zadaci.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "### Uvod:\n",
    "\n",
    "Data su dva CSV fajla:\n",
    "1. products.csv - sadrži identifikatore proizvoda i njihove opise\n",
    "2. orders.csv - sadrži porudžbine jedne online prodavnice, zajedno sa identifikatorima porudžbine, proizvoda, kupca, datumom porudžbine, količinom i cenom, kao i zemljom porudžbine"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Zadaci:"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Importuj pandas"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 379,
   "outputs": [],
   "source": [
    "import pandas as pd"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.083953Z",
     "start_time": "2023-08-27T14:04:17.036976Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Učitaj ```products.csv``` u DataFrame sa nazivom ```products_df```"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "outputs": [],
   "source": [
    "products_df = pd.read_csv(\"data/products.csv\")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.126214Z",
     "start_time": "2023-08-27T14:04:17.042658Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Učitaj ```orders.csv``` u DataFrame sa nazivom ```orders_df```"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "outputs": [],
   "source": [
    "orders_df = pd.read_csv(\"data/orders.csv\")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.255115Z",
     "start_time": "2023-08-27T14:04:17.057775Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Prikaži prvih 10 redova oba DataFrame-a:"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "outputs": [
    {
     "data": {
      "text/plain": "  StockCode                          Description\n0    85123A   WHITE HANGING HEART T-LIGHT HOLDER\n1     71053                  WHITE METAL LANTERN\n2    84406B       CREAM CUPID HEARTS COAT HANGER\n3    84029G  KNITTED UNION FLAG HOT WATER BOTTLE\n4    84029E       RED WOOLLY HOTTIE WHITE HEART.\n5     22752         SET 7 BABUSHKA NESTING BOXES\n6     21730    GLASS STAR FROSTED T-LIGHT HOLDER\n7     22633               HAND WARMER UNION JACK\n8     22632            HAND WARMER RED POLKA DOT\n9     84879        ASSORTED COLOUR BIRD ORNAMENT",
      "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>StockCode</th>\n      <th>Description</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>85123A</td>\n      <td>WHITE HANGING HEART T-LIGHT HOLDER</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>71053</td>\n      <td>WHITE METAL LANTERN</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>84406B</td>\n      <td>CREAM CUPID HEARTS COAT HANGER</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>84029G</td>\n      <td>KNITTED UNION FLAG HOT WATER BOTTLE</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>84029E</td>\n      <td>RED WOOLLY HOTTIE WHITE HEART.</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>22752</td>\n      <td>SET 7 BABUSHKA NESTING BOXES</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>21730</td>\n      <td>GLASS STAR FROSTED T-LIGHT HOLDER</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>22633</td>\n      <td>HAND WARMER UNION JACK</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>22632</td>\n      <td>HAND WARMER RED POLKA DOT</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>84879</td>\n      <td>ASSORTED COLOUR BIRD ORNAMENT</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 382,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products_df.head(10)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.260072Z",
     "start_time": "2023-08-27T14:04:17.257803Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 383,
   "outputs": [
    {
     "data": {
      "text/plain": "  InvoiceNo StockCode  Quantity     InvoiceDate  UnitPrice  CustomerID  \\\n0    536365    85123A         6  12/1/2010 8:26       2.55     17850.0   \n1    536365     71053         6  12/1/2010 8:26       3.39     17850.0   \n2    536365    84406B         8  12/1/2010 8:26       2.75     17850.0   \n3    536365    84029G         6  12/1/2010 8:26       3.39     17850.0   \n4    536365    84029E         6  12/1/2010 8:26       3.39     17850.0   \n5    536365     22752         2  12/1/2010 8:26       7.65     17850.0   \n6    536365     21730         6  12/1/2010 8:26       4.25     17850.0   \n7    536366     22633         6  12/1/2010 8:28       1.85     17850.0   \n8    536366     22632         6  12/1/2010 8:28       1.85     17850.0   \n9    536367     84879        32  12/1/2010 8:34       1.69     13047.0   \n\n          Country  \n0  United Kingdom  \n1  United Kingdom  \n2  United Kingdom  \n3  United Kingdom  \n4  United Kingdom  \n5  United Kingdom  \n6  United Kingdom  \n7  United Kingdom  \n8  United Kingdom  \n9  United Kingdom  ",
