Walmart_hackathon_2020.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Walmart-hackathon-2020.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/rkauraiya1167/walmart-hackathon-2020/blob/master/Walmart_hackathon_2020.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CKu_0BfgEKLJ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy\n",
        "import pandas as pd\n",
        "import notebook"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vWeFWC91QQNj",
        "colab_type": "code",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "outputId": "5708c408-b3d9-49b9-ffc9-9fe437cd8bee"
      },
      "source": [
        "from google.colab import files\n",
        "files.upload()\n",
        "nba = pd.read_csv(\"dataset.csv\")"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-760917b4-c937-4f2b-86ef-b30ef6e4cf87\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-760917b4-c937-4f2b-86ef-b30ef6e4cf87\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving dataset.csv to dataset (2).csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M1aH9d5DQg9K",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "fe8f6019-a45e-46de-f0a5-2cc8a7397f10"
      },
      "source": [
        "import pandas as pd\n",
        "nba\n",
        "type(nba)\n",
        "bUnit = nba.at[10, 'Item_id']\n",
        "bUnit\n",
        "# nba.get_value(4, 0, takeable = True) \n",
        "# nba.head()\n",
        "# nba.get_value(0, 'Base_Units') "
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "11"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ef6fGqB7RIp9",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "outputId": "981b1eba-328a-4dd2-f1c7-8ee4750c2a37"
      },
      "source": [
        "nba.describe()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Item_id</th>\n",
              "      <th>Base_Price</th>\n",
              "      <th>Base_Units</th>\n",
              "      <th>Price1</th>\n",
              "      <th>Units1</th>\n",
              "      <th>Price2</th>\n",
              "      <th>Units2</th>\n",
              "      <th>Price3</th>\n",
              "      <th>Units3</th>\n",
              "      <th>Price4</th>\n",
              "      <th>Units4</th>\n",
              "      <th>Base_Revenue_Per_Item</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>300.000000</td>\n",
              "      <td>300.000000</td>\n",
              "      <td>300.000000</td>\n",
              "      <td>300.000000</td>\n",
              "      <td>300.000000</td>\n",
              "      <td>300.000000</td>\n",
              "      <td>300.000000</td>\n",
              "      <td>300.000000</td>\n",
              "      <td>300.000000</td>\n",
              "      <td>300.000000</td>\n",
              "      <td>300.000000</td>\n",
              "      <td>300.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>150.500000</td>\n",
              "      <td>40.063333</td>\n",
              "      <td>481.093333</td>\n",
              "      <td>38.513333</td>\n",
              "      <td>542.926667</td>\n",
              "      <td>36.496667</td>\n",
              "      <td>604.226667</td>\n",
              "      <td>34.500000</td>\n",
              "      <td>665.543333</td>\n",
              "      <td>32.463333</td>\n",
              "      <td>726.873333</td>\n",
              "      <td>19263.240000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>86.746758</td>\n",
              "      <td>11.828456</td>\n",
              "      <td>254.868905</td>\n",
              "      <td>11.378991</td>\n",
              "      <td>288.032481</td>\n",
              "      <td>10.728794</td>\n",
              "      <td>322.623073</td>\n",
              "      <td>10.108608</td>\n",
              "      <td>358.265780</td>\n",
              "      <td>9.496452</td>\n",
              "      <td>394.604960</td>\n",
              "      <td>12254.976281</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>20.000000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>56.000000</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>59.000000</td>\n",
              "      <td>17.000000</td>\n",
              "      <td>62.000000</td>\n",
              "      <td>16.000000</td>\n",
              "      <td>65.000000</td>\n",
              "      <td>1050.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>75.750000</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>251.750000</td>\n",
              "      <td>29.000000</td>\n",
              "      <td>282.500000</td>\n",
              "      <td>27.000000</td>\n",
              "      <td>317.000000</td>\n",
              "      <td>26.000000</td>\n",
              "      <td>349.000000</td>\n",
              "      <td>24.000000</td>\n",
