12.2 Reshaping by Melting (Wide to Long).ipynb

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   "source": [
    "![title](img/cover4.png)"
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   "metadata": {},
   "source": [
    "<center><em>Copyright! This material is protected, please do not copy or distribute.    by:Taher Assaf</em></center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "<h1 align=\"center\">Udemy course : Python Bootcamp for Data Science 2021 Numpy Pandas & Seaborn</h1> \n",
    "\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 12.2 Reshaping by Melting (Wide to Long)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we import pandas library:"
   ]
  },
  {
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   "execution_count": 1,
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   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As an example, we will read a dataframe from a csv file using the function **pd.read_csv()**:"
   ]
  },
  {
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   "execution_count": 2,
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>sale1</th>\n",
       "      <th>sale2</th>\n",
       "      <th>sale3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>100</td>\n",
       "      <td>258</td>\n",
       "      <td>592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011</td>\n",
       "      <td>128</td>\n",
       "      <td>364</td>\n",
       "      <td>606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012</td>\n",
       "      <td>156</td>\n",
       "      <td>249</td>\n",
       "      <td>732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>109</td>\n",
       "      <td>271</td>\n",
       "      <td>629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>248</td>\n",
       "      <td>363</td>\n",
       "      <td>929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2015</td>\n",
       "      <td>375</td>\n",
       "      <td>299</td>\n",
       "      <td>610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2016</td>\n",
       "      <td>145</td>\n",
       "      <td>356</td>\n",
       "      <td>540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017</td>\n",
       "      <td>90</td>\n",
       "      <td>212</td>\n",
       "      <td>673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018</td>\n",
       "      <td>29</td>\n",
       "      <td>336</td>\n",
       "      <td>432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019</td>\n",
       "      <td>69</td>\n",
       "      <td>277</td>\n",
       "      <td>421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020</td>\n",
       "      <td>265</td>\n",
       "      <td>368</td>\n",
       "      <td>862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2021</td>\n",
       "      <td>184</td>\n",
       "      <td>292</td>\n",
       "      <td>688</td>\n",
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      "text/plain": [
       "    year  sale1  sale2  sale3\n",
       "0   2010    100    258    592\n",
       "1   2011    128    364    606\n",
       "2   2012    156    249    732\n",
       "3   2013    109    271    629\n",
       "4   2014    248    363    929\n",
       "5   2015    375    299    610\n",
       "6   2016    145    356    540\n",
       "7   2017     90    212    673\n",
       "8   2018     29    336    432\n",
       "9   2019     69    277    421\n",
       "10  2020    265    368    862\n",
       "11  2021    184    292    688"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "data1 = pd.read_csv('data/ex7.csv')\n",
    "data1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can reshape this dataframe by transforming the values of all columns into a single column using the function **melt()**:\n",
    "***Notice:** the column that is assigned in the argument **id_vard** will not be transformed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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       "      <td>sale1</td>\n",
       "      <td>265</td>\n",
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       "      <td>2021</td>\n",
       "      <td>sale1</td>\n",
       "      <td>184</td>\n",
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       "    <tr>\n",
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       "      <td>sale2</td>\n",
       "      <td>249</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2013</td>\n",
       "      <td>sale2</td>\n",
       "      <td>271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014</td>\n",
       "      <td>sale2</td>\n",
       "      <td>363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2015</td>\n",
       "      <td>sale2</td>\n",
       "      <td>299</td>\n",
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       "      <td>sale2</td>\n",
       "      <td>212</td>\n",
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       "    <tr>\n",
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       "      <td>sale2</td>\n",
       "      <td>336</td>\n",
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       "    <tr>\n",
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       "      <td>2019</td>\n",
       "      <td>sale2</td>\n",
       "      <td>277</td>\n",
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       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2020</td>\n",
       "      <td>sale2</td>\n",
       "      <td>368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2021</td>\n",
       "      <td>sale2</td>\n",
       "      <td>292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2010</td>\n",
       "      <td>sale3</td>\n",
       "      <td>592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2011</td>\n",
       "      <td>sale3</td>\n",
       "      <td>606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2012</td>\n",