      "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>InvoiceNo</th>\n      <th>StockCode</th>\n      <th>Quantity</th>\n      <th>InvoiceDate</th>\n      <th>UnitPrice</th>\n      <th>CustomerID</th>\n      <th>Country</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>536365</td>\n      <td>85123A</td>\n      <td>6</td>\n      <td>12/1/2010 8:26</td>\n      <td>2.55</td>\n      <td>17850.0</td>\n      <td>United Kingdom</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>536365</td>\n      <td>71053</td>\n      <td>6</td>\n      <td>12/1/2010 8:26</td>\n      <td>3.39</td>\n      <td>17850.0</td>\n      <td>United Kingdom</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>536365</td>\n      <td>84406B</td>\n      <td>8</td>\n      <td>12/1/2010 8:26</td>\n      <td>2.75</td>\n      <td>17850.0</td>\n      <td>United Kingdom</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>536365</td>\n      <td>84029G</td>\n      <td>6</td>\n      <td>12/1/2010 8:26</td>\n      <td>3.39</td>\n      <td>17850.0</td>\n      <td>United Kingdom</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>536365</td>\n      <td>84029E</td>\n      <td>6</td>\n      <td>12/1/2010 8:26</td>\n      <td>3.39</td>\n      <td>17850.0</td>\n      <td>United Kingdom</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>536365</td>\n      <td>22752</td>\n      <td>2</td>\n      <td>12/1/2010 8:26</td>\n      <td>7.65</td>\n      <td>17850.0</td>\n      <td>United Kingdom</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>536365</td>\n      <td>21730</td>\n      <td>6</td>\n      <td>12/1/2010 8:26</td>\n      <td>4.25</td>\n      <td>17850.0</td>\n      <td>United Kingdom</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>536366</td>\n      <td>22633</td>\n      <td>6</td>\n      <td>12/1/2010 8:28</td>\n      <td>1.85</td>\n      <td>17850.0</td>\n      <td>United Kingdom</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>536366</td>\n      <td>22632</td>\n      <td>6</td>\n      <td>12/1/2010 8:28</td>\n      <td>1.85</td>\n      <td>17850.0</td>\n      <td>United Kingdom</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>536367</td>\n      <td>84879</td>\n      <td>32</td>\n      <td>12/1/2010 8:34</td>\n      <td>1.69</td>\n      <td>13047.0</td>\n      <td>United Kingdom</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 383,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orders_df.head(10)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.267041Z",
     "start_time": "2023-08-27T14:04:17.264236Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Proveri koliko nedostajajućih vrednosti ima kolona ```Description``` u ```products_df``` DataFrame-u"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 384,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3685 entries, 0 to 3684\n",
      "Data columns (total 2 columns):\n",
      " #   Column       Non-Null Count  Dtype \n",
      "---  ------       --------------  ----- \n",
      " 0   StockCode    3685 non-null   object\n",
      " 1   Description  3682 non-null   object\n",
      "dtypes: object(2)\n",
      "memory usage: 57.7+ KB\n",
      "None\n",
      "     StockCode Description\n",
      "1418     21446         NaN\n",
      "1496     11001         NaN\n",
      "1624     20702         NaN\n",
      "3\n"
     ]
    }
   ],
   "source": [
    "print(products_df.info()) # broj entry-ja u indeksu (3685) - 3682 non null Description vrednosti = 3\n",
    "\n",
    "# alternativa (ispiši redove sa nedostajućim vrednostima)\n",
    "\n",
    "print(products_df[products_df[\"Description\"].isna()])\n",
    "\n",
    "# alternativa (izbroj redove sa nedostajućim vrednostima)\n",
    "\n",
    "print(products_df[\"Description\"].isna().sum())"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.273454Z",
     "start_time": "2023-08-27T14:04:17.270101Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Popuni vrednosti koje nedostaju u ```Description``` koloni sa ```Missing Description```"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 385,
   "outputs": [],
   "source": [
    "products_df[\"Description\"] = products_df[\"Description\"].fillna(\"Missing Description\")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.275678Z",