              "      <td>384.250000</td>\n",
              "      <td>8808.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>150.500000</td>\n",
              "      <td>41.000000</td>\n",
              "      <td>489.000000</td>\n",
              "      <td>39.000000</td>\n",
              "      <td>541.000000</td>\n",
              "      <td>37.000000</td>\n",
              "      <td>592.000000</td>\n",
              "      <td>35.000000</td>\n",
              "      <td>653.000000</td>\n",
              "      <td>33.000000</td>\n",
              "      <td>710.500000</td>\n",
              "      <td>17409.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>225.250000</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>700.750000</td>\n",
              "      <td>48.000000</td>\n",
              "      <td>797.250000</td>\n",
              "      <td>45.000000</td>\n",
              "      <td>886.250000</td>\n",
              "      <td>43.000000</td>\n",
              "      <td>977.750000</td>\n",
              "      <td>40.000000</td>\n",
              "      <td>1057.000000</td>\n",
              "      <td>27759.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>300.000000</td>\n",
              "      <td>60.000000</td>\n",
              "      <td>949.000000</td>\n",
              "      <td>57.000000</td>\n",
              "      <td>1104.000000</td>\n",
              "      <td>54.000000</td>\n",
              "      <td>1273.000000</td>\n",
              "      <td>51.000000</td>\n",
              "      <td>1443.000000</td>\n",
              "      <td>48.000000</td>\n",
              "      <td>1612.000000</td>\n",
              "      <td>53238.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Item_id  Base_Price  ...       Units4  Base_Revenue_Per_Item\n",
              "count  300.000000  300.000000  ...   300.000000             300.000000\n",
              "mean   150.500000   40.063333  ...   726.873333           19263.240000\n",
              "std     86.746758   11.828456  ...   394.604960           12254.976281\n",
              "min      1.000000   20.000000  ...    65.000000            1050.000000\n",
              "25%     75.750000   30.000000  ...   384.250000            8808.500000\n",
              "50%    150.500000   41.000000  ...   710.500000           17409.000000\n",
              "75%    225.250000   50.000000  ...  1057.000000           27759.000000\n",
              "max    300.000000   60.000000  ...  1612.000000           53238.000000\n",
              "\n",
              "[8 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-uD0dxeWv8SY",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "baserpi = nba['Base_Price'] * nba['Base_Units']\n",
        "nba['Base_Revenue_Per_Item'] = baserpi"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "42JZVu6dxzUN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "outputId": "5e220179-0b1e-4353-ee80-0a7fd606f455"
      },
      "source": [
        "nba"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Item_id</th>\n",
              "      <th>Base_Price</th>\n",
              "      <th>Base_Units</th>\n",
              "      <th>Price1</th>\n",
              "      <th>Units1</th>\n",
              "      <th>Price2</th>\n",
              "      <th>Units2</th>\n",
              "      <th>Price3</th>\n",
              "      <th>Units3</th>\n",
              "      <th>Price4</th>\n",
              "      <th>Units4</th>\n",
              "      <th>Base_Revenue_Per_Item</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>54</td>\n",
              "      <td>79</td>\n",
              "      <td>52</td>\n",
              "      <td>94</td>\n",
              "      <td>49</td>\n",
              "      <td>108</td>\n",
              "      <td>46</td>\n",
              "      <td>122</td>\n",
              "      <td>44</td>\n",
              "      <td>137</td>\n",
              "      <td>4266</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>56</td>\n",
              "      <td>803</td>\n",
              "      <td>54</td>\n",
              "      <td>928</td>\n",
              "      <td>51</td>\n",
              "      <td>1053</td>\n",
              "      <td>48</td>\n",
              "      <td>1177</td>\n",
              "      <td>45</td>\n",
              "      <td>1302</td>\n",
              "      <td>44968</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>48</td>\n",
              "      <td>563</td>\n",
              "      <td>46</td>\n",
              "      <td>653</td>\n",
              "      <td>44</td>\n",
              "      <td>743</td>\n",
              "      <td>41</td>\n",
              "      <td>833</td>\n",
