Group_Assignment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1de1ed34",
   "metadata": {},
   "source": [
    "<h2> Part 1: Exploring Data </h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "36a19338",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "7d08fed7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\FOOJINNY\\\\Documents\\\\Python for Business'"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "89f47cbc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['.ipynb_checkpoints', 'Assignment1(1) (1).ipynb', 'Assignment1.ipynb', 'AutomobileData-Lesson5.csv', 'climate.txt', 'climate_results.txt', 'data', 'data4', 'DataOnly.csv', 'dragon', 'Exercise - W3Resources.ipynb', 'FooJinny_Assignment_Individual(17041468).ipynb', 'Group Assignment', 'italy-covid-daywise.csv', 'Lesson 1 - first-steps-with-python-Sunway.ipynb', 'Lesson 2 - python_variables_and_data_types-Sunway.ipynb', 'Lesson 6  -Numpy-Sch.ipynb', 'Lesson3-Python_branching_and_loops-Sunway.ipynb', 'Lesson4-python_functions_and_scope-Sunway.ipynb', 'Lesson5-FileIO-Sch-Ver2-4Students.ipynb', 'Lesson5-Python_os_and_filesystem-Sunway.ipynb', 'Lesson7-Pandas.ipynb', 'movies2.csv', 'student-mat.csv', 'student-merge.R', 'student-por.csv', 'temp.txt', 'trying.txt', 'Untitled.ipynb', 'Untitled1.ipynb']\n"
     ]
    }
   ],
   "source": [
    "print(os.listdir())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "d664adbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_columns', None)\n",
    "#pd.set_option('display_max_rows', None)\n",
    "\n",
    "raw_data = pd.read_csv (\"DataOnly.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "94410076",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "      <td>Miscellaneous receipt</td>\n",
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       "      <td>Finished Material</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>Q1 2020/21</td>\n",
       "      <td>Miscellaneous receipt</td>\n",
       "      <td>PA</td>\n",
       "      <td>Incoming</td>\n",
       "      <td>Finished Material</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>Q1 2020/21</td>\n",
       "      <td>Miscellaneous receipt</td>\n",
       "      <td>PA</td>\n",
       "      <td>Incoming</td>\n",
       "      <td>Finished Material</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>Q1 2020/21</td>\n",
       "      <td>Miscellaneous receipt</td>\n",
       "      <td>PA</td>\n",
       "      <td>Incoming</td>\n",
       "      <td>Finished Material</td>\n",
       "      <td>CORR11477A-15/F209EP</td>\n",
       "      <td>1881</td>\n",
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       "      <td>Q4 2021/22</td>\n",
       "      <td>Supplier receipt</td>\n",
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       "      <td>Finished Material</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1112</th>\n",
       "      <td>Q4 2021/22</td>\n",
       "      <td>Supplier receipt</td>\n",
       "      <td>PC</td>\n",
       "      <td>Outgoing</td>\n",
       "      <td>Raw Materials</td>\n",
       "      <td>R-3533-15H/F/184</td>\n",
       "      <td>-3680</td>\n",
       "      <td>2472.64</td>\n",
       "      <td>0</td>\n",
       "      <td>-33941.10368</td>\n",
       "      <td>3680</td>\n",
       "      <td>NaN</td>\n",
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       "      <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>1113</th>\n",
       "      <td>Q4 2021/22</td>\n",
       "      <td>Supplier receipt</td>\n",
       "      <td>PC</td>\n",
       "      <td>Outgoing</td>\n",
       "      <td>Raw Materials</td>\n",
       "      <td>R-5435-61/F/1000</td>\n",
       "      <td>-36000</td>\n",
       "      <td>114877</td>\n",
       "      <td>0</td>\n",
       "      <td>-373404.96</td>\n",
       "      <td>36000</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",
       "      <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>1114</th>\n",
       "      <td>Q4 2021/22</td>\n",
       "      <td>Supplier receipt</td>\n",
       "      <td>PC</td>\n",
       "      <td>Outgoing</td>\n",
       "      <td>Raw Materials</td>\n",
       "      <td>R-6532-15/F/180</td>\n",
       "      <td>-2160</td>\n",
       "      <td>3420</td>\n",
       "      <td>0</td>\n",
       "      <td>-75288.21048</td>\n",
       "      <td>2160</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>1115</th>\n",
       "      <td>Q4 2021/22</td>\n",
       "      <td>Supplier receipt</td>\n",
       "      <td>PC</td>\n",