       "      <td>sale3</td>\n",
       "      <td>732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2013</td>\n",
       "      <td>sale3</td>\n",
       "      <td>629</td>\n",
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       "    <tr>\n",
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       "      <td>929</td>\n",
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       "    <tr>\n",
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       "      <td>sale3</td>\n",
       "      <td>610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2016</td>\n",
       "      <td>sale3</td>\n",
       "      <td>540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2017</td>\n",
       "      <td>sale3</td>\n",
       "      <td>673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2018</td>\n",
       "      <td>sale3</td>\n",
       "      <td>432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2019</td>\n",
       "      <td>sale3</td>\n",
       "      <td>421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2020</td>\n",
       "      <td>sale3</td>\n",
       "      <td>862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2021</td>\n",
       "      <td>sale3</td>\n",
       "      <td>688</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "    year variable  value\n",
       "0   2010    sale1    100\n",
       "1   2011    sale1    128\n",
       "2   2012    sale1    156\n",
       "3   2013    sale1    109\n",
       "4   2014    sale1    248\n",
       "5   2015    sale1    375\n",
       "6   2016    sale1    145\n",
       "7   2017    sale1     90\n",
       "8   2018    sale1     29\n",
       "9   2019    sale1     69\n",
       "10  2020    sale1    265\n",
       "11  2021    sale1    184\n",
       "12  2010    sale2    258\n",
       "13  2011    sale2    364\n",
       "14  2012    sale2    249\n",
       "15  2013    sale2    271\n",
       "16  2014    sale2    363\n",
       "17  2015    sale2    299\n",
       "18  2016    sale2    356\n",
       "19  2017    sale2    212\n",
       "20  2018    sale2    336\n",
       "21  2019    sale2    277\n",
       "22  2020    sale2    368\n",
       "23  2021    sale2    292\n",
       "24  2010    sale3    592\n",
       "25  2011    sale3    606\n",
       "26  2012    sale3    732\n",
       "27  2013    sale3    629\n",
       "28  2014    sale3    929\n",
       "29  2015    sale3    610\n",
       "30  2016    sale3    540\n",
       "31  2017    sale3    673\n",
       "32  2018    sale3    432\n",
       "33  2019    sale3    421\n",
       "34  2020    sale3    862\n",
       "35  2021    sale3    688"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2 = data1.melt(id_vars= 'year')\n",
    "data2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can rename the newly created columns ourselves by using the arguments **var_name** and **value_name**, instead of the default names (variable and value): "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019</td>\n",
       "      <td>sale1</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020</td>\n",
       "      <td>sale1</td>\n",
       "      <td>265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2021</td>\n",
       "      <td>sale1</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2010</td>\n",
       "      <td>sale2</td>\n",
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       "      <td>sale2</td>\n",
       "      <td>249</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2013</td>\n",
       "      <td>sale2</td>\n",
       "      <td>271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014</td>\n",
       "      <td>sale2</td>\n",
       "      <td>363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2015</td>\n",
       "      <td>sale2</td>\n",
       "      <td>299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2018</td>\n",
       "      <td>sale2</td>\n",
       "      <td>336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019</td>\n",
       "      <td>sale2</td>\n",
       "      <td>277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2020</td>\n",
       "      <td>sale2</td>\n",
       "      <td>368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2021</td>\n",
       "      <td>sale2</td>\n",
       "      <td>292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2010</td>\n",
       "      <td>sale3</td>\n",
       "      <td>592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2011</td>\n",
       "      <td>sale3</td>\n",
       "      <td>606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2012</td>\n",
       "      <td>sale3</td>\n",
       "      <td>732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2013</td>\n",
       "      <td>sale3</td>\n",
       "      <td>629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2014</td>\n",
       "      <td>sale3</td>\n",
       "      <td>929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2015</td>\n",
       "      <td>sale3</td>\n",
       "      <td>610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2016</td>\n",
       "      <td>sale3</td>\n",
       "      <td>540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2017</td>\n",
       "      <td>sale3</td>\n",
       "      <td>673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2018</td>\n",
       "      <td>sale3</td>\n",
       "      <td>432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2019</td>\n",
       "      <td>sale3</td>\n",
       "      <td>421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2020</td>\n",
       "      <td>sale3</td>\n",
       "      <td>862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2021</td>\n",
       "      <td>sale3</td>\n",
       "      <td>688</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    year  sales  amount\n",
