kaustavbhattacharjee/jupyter-notebook-tutorial.ipynb

## jupyter-notebook-tutorial.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set(style=\"darkgrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"fortune500.csv\")"
   ]
  },
  {
   "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>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company</th>\n",
       "      <th>Revenue (in millions)</th>\n",
       "      <th>Profit (in millions)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1955</td>\n",
       "      <td>1</td>\n",
       "      <td>General Motors</td>\n",
       "      <td>9823.5</td>\n",
       "      <td>806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1955</td>\n",
       "      <td>2</td>\n",
       "      <td>Exxon Mobil</td>\n",
       "      <td>5661.4</td>\n",
       "      <td>584.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1955</td>\n",
       "      <td>3</td>\n",
       "      <td>U.S. Steel</td>\n",
       "      <td>3250.4</td>\n",
       "      <td>195.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1955</td>\n",
       "      <td>4</td>\n",
       "      <td>General Electric</td>\n",
       "      <td>2959.1</td>\n",
       "      <td>212.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1955</td>\n",
       "      <td>5</td>\n",
       "      <td>Esmark</td>\n",
       "      <td>2510.8</td>\n",
       "      <td>19.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year  Rank           Company  Revenue (in millions) Profit (in millions)\n",
       "0  1955     1    General Motors                 9823.5                  806\n",
       "1  1955     2       Exxon Mobil                 5661.4                584.8\n",
       "2  1955     3        U.S. Steel                 3250.4                195.4\n",
       "3  1955     4  General Electric                 2959.1                212.6\n",
       "4  1955     5            Esmark                 2510.8                 19.1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "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>Year</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Company</th>\n",
       "      <th>Revenue (in millions)</th>\n",
       "      <th>Profit (in millions)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>25495</th>\n",
       "      <td>2005</td>\n",
       "      <td>496</td>\n",
       "      <td>Wm. Wrigley Jr.</td>\n",
       "      <td>3648.6</td>\n",
       "      <td>493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25496</th>\n",
       "      <td>2005</td>\n",
       "      <td>497</td>\n",
       "      <td>Peabody Energy</td>\n",
       "      <td>3631.6</td>\n",
       "      <td>175.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25497</th>\n",
       "      <td>2005</td>\n",
       "      <td>498</td>\n",
       "      <td>Wendy's International</td>\n",
       "      <td>3630.4</td>\n",
       "      <td>57.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25498</th>\n",
       "      <td>2005</td>\n",
       "      <td>499</td>\n",
       "      <td>Kindred Healthcare</td>\n",
       "      <td>3616.6</td>\n",
       "      <td>70.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25499</th>\n",
       "      <td>2005</td>\n",
       "      <td>500</td>\n",
       "      <td>Cincinnati Financial</td>\n",
       "      <td>3614.0</td>\n",
       "      <td>584</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Year  Rank                Company  Revenue (in millions)  \\\n",
       "25495  2005   496        Wm. Wrigley Jr.                 3648.6   \n",
       "25496  2005   497         Peabody Energy                 3631.6   \n",
       "25497  2005   498  Wendy's International                 3630.4   \n",
       "25498  2005   499     Kindred Healthcare                 3616.6   \n",
       "25499  2005   500   Cincinnati Financial                 3614.0   \n",
       "\n",
       "      Profit (in millions)  \n",
       "25495                  493  \n",
       "25496                175.4  \n",
       "25497                 57.8  \n",
       "25498                 70.6  \n",
       "25499                  584  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns=['year','rank','company','revenue','profit']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25500"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year         int64\n",
       "rank         int64\n",
       "company     object\n",
       "revenue    float64\n",
       "profit      object\n",
       "dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>year</th>\n",
       "      <th>rank</th>\n",
       "      <th>company</th>\n",
       "      <th>revenue</th>\n",
       "      <th>profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>1955</td>\n",
       "      <td>229</td>\n",
       "      <td>Norton</td>\n",
       "      <td>135.0</td>\n",
       "      <td>N.A.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>290</th>\n",
       "      <td>1955</td>\n",
       "      <td>291</td>\n",
       "      <td>Schlitz Brewing</td>\n",
       "      <td>100.0</td>\n",
       "      <td>N.A.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>294</th>\n",
       "      <td>1955</td>\n",
       "      <td>295</td>\n",
       "      <td>Pacific Vegetable Oil</td>\n",
       "      <td>97.9</td>\n",
       "      <td>N.A.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>296</th>\n",
       "      <td>1955</td>\n",
       "      <td>297</td>\n",
       "      <td>Liebmann Breweries</td>\n",
       "      <td>96.0</td>\n",
       "      <td>N.A.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>352</th>\n",
       "      <td>1955</td>\n",
       "      <td>353</td>\n",
       "      <td>Minneapolis-Moline</td>\n",
       "      <td>77.4</td>\n",
       "      <td>N.A.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     year  rank                company  revenue profit\n",
       "228  1955   229                 Norton    135.0   N.A.\n",
       "290  1955   291        Schlitz Brewing    100.0   N.A.\n",
       "294  1955   295  Pacific Vegetable Oil     97.9   N.A.\n",
       "296  1955   297     Liebmann Breweries     96.0   N.A.\n",
       "352  1955   353     Minneapolis-Moline     77.4   N.A."
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "non_numeric_profits=df.profit.str.contains('[^0-9.-]')\n",
    "df.loc[non_numeric_profits].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'N.A.'}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "set(df.profit[non_numeric_profits])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "369"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.profit[non_numeric_profits])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bin_sizes, _, _ = plt.hist(df.year[non_numeric_profits], bins=range(1955, 2006))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df.loc[~non_numeric_profits]\n",
    "df.profit=df.profit.apply(pd.to_numeric)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25131"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year         int64\n",
       "rank         int64\n",
       "company     object\n",
       "revenue    float64\n",
       "profit     float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "group_by_year=df.loc[:,['year','revenue','profit']].groupby('year')\n",
    "avgs=group_by_year.mean()\n",
    "x=avgs.index\n",
    "y1=avgs.profit\n",
    "def plot(x,y,ax,title,y_label):\n",
    "    ax.set_title(title)\n",
    "    ax.set_ylabel(y_label)\n",
    "    ax.plot(x,y)\n",
    "    ax.margins(x=0,y=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax=plt.subplots()\n",
    "plot(x,y1,ax,\"Increase in mean Fortune 500 company profits from 1955 to 2005\", \"Profit(millions)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y2 = avgs.revenue\n",
    "fig, ax = plt.subplots()\n",
    "plot(x, y2, ax, 'Increase in mean Fortune 500 company revenues from 1955 to 2005', 'Revenue (millions)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_with_std(x, y, stds, ax, title, y_label):\n",
    "    ax.fill_between(x, y - stds, y + stds, alpha=0.2)\n",
    "    plot(x, y, ax, title, y_label)\n",
    "fig, (ax1, ax2) = plt.subplots(ncols=2)\n",
    "title = 'Increase in mean and std Fortune 500 company %s from 1955 to 2005'\n",
    "stds1 = group_by_year.std().profit.values\n",
    "stds2 = group_by_year.std().revenue.values\n",
    "plot_with_std(x, y1.values, stds1, ax1, title % 'profits', 'Profit (millions)')\n",
    "plot_with_std(x, y2.values, stds2, ax2, title % 'revenues', 'Revenue (millions)')\n",
    "fig.set_size_inches(14, 4)\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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