s1n04-creating-a-dataframe.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating a [`DataFrame`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html#pandas.DataFrame)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are actually quite a few ways to create a [`DataFrame`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.html) from existing objects.\n",
    "\n",
    "Let's explore!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setup\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## From a 2-dimensional object"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If your data is already in rows and columns, like a list of lists, you can just pass it along to the constructor.  Labels and Column headings will be automatically generated as a range."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Craig</td>\n",
       "      <td>Dennis</td>\n",
       "      <td>42.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Treasure</td>\n",
       "      <td>Porth</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0       1      2\n",
       "0     Craig  Dennis  42.42\n",
       "1  Treasure   Porth  25.00"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_users_list = [\n",
    "    ['Craig', 'Dennis', 42.42],\n",
    "    ['Treasure', 'Porth', 25.00]\n",
    "]\n",
    "\n",
    "pd.DataFrame(test_users_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice how both the labels and column headings are autogenerated. You can specify the `index` and `columns`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>first_name</th>\n",
       "      <th>last_name</th>\n",
       "      <th>balance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>craigsdennis</th>\n",
       "      <td>Craig</td>\n",
       "      <td>Dennis</td>\n",
       "      <td>42.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>treasure</th>\n",
       "      <td>Treasure</td>\n",
       "      <td>Porth</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             first_name last_name  balance\n",
       "craigsdennis      Craig    Dennis    42.42\n",
       "treasure       Treasure     Porth    25.00"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(test_users_list, index=['craigsdennis', 'treasure'],\n",
    "            columns=['first_name', 'last_name', 'balance'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## From a dictionary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Much like a `Series`, if you do not specify the index it will be autogenerated in range format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>first_name</th>\n",
       "      <th>last_name</th>\n",
       "      <th>balance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Craig</td>\n",
       "      <td>Dennis</td>\n",
       "      <td>42.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Treasure</td>\n",
       "      <td>Porth</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  first_name last_name  balance\n",
       "0      Craig    Dennis    42.42\n",
       "1   Treasure     Porth    25.00"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Default expected Dictionary layout is column name, to ordered values\n",
    "test_user_data = {\n",
    "    'first_name': ['Craig', 'Treasure'],\n",
    "    'last_name': ['Dennis', 'Porth'],\n",
    "    'balance': [42.42, 25.00]\n",
    "}\n",
    "\n",
    "pd.DataFrame(test_user_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And remember that you can specify the index by supplying the `index` keyword argument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>first_name</th>\n",
       "      <th>last_name</th>\n",
       "      <th>balance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>craigsdennis</th>\n",
       "      <td>Craig</td>\n",
       "      <td>Dennis</td>\n",
       "      <td>42.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>treasure</th>\n",
       "      <td>Treasure</td>\n",
       "      <td>Porth</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             first_name last_name  balance\n",
       "craigsdennis      Craig    Dennis    42.42\n",
       "treasure       Treasure     Porth    25.00"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(test_user_data, index=['craigsdennis', 'treasure'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [`DataFrame.from_dict`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.from_dict.html#pandas.DataFrame.from_dict) adds more options"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The `orient` keyword\n",
    "The orient keyword allows you to specify whether the keys of your dictionary are part of the labels (`index`) or the column titles (`columns`). Note how the nested dictionaries have been used to define the columns. You could also pass a list to the `columns` "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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",
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       "    }\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>first_name</th>\n",
       "      <th>last_name</th>\n",
       "      <th>balance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>craigsdennis</th>\n",
       "      <td>Craig</td>\n",
       "      <td>Dennis</td>\n",
       "      <td>42.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>treasure</th>\n",
       "      <td>Treasure</td>\n",
       "      <td>Porth</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             first_name last_name  balance\n",
       "craigsdennis      Craig    Dennis    42.42\n",
       "treasure       Treasure     Porth    25.00"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_username = {\n",
    "    'craigsdennis': {\n",
    "        'first_name': 'Craig',\n",
    "        'last_name': 'Dennis',\n",
    "        'balance': 42.42\n",
    "    },\n",
    "    'treasure': {\n",
    "        'first_name': 'Treasure',\n",
    "        'last_name': 'Porth',\n",
    "        'balance': 25.00\n",
    "    }\n",
    "}\n",
    "\n",
    "pd.DataFrame.from_dict(by_username, orient='index')"
   ]
  }
 ],
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