       "0   2010  sale1     100\n",
       "1   2011  sale1     128\n",
       "2   2012  sale1     156\n",
       "3   2013  sale1     109\n",
       "4   2014  sale1     248\n",
       "5   2015  sale1     375\n",
       "6   2016  sale1     145\n",
       "7   2017  sale1      90\n",
       "8   2018  sale1      29\n",
       "9   2019  sale1      69\n",
       "10  2020  sale1     265\n",
       "11  2021  sale1     184\n",
       "12  2010  sale2     258\n",
       "13  2011  sale2     364\n",
       "14  2012  sale2     249\n",
       "15  2013  sale2     271\n",
       "16  2014  sale2     363\n",
       "17  2015  sale2     299\n",
       "18  2016  sale2     356\n",
       "19  2017  sale2     212\n",
       "20  2018  sale2     336\n",
       "21  2019  sale2     277\n",
       "22  2020  sale2     368\n",
       "23  2021  sale2     292\n",
       "24  2010  sale3     592\n",
       "25  2011  sale3     606\n",
       "26  2012  sale3     732\n",
       "27  2013  sale3     629\n",
       "28  2014  sale3     929\n",
       "29  2015  sale3     610\n",
       "30  2016  sale3     540\n",
       "31  2017  sale3     673\n",
       "32  2018  sale3     432\n",
       "33  2019  sale3     421\n",
       "34  2020  sale3     862\n",
       "35  2021  sale3     688"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2 = data1.melt(id_vars= 'year', var_name= 'sales', value_name = 'amount')\n",
    "data2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another example, lets read this dataframe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "hide_input": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
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       "        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>google</th>\n",
       "      <th>apple</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>30-Apr-21</th>\n",
       "      <td>2410.12</td>\n",
       "      <td>131.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29-Apr-21</th>\n",
       "      <td>2429.89</td>\n",
       "      <td>133.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28-Apr-21</th>\n",
       "      <td>2379.91</td>\n",
       "      <td>133.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27-Apr-21</th>\n",
       "      <td>2307.12</td>\n",
       "      <td>134.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26-Apr-21</th>\n",
       "      <td>2326.74</td>\n",
       "      <td>134.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23-Apr-21</th>\n",
       "      <td>2315.30</td>\n",
       "      <td>134.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22-Apr-21</th>\n",
       "      <td>2267.92</td>\n",
       "      <td>131.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21-Apr-21</th>\n",
       "      <td>2293.29</td>\n",
       "      <td>133.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20-Apr-21</th>\n",
       "      <td>2293.63</td>\n",
       "      <td>132.88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            google   apple\n",
       "date                      \n",
       "30-Apr-21  2410.12  131.24\n",
       "29-Apr-21  2429.89  133.25\n",
       "28-Apr-21  2379.91  133.35\n",
       "27-Apr-21  2307.12  134.16\n",
       "26-Apr-21  2326.74  134.49\n",
       "23-Apr-21  2315.30  134.09\n",
       "22-Apr-21  2267.92  131.72\n",
       "21-Apr-21  2293.29  133.27\n",
       "20-Apr-21  2293.63  132.88"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3 = pd.read_csv('data/ex8.csv', index_col = 'date')\n",
    "data3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can move the prices of google and apple into one column using the function **melt()**:\n",
    "\n",
    "***Notice**: the index is automatically removed after melting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "hide_input": false
   },
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>company</th>\n",
       "      <th>closing price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>2429.89</td>\n",
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       "      <th>2</th>\n",
       "      <td>google</td>\n",
       "      <td>2379.91</td>\n",
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       "      <th>3</th>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>google</td>\n",
       "      <td>2326.74</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>google</td>\n",
       "      <td>2315.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>google</td>\n",
       "      <td>2267.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>google</td>\n",
       "      <td>2293.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>google</td>\n",
       "      <td>2293.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>apple</td>\n",
       "      <td>131.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>apple</td>\n",
       "      <td>133.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>apple</td>\n",
       "      <td>133.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>apple</td>\n",
       "      <td>134.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>apple</td>\n",
       "      <td>134.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>apple</td>\n",
       "      <td>134.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>apple</td>\n",
       "      <td>131.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>apple</td>\n",
       "      <td>133.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>apple</td>\n",
       "      <td>132.88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   company  closing price\n",
       "0   google        2410.12\n",
       "1   google        2429.89\n",
       "2   google        2379.91\n",
       "3   google        2307.12\n",
       "4   google        2326.74\n",
       "5   google        2315.30\n",
       "6   google        2267.92\n",