       "      <td>Outgoing</td>\n",
       "      <td>Services</td>\n",
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       "      <td>-1</td>\n",
       "      <td>3</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1116 rows × 32 columns</p>\n",
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      "text/plain": [
       "          Period          Document type TALA Category Direction  \\\n",
       "0     Q1 2020/21  Miscellaneous receipt            PA  Incoming   \n",
       "1     Q1 2020/21  Miscellaneous receipt            PA  Incoming   \n",
       "2     Q1 2020/21  Miscellaneous receipt            PA  Incoming   \n",
       "3     Q1 2020/21  Miscellaneous receipt            PA  Incoming   \n",
       "4     Q1 2020/21  Miscellaneous receipt            PA  Incoming   \n",
       "...          ...                    ...           ...       ...   \n",
       "1111  Q4 2021/22       Supplier receipt            PC  Outgoing   \n",
       "1112  Q4 2021/22       Supplier receipt            PC  Outgoing   \n",
       "1113  Q4 2021/22       Supplier receipt            PC  Outgoing   \n",
       "1114  Q4 2021/22       Supplier receipt            PC  Outgoing   \n",
       "1115  Q4 2021/22       Supplier receipt            PC  Outgoing   \n",
       "\n",
       "            Items_group                  Item On-hand quantity Qty_in_stock  \\\n",
       "0     Finished Material         8338-15/F/244                0            0   \n",
       "1     Finished Material  CLAR16177A-61/F/1340             2010     14272.34   \n",
       "2     Finished Material   CLAR16489B-15/F/218              414            0   \n",
       "3     Finished Material  CLAR16489B-15/F/218W               65            0   \n",
       "4     Finished Material  CORR11477A-15/F209EP             1881            0   \n",
       "...                 ...                   ...              ...          ...   \n",
       "1111  Finished Material         Y-MY004/F/275           -21600        24340   \n",
       "1112      Raw Materials      R-3533-15H/F/184            -3680      2472.64   \n",
       "1113      Raw Materials      R-5435-61/F/1000           -36000       114877   \n",
       "1114      Raw Materials       R-6532-15/F/180            -2160         3420   \n",
       "1115           Services                Z-PF07               -1            3   \n",
       "\n",
       "     Receipt_quantity   Stock_Value Issue_quantity Unnamed: 11 Unnamed: 12  \\\n",
       "0                   1        5.5537              0         NaN         NaN   \n",
       "1                2010   13759.53138              0         NaN         NaN   \n",
       "2                 414     2093.0184              0         NaN         NaN   \n",
       "3                1144     8767.1584              0         NaN         NaN   \n",
       "4                1881    16277.4216              0         NaN         NaN   \n",
       "...               ...           ...            ...         ...         ...   \n",
       "1111                0   -48940.5672          21600         NaN         NaN   \n",
       "1112                0  -33941.10368           3680         NaN         NaN   \n",
       "1113                0    -373404.96          36000         NaN         NaN   \n",
       "1114                0  -75288.21048           2160         NaN         NaN   \n",
       "1115                0   -1200.41148              1         NaN         NaN   \n",
       "\n",
       "     Unnamed: 13 Unnamed: 14 Unnamed: 15 Unnamed: 16  Unnamed: 17  \\\n",
       "0            NaN         NaN         NaN         NaN          NaN   \n",
       "1            NaN         NaN         NaN         NaN          NaN   \n",
       "2            NaN         NaN         NaN         NaN          NaN   \n",
       "3            NaN         NaN         NaN         NaN          NaN   \n",
       "4            NaN         NaN         NaN         NaN          NaN   \n",
       "...          ...         ...         ...         ...          ...   \n",
       "1111         NaN         NaN         NaN         NaN          NaN   \n",
       "1112         NaN         NaN         NaN         NaN          NaN   \n",
       "1113         NaN         NaN         NaN         NaN          NaN   \n",
       "1114         NaN         NaN         NaN         NaN          NaN   \n",
       "1115         NaN         NaN         NaN         NaN          NaN   \n",
       "\n",
       "      Unnamed: 18  Unnamed: 19  Unnamed: 20  Unnamed: 21  Unnamed: 22  \\\n",
