    8/8              NaN           NaN NaN\n",
       "2013-01-03 06:00:00      NaN    8/8              NaN           NaN NaN\n",
       "2013-01-03 09:00:00      NaN    1/8              NaN           NaN NaN\n",
       "2013-01-05 09:00:00  25000.0  clear              NaN           NaN NaN\n",
       "2013-01-05 18:00:00      NaN    4/8              NaN           NaN NaN"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop rows that have no data\n",
    "sky_observations.dropna(how='all', inplace=True)\n",
    "\n",
    "sky_observations.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Vis                float64\n",
       "Cloud               object\n",
       "Current weather    float64\n",
       "Past weather       float64\n",
       "?                  float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the inferred data types\n",
    "sky_observations.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['8/8', '1/8', 'clear', '4/8', '6/8', '3/8', '7/8', nan, '2/8',\n",
       "       '5/8'], dtype=object)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# What are the values in the 'Cloud' column?\n",
    "sky_observations['Cloud'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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>Vis</th>\n",
       "      <th>Cloud</th>\n",
       "      <th>Current weather</th>\n",
       "      <th>Past weather</th>\n",
       "      <th>?</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-03 03:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03 06:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03 09:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.125</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05 09:00:00</th>\n",
       "      <td>25000.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05 18:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Vis  Cloud  Current weather  Past weather   ?\n",
       "Datetime                                                              \n",
       "2013-01-03 03:00:00      NaN  1.000              NaN           NaN NaN\n",
       "2013-01-03 06:00:00      NaN  1.000              NaN           NaN NaN\n",
       "2013-01-03 09:00:00      NaN  0.125              NaN           NaN NaN\n",
       "2013-01-05 09:00:00  25000.0  0.000              NaN           NaN NaN\n",
       "2013-01-05 18:00:00      NaN  0.500              NaN           NaN NaN"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 'obscured' means that the visibility was too low to see clouds. We will consider it to be NaN.\n",
    "\n",
    "# Define a function to Change the 'Cloud' column to numerical values\n",
    "def cloud_to_numeric(s):\n",
    "    if s == 'clear' or pd.isnull(s):\n",
    "        return 0\n",
    "    else: \n",
    "        return int(s[0]) / 8.0\n",
    "\n",
    "# Apply the function to every item and assign it back to the original dataframe\n",
    "sky_observations['Cloud'] = \\\n",
    "    sky_observations['Cloud'].apply(cloud_to_numeric, convert_dtype=False).astype('float64')\n",
    "sky_observations.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1584ce95e20>]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the cloud cover with scatter plot using matplotlib\n",
    "clouds = sky_observations[['Cloud']][:100]\n",
    "plt.plot_date(clouds.index, clouds.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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>Cloud</th>\n",
       "      <th>Dew pt</th>\n",
       "      <th>Feels like</th>\n",
       "      <th>Fire</th>\n",
       "      <th>Pres</th>\n",
       "      <th>Rain</th>\n",
       "      <th>Rain 10'</th>\n",
       "      <th>Tmp</th>\n",
       "      <th>Wind dir</th>\n",
       "      <th>Wind gust</th>\n",
       "      <th>Wind spd</th>\n",
       "      <th>rh</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datetime</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01 00:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.7</td>\n",
       "      <td>15.9</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1014.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.9</td>\n",
       "      <td>67.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>44.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01 00:30:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4.7</td>\n",
       "      <td>14.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1014.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.5</td>\n",
       "      <td>112.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>52.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01 01:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4.6</td>\n",
       "      <td>12.8</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1013.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.8</td>\n",
       "      <td>157.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01 01:30:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.9</td>\n",
       "      <td>13.3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1013.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.3</td>\n",
       "      <td>202.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01 02:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4.7</td>\n",