              "      <td>39</td>\n",
              "      <td>923</td>\n",
              "      <td>27024</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>49</td>\n",
              "      <td>65</td>\n",
              "      <td>47</td>\n",
              "      <td>71</td>\n",
              "      <td>45</td>\n",
              "      <td>76</td>\n",
              "      <td>42</td>\n",
              "      <td>82</td>\n",
              "      <td>40</td>\n",
              "      <td>87</td>\n",
              "      <td>3185</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>22</td>\n",
              "      <td>497</td>\n",
              "      <td>21</td>\n",
              "      <td>589</td>\n",
              "      <td>20</td>\n",
              "      <td>680</td>\n",
              "      <td>19</td>\n",
              "      <td>771</td>\n",
              "      <td>18</td>\n",
              "      <td>862</td>\n",
              "      <td>10934</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",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>295</th>\n",
              "      <td>296</td>\n",
              "      <td>43</td>\n",
              "      <td>493</td>\n",
              "      <td>41</td>\n",
              "      <td>547</td>\n",
              "      <td>39</td>\n",
              "      <td>601</td>\n",
              "      <td>37</td>\n",
              "      <td>654</td>\n",
              "      <td>35</td>\n",
              "      <td>708</td>\n",
              "      <td>21199</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>296</th>\n",
              "      <td>297</td>\n",
              "      <td>41</td>\n",
              "      <td>502</td>\n",
              "      <td>39</td>\n",
              "      <td>585</td>\n",
              "      <td>37</td>\n",
              "      <td>667</td>\n",
              "      <td>35</td>\n",
              "      <td>749</td>\n",
              "      <td>33</td>\n",
              "      <td>831</td>\n",
              "      <td>20582</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>297</th>\n",
              "      <td>298</td>\n",
              "      <td>38</td>\n",
              "      <td>748</td>\n",
              "      <td>37</td>\n",
              "      <td>791</td>\n",
              "      <td>35</td>\n",
              "      <td>834</td>\n",
              "      <td>33</td>\n",
              "      <td>877</td>\n",
              "      <td>31</td>\n",
              "      <td>920</td>\n",
              "      <td>28424</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>298</th>\n",
              "      <td>299</td>\n",
              "      <td>33</td>\n",
              "      <td>285</td>\n",
              "      <td>32</td>\n",
              "      <td>316</td>\n",
              "      <td>30</td>\n",
              "      <td>346</td>\n",
              "      <td>29</td>\n",
              "      <td>376</td>\n",
              "      <td>27</td>\n",
              "      <td>407</td>\n",
              "      <td>9405</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>299</th>\n",
              "      <td>300</td>\n",
              "      <td>29</td>\n",
              "      <td>674</td>\n",
              "      <td>28</td>\n",
              "      <td>761</td>\n",
              "      <td>27</td>\n",
              "      <td>847</td>\n",
              "      <td>25</td>\n",
              "      <td>933</td>\n",
              "      <td>24</td>\n",
              "      <td>1019</td>\n",
              "      <td>19546</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>300 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     Item_id  Base_Price  Base_Units  ...  Price4  Units4  Base_Revenue_Per_Item\n",
              "0          1          54          79  ...      44     137                   4266\n",
              "1          2          56         803  ...      45    1302                  44968\n",
              "2          3          48         563  ...      39     923                  27024\n",
              "3          4          49          65  ...      40      87                   3185\n",
              "4          5          22         497  ...      18     862                  10934\n",
              "..       ...         ...         ...  ...     ...     ...                    ...\n",
              "295      296          43         493  ...      35     708                  21199\n",
              "296      297          41         502  ...      33     831                  20582\n",
              "297      298          38         748  ...      31     920                  28424\n",
              "298      299          33         285  ...      27     407                   9405\n",