       "0             NaN          NaN          NaN          NaN          NaN   \n",
       "1             NaN          NaN          NaN          NaN          NaN   \n",
       "2             NaN          NaN          NaN          NaN          NaN   \n",
       "3             NaN          NaN          NaN          NaN          NaN   \n",
       "4             NaN          NaN          NaN          NaN          NaN   \n",
       "...           ...          ...          ...          ...          ...   \n",
       "1111          NaN          NaN          NaN          NaN          NaN   \n",
       "1112          NaN          NaN          NaN          NaN          NaN   \n",
       "1113          NaN          NaN          NaN          NaN          NaN   \n",
       "1114          NaN          NaN          NaN          NaN          NaN   \n",
       "1115          NaN          NaN          NaN          NaN          NaN   \n",
       "\n",
       "      Unnamed: 23  Unnamed: 24  Unnamed: 25  Unnamed: 26  Unnamed: 27  \\\n",
       "0             NaN          NaN          NaN          NaN          NaN   \n",
       "1             NaN          NaN          NaN          NaN          NaN   \n",
       "2             NaN          NaN          NaN          NaN          NaN   \n",
       "3             NaN          NaN          NaN          NaN          NaN   \n",
       "4             NaN          NaN          NaN          NaN          NaN   \n",
       "...           ...          ...          ...          ...          ...   \n",
       "1111          NaN          NaN          NaN          NaN          NaN   \n",
       "1112          NaN          NaN          NaN          NaN          NaN   \n",
       "1113          NaN          NaN          NaN          NaN          NaN   \n",
       "1114          NaN          NaN          NaN          NaN          NaN   \n",
       "1115          NaN          NaN          NaN          NaN          NaN   \n",
       "\n",
       "      Unnamed: 28  Unnamed: 29  Unnamed: 30  Unnamed: 31  \n",
       "0             NaN          NaN          NaN          NaN  \n",
       "1             NaN          NaN          NaN          NaN  \n",
       "2             NaN          NaN          NaN          NaN  \n",
       "3             NaN          NaN          NaN          NaN  \n",
       "4             NaN          NaN          NaN          NaN  \n",
       "...           ...          ...          ...          ...  \n",
       "1111          NaN          NaN          NaN          NaN  \n",
       "1112          NaN          NaN          NaN          NaN  \n",
       "1113          NaN          NaN          NaN          NaN  \n",
       "1114          NaN          NaN          NaN          NaN  \n",
       "1115          NaN          NaN          NaN          NaN  \n",
       "\n",
       "[1116 rows x 32 columns]"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac5caf2c",
   "metadata": {},
   "source": [
    "<h2> Part 1.1 Delete Unnamed Columns </h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "f419042f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Period', 'Document type', 'TALA Category', 'Direction', 'Items_group',\n",
       "       'Item', 'On-hand quantity', 'Qty_in_stock', 'Receipt_quantity',\n",
       "       'Stock_Value', 'Issue_quantity', 'Unnamed: 11', 'Unnamed: 12',\n",
       "       'Unnamed: 13', 'Unnamed: 14', 'Unnamed: 15', 'Unnamed: 16',\n",
       "       'Unnamed: 17', 'Unnamed: 18', 'Unnamed: 19', 'Unnamed: 20',\n",
       "       'Unnamed: 21', 'Unnamed: 22', 'Unnamed: 23', 'Unnamed: 24',\n",
       "       'Unnamed: 25', 'Unnamed: 26', 'Unnamed: 27', 'Unnamed: 28',\n",
       "       'Unnamed: 29', 'Unnamed: 30', 'Unnamed: 31'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "22c9cd49",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Period</th>\n",
       "      <th>Document type</th>\n",
       "      <th>TALA Category</th>\n",
       "      <th>Direction</th>\n",
       "      <th>Items_group</th>\n",
       "      <th>Item</th>\n",
       "      <th>On-hand quantity</th>\n",
       "      <th>Qty_in_stock</th>\n",
       "      <th>Receipt_quantity</th>\n",
       "      <th>Stock_Value</th>\n",
       "      <th>Issue_quantity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Q1 2020/21</td>\n",
       "      <td>Miscellaneous receipt</td>\n",
       "      <td>PA</td>\n",
       "      <td>Incoming</td>\n",
       "      <td>Finished Material</td>\n",