       "      <td>12.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1013.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>225.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>59.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Cloud  Dew pt  Feels like  Fire    Pres  Rain  Rain 10'  \\\n",
       "Datetime                                                                       \n",
       "2013-01-01 00:00:00    NaN     3.7        15.9   5.0  1014.1   0.0       0.0   \n",
       "2013-01-01 00:30:00    NaN     4.7        14.5   3.0  1014.0   0.0       0.0   \n",
       "2013-01-01 01:00:00    NaN     4.6        12.8   3.0  1013.5   0.0       0.0   \n",
       "2013-01-01 01:30:00    NaN     5.9        13.3   3.0  1013.4   0.0       0.0   \n",
       "2013-01-01 02:00:00    NaN     4.7        12.5   3.0  1013.2   0.0       0.0   \n",
       "\n",
       "                      Tmp  Wind dir  Wind gust  Wind spd    rh  \n",
       "Datetime                                                        \n",
       "2013-01-01 00:00:00  15.9      67.5        6.0       2.0  44.0  \n",
       "2013-01-01 00:30:00  14.5     112.5        0.0       0.0  52.0  \n",
       "2013-01-01 01:00:00  12.8     157.5        0.0       0.0  57.0  \n",
       "2013-01-01 01:30:00  13.3     202.5        9.0       6.0  61.0  \n",
       "2013-01-01 02:00:00  12.5     225.0        7.0       2.0  59.0  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Join the two observations together\n",
    "combined_observations = regular_observations.combine_first(sky_observations[['Cloud']])\n",
    "combined_observations.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2013-01-01 00:00:00', '2013-01-01 00:30:00',\n",
       "               '2013-01-01 01:00:00', '2013-01-01 01:30:00',\n",
       "               '2013-01-01 02:00:00', '2013-01-01 02:30:00',\n",
       "               '2013-01-01 03:00:00', '2013-01-01 03:30:00',\n",
       "               '2013-01-01 04:00:00', '2013-01-01 04:30:00',\n",
       "               ...\n",
       "               '2016-12-31 19:00:00', '2016-12-31 19:30:00',\n",
       "               '2016-12-31 20:00:00', '2016-12-31 20:30:00',\n",
       "               '2016-12-31 21:00:00', '2016-12-31 21:30:00',\n",
       "               '2016-12-31 22:00:00', '2016-12-31 22:30:00',\n",
       "               '2016-12-31 23:00:00', '2016-12-31 23:30:00'],\n",
       "              dtype='datetime64[ns]', length=70128, freq='30T')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a new series with 30-minutely timestamps\n",
    "time_series = pd.date_range('2013-01-01', '2017-01-01', freq='30min')[:-1]\n",
    "time_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Cloud</th>\n",
       "      <th>Dew pt</th>\n",
       "      <th>Feels like</th>\n",
       "      <th>Fire</th>\n",
       "      <th>Pres</th>\n",
       "      <th>Rain</th>\n",
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       "      <th>Wind spd</th>\n",
       "      <th>rh</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01 00:00:00</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>4.6</td>\n",
       "      <td>12.8</td>\n",
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       "      <td>1013.5</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>225.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>59.0</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31 21:30:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2016-12-31 22:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2016-12-31 22:30:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31 23:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2016-12-31 23:30:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "<p>70128 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Cloud  Dew pt  Feels like  Fire    Pres  Rain  Rain 10'  \\\n",
       "2013-01-01 00:00:00    NaN     3.7        15.9   5.0  1014.1   0.0       0.0   \n",
       "2013-01-01 00:30:00    NaN     4.7        14.5   3.0  1014.0   0.0       0.0   \n",
       "2013-01-01 01:00:00    NaN     4.6        12.8   3.0  1013.5   0.0       0.0   \n",
       "2013-01-01 01:30:00    NaN     5.9        13.3   3.0  1013.4   0.0       0.0   \n",
       "2013-01-01 02:00:00    NaN     4.7        12.5   3.0  1013.2   0.0       0.0   \n",
       "...                    ...     ...         ...   ...     ...   ...       ...   \n",
       "2016-12-31 21:30:00    NaN     NaN         NaN   NaN     NaN   NaN       NaN   \n",
       "2016-12-31 22:00:00    NaN     NaN         NaN   NaN     NaN   NaN       NaN   \n",
       "2016-12-31 22:30:00    NaN     NaN         NaN   NaN     NaN   NaN       NaN   \n",
       "2016-12-31 23:00:00    NaN     NaN         NaN   NaN     NaN   NaN       NaN   \n",
       "2016-12-31 23:30:00    NaN     NaN         NaN   NaN     NaN   NaN       NaN   \n",
       "\n",
       "                      Tmp  Wind dir  Wind gust  Wind spd    rh  \n",
       "2013-01-01 00:00:00  15.9      67.5        6.0       2.0  44.0  \n",
       "2013-01-01 00:30:00  14.5     112.5        0.0       0.0  52.0  \n",
       "2013-01-01 01:00:00  12.8     157.5        0.0       0.0  57.0  \n",
       "2013-01-01 01:30:00  13.3     202.5        9.0       6.0  61.0  \n",
       "2013-01-01 02:00:00  12.5     225.0        7.0       2.0  59.0  \n",
       "...                   ...       ...        ...       ...   ...  \n",