              "299      300          29         674  ...      24    1019                  19546\n",
              "\n",
              "[300 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qfqkF7pM0uHz",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "Base_Revenue = nba['Base_Revenue_Per_Item'].sum()"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GZPRSK_u03wo",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "b49c38fc-15b8-4893-ecc2-32861e9e83ea"
      },
      "source": [
        "Base_Revenue"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "5778972"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "geUpaXIr08AX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "Total_Base_Units = nba['Base_Units'].sum()"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "263z5Lz-1LsM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "6837c6a0-a7cb-4635-9a0b-bea6eb4e010b"
      },
      "source": [
        "Total_Base_Units"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "144328"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dU_Tfqm12DRB",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "x = 0.10\n",
        "y = 0.25\n",
        "\n",
        "Erevenue = Base_Revenue * x;\n",
        "Equantity = Total_Base_Units * y; "
      ],
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jK6MAKTf-cub",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        },
        "outputId": "b218d1c4-6428-42fb-a4b7-a14b88dfba88"
      },
      "source": [
        "i = nba[nba['Item_id']==300]\n",
        "print(i['Base_Price'])"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "299    29\n",
            "Name: Base_Price, dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QqaTr8BhCOHD",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "d8f3afbc-f9c0-442e-da22-8257cfeee08a"
      },
      "source": [
        "import math\n",
        "er = math.floor(Erevenue)\n",
        "eq = math.floor(Equantity)\n",
        "index = 299\n",
        "\n",
        "key = str(index) +\"_\" + str(er) + \"_\" + str(eq)\n",
        "key"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'299_577897_36082'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JbRGCfGFGN18",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "9d8daa81-a223-40a5-937a-079ae3013822"
      },
      "source": [
        "#HashMap<String, bool> var = new HashMap<String, bool>()\n",
        "\n",
        "import pprint\n",
        "import array\n",
        "import numpy\n",
        "dp = {}\n",
        "def solve(er,eq,index):\n",
        "  if index < 0:\n",
        "    return False\n",
        "  key = str(index) +\"_\" + str(er) + \"_\" + str(eq)\n",
        "  if er<0 and eq<0:\n",
        "    dp[key] = True\n",
        "    return dp[key]\n",
        "  if key in dp.keys(): \n",
        "    return dp[key]\n",
        "  i = nba[nba['Item_id']==index]\n",
        "  #print(i['Base_Price'])\n",
        "  bp = nba.at[index, 'Base_Price'] \n",
        "  bq = nba.at[index, 'Base_Units'] \n",
        "  p1 = nba.at[index, 'Price1']\n",
        "  q1 = nba.at[index, 'Units1'] \n",
        "  p2 = nba.at[index, 'Price2'] \n",
        "  q2 = nba.at[index, 'Units2'] \n",
        "  p3 = nba.at[index, 'Price3'] \n",
        "  q3 = nba.at[index, 'Units3'] \n",
        "  p4 = nba.at[index, 'Price4'] \n",
        "  q4 = nba.at[index, 'Units4'] \n",
        "  dp[key] = solve(er,eq,index-1) or solve(er-(p1*q1-bp*bq),eq-(q1-bq),index-1) or solve(er-(p2*q2-bp*bq),eq-(q2-bq),index-1) or solve(er-(p3*q3-bp*bq),eq-(q3-bq),index-1) or solve(er-(p4*q4-bp*bq),eq-(q4-bq),index-1)\n",
        "            # solve(er- p1*q1,eq-q1,n-1) or\n",
        "            # solve(er- p2*q2,eq-q2,n-1) or\n",
        "            # solve(er- p3*q3,eq-q3,n-1) or\n",
        "            # solve(er- p4*q4,eq-q4,n-1)\n",
        "  return dp[key]\n",
        "solve(er, eq, 299)"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ERROR:root:Internal Python error in the inspect module.\n",
            "Below is the traceback from this internal error.\n",
            "\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\", line 2882, in run_code\n",
            "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
            "  File \"<ipython-input-44-ac7c54637366>\", line 34, in <module>\n",
            "    solve(er, eq, 299)\n",
            "  File \"<ipython-input-44-ac7c54637366>\", line 28, in solve\n",
            "    dp[key] = solve(er,eq,index-1) or solve(er-(p1*q1-bp*bq),eq-(q1-bq),index-1) or solve(er-(p2*q2-bp*bq),eq-(q2-bq),index-1) or solve(er-(p3*q3-bp*bq),eq-(q3-bq),index-1) or solve(er-(p4*q4-bp*bq),eq-(q4-bq),index-1)\n",
            "  File \"<ipython-input-44-ac7c54637366>\", line 28, in solve\n",