       "      <td>8338-15/F/244</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5.5537</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Q1 2020/21</td>\n",
       "      <td>Miscellaneous receipt</td>\n",
       "      <td>PA</td>\n",
       "      <td>Incoming</td>\n",
       "      <td>Finished Material</td>\n",
       "      <td>CLAR16177A-61/F/1340</td>\n",
       "      <td>2010</td>\n",
       "      <td>14272.34</td>\n",
       "      <td>2010</td>\n",
       "      <td>13759.53138</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Q1 2020/21</td>\n",
       "      <td>Miscellaneous receipt</td>\n",
       "      <td>PA</td>\n",
       "      <td>Incoming</td>\n",
       "      <td>Finished Material</td>\n",
       "      <td>CLAR16489B-15/F/218</td>\n",
       "      <td>414</td>\n",
       "      <td>0</td>\n",
       "      <td>414</td>\n",
       "      <td>2093.0184</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Q1 2020/21</td>\n",
       "      <td>Miscellaneous receipt</td>\n",
       "      <td>PA</td>\n",
       "      <td>Incoming</td>\n",
       "      <td>Finished Material</td>\n",
       "      <td>CLAR16489B-15/F/218W</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>1144</td>\n",
       "      <td>8767.1584</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Q1 2020/21</td>\n",
       "      <td>Miscellaneous receipt</td>\n",
       "      <td>PA</td>\n",
       "      <td>Incoming</td>\n",
       "      <td>Finished Material</td>\n",
       "      <td>CORR11477A-15/F209EP</td>\n",
       "      <td>1881</td>\n",
       "      <td>0</td>\n",
       "      <td>1881</td>\n",
       "      <td>16277.4216</td>\n",
       "      <td>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1111</th>\n",
       "      <td>Q4 2021/22</td>\n",
       "      <td>Supplier receipt</td>\n",
       "      <td>PC</td>\n",
       "      <td>Outgoing</td>\n",
       "      <td>Finished Material</td>\n",
       "      <td>Y-MY004/F/275</td>\n",
       "      <td>-21600</td>\n",
       "      <td>24340</td>\n",
       "      <td>0</td>\n",
       "      <td>-48940.5672</td>\n",
       "      <td>21600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1112</th>\n",
       "      <td>Q4 2021/22</td>\n",
       "      <td>Supplier receipt</td>\n",
       "      <td>PC</td>\n",
       "      <td>Outgoing</td>\n",
       "      <td>Raw Materials</td>\n",
       "      <td>R-3533-15H/F/184</td>\n",
       "      <td>-3680</td>\n",
       "      <td>2472.64</td>\n",
       "      <td>0</td>\n",
       "      <td>-33941.10368</td>\n",
       "      <td>3680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1113</th>\n",
       "      <td>Q4 2021/22</td>\n",
       "      <td>Supplier receipt</td>\n",
       "      <td>PC</td>\n",
       "      <td>Outgoing</td>\n",
       "      <td>Raw Materials</td>\n",
       "      <td>R-5435-61/F/1000</td>\n",
       "      <td>-36000</td>\n",
       "      <td>114877</td>\n",
       "      <td>0</td>\n",
       "      <td>-373404.96</td>\n",
       "      <td>36000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1114</th>\n",
       "      <td>Q4 2021/22</td>\n",
       "      <td>Supplier receipt</td>\n",
       "      <td>PC</td>\n",
       "      <td>Outgoing</td>\n",
       "      <td>Raw Materials</td>\n",
       "      <td>R-6532-15/F/180</td>\n",
       "      <td>-2160</td>\n",
       "      <td>3420</td>\n",
       "      <td>0</td>\n",
       "      <td>-75288.21048</td>\n",
       "      <td>2160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1115</th>\n",
       "      <td>Q4 2021/22</td>\n",
       "      <td>Supplier receipt</td>\n",
       "      <td>PC</td>\n",
       "      <td>Outgoing</td>\n",
       "      <td>Services</td>\n",
       "      <td>Z-PF07</td>\n",
       "      <td>-1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>-1200.41148</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1116 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Period          Document type TALA Category Direction  \\\n",
       "0     Q1 2020/21  Miscellaneous receipt            PA  Incoming   \n",
       "1     Q1 2020/21  Miscellaneous receipt            PA  Incoming   \n",
       "2     Q1 2020/21  Miscellaneous receipt            PA  Incoming   \n",
       "3     Q1 2020/21  Miscellaneous receipt            PA  Incoming   \n",
       "4     Q1 2020/21  Miscellaneous receipt            PA  Incoming   \n",
       "...          ...                    ...           ...       ...   \n",