       "7   google        2293.29\n",
       "8   google        2293.63\n",
       "9    apple         131.24\n",
       "10   apple         133.25\n",
       "11   apple         133.35\n",
       "12   apple         134.16\n",
       "13   apple         134.49\n",
       "14   apple         134.09\n",
       "15   apple         131.72\n",
       "16   apple         133.27\n",
       "17   apple         132.88"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3.melt(var_name='company', value_name='closing price')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To keep the original index after melting: we need to add the argument **ignore_index = False**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "hide_input": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>closing price</th>\n",
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       "      <th>30-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2410.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2429.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2379.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2307.12</td>\n",
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       "      <th>26-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2326.74</td>\n",
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       "    <tr>\n",
       "      <th>23-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2315.30</td>\n",
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       "    <tr>\n",
       "      <th>22-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2267.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2293.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2293.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>131.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>133.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>133.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>134.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>134.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>134.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>131.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>133.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>132.88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          company  closing price\n",
       "date                            \n",
       "30-Apr-21  google        2410.12\n",
       "29-Apr-21  google        2429.89\n",
       "28-Apr-21  google        2379.91\n",
       "27-Apr-21  google        2307.12\n",
       "26-Apr-21  google        2326.74\n",
       "23-Apr-21  google        2315.30\n",
       "22-Apr-21  google        2267.92\n",
       "21-Apr-21  google        2293.29\n",
       "20-Apr-21  google        2293.63\n",
       "30-Apr-21   apple         131.24\n",
       "29-Apr-21   apple         133.25\n",
       "28-Apr-21   apple         133.35\n",
       "27-Apr-21   apple         134.16\n",
       "26-Apr-21   apple         134.49\n",
       "23-Apr-21   apple         134.09\n",
       "22-Apr-21   apple         131.72\n",
       "21-Apr-21   apple         133.27\n",
       "20-Apr-21   apple         132.88"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data4 = data3.melt( var_name='company', value_name='closing price', ignore_index  =False)\n",
    "data4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is better to sort the index after melting, and we do that using the function **sort_index()**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "hide_input": false
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "    <tr>\n",
       "      <th>21-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2293.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>133.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2267.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>131.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2315.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>134.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2326.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>134.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2307.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>134.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2379.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>133.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>133.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2429.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30-Apr-21</th>\n",
       "      <td>apple</td>\n",
       "      <td>131.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30-Apr-21</th>\n",
       "      <td>google</td>\n",
       "      <td>2410.12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          company  closing price\n",
       "date                            \n",
       "20-Apr-21  google        2293.63\n",
       "20-Apr-21   apple         132.88\n",
       "21-Apr-21  google        2293.29\n",
       "21-Apr-21   apple         133.27\n",
       "22-Apr-21  google        2267.92\n",
       "22-Apr-21   apple         131.72\n",
       "23-Apr-21  google        2315.30\n",
       "23-Apr-21   apple         134.09\n",
       "26-Apr-21  google        2326.74\n",
       "26-Apr-21   apple         134.49\n",
       "27-Apr-21  google        2307.12\n",
       "27-Apr-21   apple         134.16\n",
       "28-Apr-21  google        2379.91\n",
       "28-Apr-21   apple         133.35\n",
       "29-Apr-21   apple         133.25\n",
       "29-Apr-21  google        2429.89\n",
       "30-Apr-21   apple         131.24\n",
       "30-Apr-21  google        2410.12"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data4.sort_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***\n",
    "\n",
    "<h1 align=\"center\">Thank You</h1> \n",
    "\n",
    "***"
   ]
  }
 ],
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