       "2016-12-31 21:30:00   NaN       NaN        NaN       NaN   NaN  \n",
       "2016-12-31 22:00:00   NaN       NaN        NaN       NaN   NaN  \n",
       "2016-12-31 22:30:00   NaN       NaN        NaN       NaN   NaN  \n",
       "2016-12-31 23:00:00   NaN       NaN        NaN       NaN   NaN  \n",
       "2016-12-31 23:30:00   NaN       NaN        NaN       NaN   NaN  \n",
       "\n",
       "[70128 rows x 12 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reindex our dataset\n",
    "indexed_observations = combined_observations.reindex(time_series)\n",
    "indexed_observations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Cloud', 'Dew pt', 'Feels like', 'Fire', 'Pres', 'Rain', 'Rain 10'',\n",
       "       'Tmp', 'Wind dir', 'Wind gust', 'Wind spd', 'rh'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the columns in the dataset\n",
    "indexed_observations.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <td>225.0</td>\n",
       "      <td>7.0</td>\n",
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       "      <td>59.0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>0.625</td>\n",
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       "      <td>81.0</td>\n",
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       "    <tr>\n",
       "      <th>2016-12-31 22:30:00</th>\n",
       "      <td>0.625</td>\n",
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       "      <td>11.0</td>\n",
       "      <td>81.0</td>\n",
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       "    <tr>\n",
       "      <th>2016-12-31 23:30:00</th>\n",
       "      <td>0.625</td>\n",
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       "      <td>11.0</td>\n",
       "      <td>81.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>70128 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Cloud  Dew pt  Feels like  Fire    Pres  Rain  Rain 10'  \\\n",
       "2013-01-01 00:00:00  1.000     3.7        15.9   5.0  1014.1   0.0       0.0   \n",
       "2013-01-01 00:30:00  1.000     4.7        14.5   3.0  1014.0   0.0       0.0   \n",
       "2013-01-01 01:00:00  1.000     4.6        12.8   3.0  1013.5   0.0       0.0   \n",
       "2013-01-01 01:30:00  1.000     5.9        13.3   3.0  1013.4   0.0       0.0   \n",
       "2013-01-01 02:00:00  1.000     4.7        12.5   3.0  1013.2   0.0       0.0   \n",
       "...                    ...     ...         ...   ...     ...   ...       ...   \n",
       "2016-12-31 21:30:00  0.625    11.4        14.0   2.0  1018.3   0.0       0.0   \n",
       "2016-12-31 22:00:00  0.625    11.4        14.0   2.0  1018.3   0.0       0.0   \n",
       "2016-12-31 22:30:00  0.625    11.4        14.0   2.0  1018.3   0.0       0.0   \n",
       "2016-12-31 23:00:00  0.625    11.4        14.0   2.0  1018.3   0.0       0.0   \n",
       "2016-12-31 23:30:00  0.625    11.4        14.0   2.0  1018.3   0.0       0.0   \n",
       "\n",
       "                      Tmp  Wind dir  Wind gust  Wind spd    rh  \n",
       "2013-01-01 00:00:00  15.9      67.5        6.0       2.0  44.0  \n",
       "2013-01-01 00:30:00  14.5     112.5        0.0       0.0  52.0  \n",
       "2013-01-01 01:00:00  12.8     157.5        0.0       0.0  57.0  \n",
       "2013-01-01 01:30:00  13.3     202.5        9.0       6.0  61.0  \n",
       "2013-01-01 02:00:00  12.5     225.0        7.0       2.0  59.0  \n",
       "...                   ...       ...        ...       ...   ...  \n",
       "2016-12-31 21:30:00  14.6     135.0       17.0      11.0  81.0  \n",
       "2016-12-31 22:00:00  14.6     135.0       17.0      11.0  81.0  \n",
       "2016-12-31 22:30:00  14.6     135.0       17.0      11.0  81.0  \n",
       "2016-12-31 23:00:00  14.6     135.0       17.0      11.0  81.0  \n",
       "2016-12-31 23:30:00  14.6     135.0       17.0      11.0  81.0  \n",
       "\n",
       "[70128 rows x 12 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Interpolate data to fill NaN\n",
    "for column in indexed_observations.columns:\n",
    "    indexed_observations[column].interpolate('time', inplace=True, limit_direction='both')\n",
    "\n",
    "# Preview the cleaned data    \n",
    "indexed_observations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Current bug in pandas fails plotting some interpolated frequencies\n",
    "# see https://github.com/pandas-dev/pandas/issues/14763 (to be fixed by 31 August, 2017)\n",
    "\n",
    "# Convert pandas DateTimeIndex to Python's datetime.datetime\n",
    "timestamps = indexed_observations.index[:1000].to_pydatetime()\n",
    "\n",
    "# Selecting a few columns to plot\n",
    "selection1 = indexed_observations[['Wind spd', 'Wind gust', 'Tmp', 'Feels like']][:1000]\n",
    "selection2 = indexed_observations[['Cloud']][:1000]\n",
    "\n",
    "# For now, we copy the index and values to matplotlib\n",
    "# see https://stackoverflow.com/questions/43206554/typeerror-float-argument-must-be-a-string-or-a-number-not-period/45191625#45191625\n",
    "legend = plt.plot_date(timestamps, selection1.values, '-')\n",
    "plt.legend(selection1.columns)\n",
    "plt.show()\n",
    "\n",
    "legend = plt.plot_date(timestamps, selection2.values, '-')\n",
    "plt.legend(selection2.columns)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}