       "1111  Q4 2021/22       Supplier receipt            PC  Outgoing   \n",
       "1112  Q4 2021/22       Supplier receipt            PC  Outgoing   \n",
       "1113  Q4 2021/22       Supplier receipt            PC  Outgoing   \n",
       "1114  Q4 2021/22       Supplier receipt            PC  Outgoing   \n",
       "1115  Q4 2021/22       Supplier receipt            PC  Outgoing   \n",
       "\n",
       "            Items_group                  Item On-hand quantity Qty_in_stock  \\\n",
       "0     Finished Material         8338-15/F/244                0            0   \n",
       "1     Finished Material  CLAR16177A-61/F/1340             2010     14272.34   \n",
       "2     Finished Material   CLAR16489B-15/F/218              414            0   \n",
       "3     Finished Material  CLAR16489B-15/F/218W               65            0   \n",
       "4     Finished Material  CORR11477A-15/F209EP             1881            0   \n",
       "...                 ...                   ...              ...          ...   \n",
       "1111  Finished Material         Y-MY004/F/275           -21600        24340   \n",
       "1112      Raw Materials      R-3533-15H/F/184            -3680      2472.64   \n",
       "1113      Raw Materials      R-5435-61/F/1000           -36000       114877   \n",
       "1114      Raw Materials       R-6532-15/F/180            -2160         3420   \n",
       "1115           Services                Z-PF07               -1            3   \n",
       "\n",
       "     Receipt_quantity   Stock_Value Issue_quantity  \n",
       "0                   1        5.5537              0  \n",
       "1                2010   13759.53138              0  \n",
       "2                 414     2093.0184              0  \n",
       "3                1144     8767.1584              0  \n",
       "4                1881    16277.4216              0  \n",
       "...               ...           ...            ...  \n",
       "1111                0   -48940.5672          21600  \n",
       "1112                0  -33941.10368           3680  \n",
       "1113                0    -373404.96          36000  \n",
       "1114                0  -75288.21048           2160  \n",
       "1115                0   -1200.41148              1  \n",
       "\n",
       "[1116 rows x 11 columns]"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#remove unnamed columns \n",
    "\n",
    "raw_data_subset = raw_data [['Period', 'Document type', 'TALA Category', 'Direction', 'Items_group', 'Item',\n",
    "                             'On-hand quantity', 'Qty_in_stock', 'Receipt_quantity','Stock_Value', 'Issue_quantity']]\n",
    "    \n",
    "raw_data_subset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "f30e2f79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Period              0\n",
       "Document type       0\n",
       "TALA Category       0\n",
       "Direction           0\n",
       "Items_group         0\n",
       "Item                0\n",
       "On-hand quantity    0\n",
       "Qty_in_stock        0\n",
       "Receipt_quantity    0\n",
       "Stock_Value         0\n",
       "Issue_quantity      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#detecting null values\n",
    "\n",
    "raw_data_subset.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "41af7e35",
   "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>Period</th>\n",
       "      <th>Document type</th>\n",
       "      <th>TALA Category</th>\n",
       "      <th>Direction</th>\n",
       "      <th>Items_group</th>\n",
       "      <th>Item</th>\n",
       "      <th>On-hand quantity</th>\n",
       "      <th>Qty_in_stock</th>\n",
       "      <th>Receipt_quantity</th>\n",
       "      <th>Stock_Value</th>\n",
       "      <th>Issue_quantity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1116</td>\n",
       "      <td>1116</td>\n",
       "      <td>1116</td>\n",
       "      <td>1116</td>\n",
       "      <td>1116</td>\n",
       "      <td>1116</td>\n",
       "      <td>1116</td>\n",
       "      <td>1116</td>\n",
       "      <td>1116</td>\n",
       "      <td>1116</td>\n",
       "      <td>1116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>14</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>238</td>\n",
       "      <td>754</td>\n",
       "      <td>364</td>\n",
       "      <td>483</td>\n",
       "      <td>981</td>\n",
       "      <td>294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>Q4 2021/22</td>\n",
       "      <td>Supplier receipt</td>\n",