     "start_time": "2023-08-27T14:04:17.273942Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Napravi novi orders_df spajajući ```orders_df``` i ```products_df``` da bi u novom DataFrame-u uz svaki proizvod iz porudžbine postojala informacija o opisu proizvoda"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 386,
   "outputs": [],
   "source": [
    "orders_df = pd.merge(\n",
    "    orders_df, \n",
    "    products_df, \n",
    "    left_on=\"StockCode\", \n",
    "    right_on=\"StockCode\",\n",
    "    how=\"left\"\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.356187Z",
     "start_time": "2023-08-27T14:04:17.294423Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Napravi novu ```Total``` kolonu u okviru ```orders_df``` koja se dobija kao proizvod vrednosti ```Quantity``` i ```UnitPrice``` kolona"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 387,
   "outputs": [],
   "source": [
    "orders_df[\"Total\"] = orders_df[\"Quantity\"] * orders_df[\"UnitPrice\"]"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.356379Z",
     "start_time": "2023-08-27T14:04:17.334710Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Sačuvaj novi ```order_df``` u fajl sa nazivom ```extended_orders.csv```"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 388,
   "outputs": [],
   "source": [
    "#orders_df.to_csv(\"extended_orders.csv\")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.356428Z",
     "start_time": "2023-08-27T14:04:17.337456Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Grupiši orders_df tako da dobiješ ukupnu zaradu po državi"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 389,
   "outputs": [
    {
     "data": {
      "text/plain": "Country\nAustralia                137077.270\nAustria                   10154.320\nBahrain                     548.400\nBelgium                   40910.960\nBrazil                     1143.600\nCanada                     3666.380\nChannel Islands           20086.290\nCyprus                    12946.290\nCzech Republic              707.720\nDenmark                   18768.140\nEIRE                     250285.220\nEuropean Community         1291.750\nFinland                   22326.740\nFrance                   196712.840\nGermany                  221698.210\nGreece                     4710.520\nIceland                    4310.000\nIsrael                     6994.250\nItaly                     16890.510\nJapan                     35340.620\nLebanon                    1693.880\nLithuania                  1661.060\nMalta                      2505.470\nNetherlands              284661.540\nNorway                    35163.460\nPoland                     7213.140\nPortugal                  29059.810\nRSA                        1002.310\nSaudi Arabia                131.170\nSingapore                  9120.390\nSpain                     54774.580\nSweden                    36595.910\nSwitzerland               55739.400\nUSA                        1730.920\nUnited Arab Emirates       1902.280\nUnited Kingdom          6767873.394\nUnspecified                2667.070\nName: Total, dtype: float64"
     },
     "execution_count": 389,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profit_per_country_df = orders_df.groupby(\"Country\")[\"Total\"].sum()\n",
    "profit_per_country_df"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.372967Z",
     "start_time": "2023-08-27T14:04:17.347878Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 390,
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: title={'center': 'Total profit per country'}, xlabel='Total Profit', ylabel='Country'>"
     },
     "execution_count": 390,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "profit_per_country_df.plot.bar(\n",
    "    x=\"Country\",\n",
    "    y=\"Total\",\n",
    "    title=\"Total profit per country\",\n",
    "    ylabel=\"Country\",\n",
    "    xlabel=\"Total Profit\"\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.648448Z",
     "start_time": "2023-08-27T14:04:17.373191Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "Prikaži rezultate na dijagramu. Stilizuj dijagram"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "profit_per_country_df = profit_per_country_df.nlargest(10)\n",
    "ax = profit_per_country_df.plot.bar(\n",
    "    x=\"Country\", \n",
    "    y=\"Total\",\n",
    "    title=\"Total profit per country\",\n",
    "    ylabel=\"Country\",\n",
    "    xlabel=\"Total Profit\",\n",
    "    color=\"green\",\n",
    "    width=1,\n",
    "    edgecolor=\"white\",\n",
    "    linewidth=0.7\n",
    ")"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-27T14:04:17.740324Z",
     "start_time": "2023-08-27T14:04:17.658309Z"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}