       "      <td>PC</td>\n",
       "      <td>Incoming</td>\n",
       "      <td>Finished Material</td>\n",
       "      <td>EMBR18451A-61/F/1060</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>171</td>\n",
       "      <td>666</td>\n",
       "      <td>616</td>\n",
       "      <td>711</td>\n",
       "      <td>568</td>\n",
       "      <td>21</td>\n",
       "      <td>14</td>\n",
       "      <td>379</td>\n",
       "      <td>399</td>\n",
       "      <td>10</td>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Period     Document type TALA Category Direction  \\\n",
       "count         1116              1116          1116      1116   \n",
       "unique          14                 4             4         3   \n",
       "top     Q4 2021/22  Supplier receipt            PC  Incoming   \n",
       "freq           171               666           616       711   \n",
       "\n",
       "              Items_group                  Item On-hand quantity Qty_in_stock  \\\n",
       "count                1116                  1116             1116         1116   \n",
       "unique                  5                   238              754          364   \n",
       "top     Finished Material  EMBR18451A-61/F/1060                1            0   \n",
       "freq                  568                    21               14          379   \n",
       "\n",
       "       Receipt_quantity Stock_Value Issue_quantity  \n",
       "count              1116        1116           1116  \n",
       "unique              483         981            294  \n",
       "top                   0           0              0  \n",
       "freq                399          10            710  "
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check all values\n",
    "\n",
    "raw_data_subset.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c337508b",
   "metadata": {},
   "source": [
    "<h2> Part 2: Detecting any NaN and Unnamed Problem </h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "66fc7063",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Period              object\n",
       "Document type       object\n",
       "TALA Category       object\n",
       "Direction           object\n",
       "Items_group         object\n",
       "Item                object\n",
       "On-hand quantity    object\n",
       "Qty_in_stock        object\n",
       "Receipt_quantity    object\n",
       "Stock_Value         object\n",
       "Issue_quantity      object\n",
       "dtype: object"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check values type\n",
    "\n",
    "raw_data_subset.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5c634c95",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "0847ec26",
   "metadata": {},
   "outputs": [],
   "source": [
    "missing_values = [\"N/a\", \"na\", np.nan]\n",
    "df = pd.read_csv (\"DataOnly.csv\", na_values = missing_values )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "81bde66d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Period                 0\n",
       "Document type          0\n",
       "TALA Category          0\n",
       "Direction              0\n",
       "Items_group            0\n",
       "Item                   0\n",
       "On-hand quantity       0\n",
       "Qty_in_stock           0\n",
       "Receipt_quantity       0\n",
       "Stock_Value            0\n",
       "Issue_quantity         0\n",
       "Unnamed: 11         1111\n",
       "Unnamed: 12         1111\n",
       "Unnamed: 13         1111\n",
       "Unnamed: 14         1111\n",
       "Unnamed: 15         1111\n",
       "Unnamed: 16         1111\n",
       "Unnamed: 17         1111\n",
       "Unnamed: 18         1111\n",
       "Unnamed: 19         1111\n",
       "Unnamed: 20         1111\n",
       "Unnamed: 21         1111\n",
       "Unnamed: 22         1116\n",
       "Unnamed: 23         1116\n",
       "Unnamed: 24         1116\n",
       "Unnamed: 25         1116\n",
       "Unnamed: 26         1116\n",
       "Unnamed: 27         1116\n",
       "Unnamed: 28         1116\n",
       "Unnamed: 29         1116\n",
       "Unnamed: 30         1116\n",
       "Unnamed: 31         1116\n",
       "dtype: int64"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "e99d9d70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame._add_numeric_operations.<locals>.any of       Period  Document type  TALA Category  Direction  Items_group   Item  \\\n",
       "0      False          False          False      False        False  False   \n",
       "1      False          False          False      False        False  False   \n",
       "2      False          False          False      False        False  False   \n",
       "3      False          False          False      False        False  False   \n",
       "4      False          False          False      False        False  False   \n",
       "...      ...            ...            ...        ...          ...    ...   \n",
       "1111   False          False          False      False        False  False   \n",
       "1112   False          False          False      False        False  False   \n",
       "1113   False          False          False      False        False  False   \n",
       "1114   False          False          False      False        False  False   \n",
       "1115   False          False          False      False        False  False   \n",
       "\n",
       "      On-hand quantity  Qty_in_stock  Receipt_quantity  Stock_Value  ...  \\\n",
       "0                False         False             False        False  ...   \n",
       "1                False         False             False        False  ...   \n",
       "2                False         False             False        False  ...   \n",
       "3                False         False             False        False  ...   \n",
       "4                False         False             False        False  ...   \n",
       "...                ...           ...               ...          ...  ...   \n",
       "1111             False         False             False        False  ...   \n",
       "1112             False         False             False        False  ...   \n",
       "1113             False         False             False        False  ...   \n",
       "1114             False         False             False        False  ...   \n",
       "1115             False         False             False        False  ...   \n",
       "\n",
       "      Unnamed: 22  Unnamed: 23  Unnamed: 24  Unnamed: 25  Unnamed: 26  \\\n",
       "0            True         True         True         True         True   \n",
       "1            True         True         True         True         True   \n",
       "2            True         True         True         True         True   \n",
       "3            True         True         True         True         True   \n",
       "4            True         True         True         True         True   \n",
       "...           ...          ...          ...          ...          ...   \n",
       "1111         True         True         True         True         True   \n",
       "1112         True         True         True         True         True   \n",
       "1113         True         True         True         True         True   \n",
       "1114         True         True         True         True         True   \n",
       "1115         True         True         True         True         True   \n",
       "\n",
       "      Unnamed: 27  Unnamed: 28  Unnamed: 29  Unnamed: 30  Unnamed: 31  \n",
       "0            True         True         True         True         True  \n",
       "1            True         True         True         True         True  \n",
       "2            True         True         True         True         True  \n",
       "3            True         True         True         True         True  \n",
       "4            True         True         True         True         True  \n",
       "...           ...          ...          ...          ...          ...  \n",
       "1111         True         True         True         True         True  \n",
       "1112         True         True         True         True         True  \n",
       "1113         True         True         True         True         True  \n",
       "1114         True         True         True         True         True  \n",
       "1115         True         True         True         True         True  \n",
       "\n",
       "[1116 rows x 32 columns]>"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().any"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "679b5b86",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.isnull(), yticklabels = False, annot = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "71d818c7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "50ace080",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e6a0b53",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}