            "    dp[key] = solve(er,eq,index-1) or solve(er-(p1*q1-bp*bq),eq-(q1-bq),index-1) or solve(er-(p2*q2-bp*bq),eq-(q2-bq),index-1) or solve(er-(p3*q3-bp*bq),eq-(q3-bq),index-1) or solve(er-(p4*q4-bp*bq),eq-(q4-bq),index-1)\n",
            "  File \"<ipython-input-44-ac7c54637366>\", line 28, in solve\n",
            "    dp[key] = solve(er,eq,index-1) or solve(er-(p1*q1-bp*bq),eq-(q1-bq),index-1) or solve(er-(p2*q2-bp*bq),eq-(q2-bq),index-1) or solve(er-(p3*q3-bp*bq),eq-(q3-bq),index-1) or solve(er-(p4*q4-bp*bq),eq-(q4-bq),index-1)\n",
            "  [Previous line repeated 296 more times]\n",
            "  File \"<ipython-input-44-ac7c54637366>\", line 16, in solve\n",
            "    i = nba[nba['Item_id']==index]\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/pandas/core/frame.py\", line 2791, in __getitem__\n",
            "    return self._getitem_bool_array(key)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/pandas/core/frame.py\", line 2845, in _getitem_bool_array\n",
            "    return self._take_with_is_copy(indexer, axis=0)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/pandas/core/generic.py\", line 3409, in _take_with_is_copy\n",
            "    result = self.take(indices=indices, axis=axis, **kwargs)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/pandas/core/generic.py\", line 3395, in take\n",
            "    indices, axis=self._get_block_manager_axis(axis), verify=True\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/pandas/core/internals/managers.py\", line 1392, in take\n",
            "    new_labels = self.axes[axis].take(indexer)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/base.py\", line 764, in take\n",
            "    return self._shallow_copy(taken)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/range.py\", line 394, in _shallow_copy\n",
            "    return self._int64index._shallow_copy(values, **kwargs)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/numeric.py\", line 111, in _shallow_copy\n",
            "    return self._shallow_copy_with_infer(values=values, **kwargs)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/base.py\", line 567, in _shallow_copy_with_infer\n",
            "    return Index(values, **attributes)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/base.py\", line 284, in __new__\n",
            "    if isinstance(data, ABCPandasArray):\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/pandas/core/dtypes/generic.py\", line 12, in _check\n",
            "    return getattr(inst, attr, \"_typ\") in comp\n",
            "KeyboardInterrupt\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\", line 1823, in showtraceback\n",
            "    stb = value._render_traceback_()\n",
            "AttributeError: 'KeyboardInterrupt' object has no attribute '_render_traceback_'\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/IPython/core/ultratb.py\", line 1132, in get_records\n",
            "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/IPython/core/ultratb.py\", line 313, in wrapped\n",
            "    return f(*args, **kwargs)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/IPython/core/ultratb.py\", line 358, in _fixed_getinnerframes\n",
            "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
            "  File \"/usr/lib/python3.6/inspect.py\", line 1490, in getinnerframes\n",
            "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
            "  File \"/usr/lib/python3.6/inspect.py\", line 1448, in getframeinfo\n",
            "    filename = getsourcefile(frame) or getfile(frame)\n",
            "  File \"/usr/lib/python3.6/inspect.py\", line 696, in getsourcefile\n",
            "    if getattr(getmodule(object, filename), '__loader__', None) is not None:\n",
            "  File \"/usr/lib/python3.6/inspect.py\", line 732, in getmodule\n",
            "    for modname, module in list(sys.modules.items()):\n",
            "KeyboardInterrupt\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GE2dvy2ewVPn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        },
        "outputId": "e80c4127-3c3c-408b-de8b-c90f0c9e6cc2"
      },
      "source": [
        "i = nba[nba['Item_id']==299]\n",
        "print(i['Base_Price'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "298    33\n",
            "Name: Base_Price, dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "br72BQjyfXD_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import array\n",
        "import numpy \n",
        "index = 299\n",
        "# ans = array.array('i')\n",
        "size = 300\n",
        "ans = [0] * size\n",
        "def backtrack(index,er,eq):\n",
        "  i = nba[nba['Item_id']==index]\n",
        "  print(i['Base_Price'])\n",
        " # nba.at[index, 'Base_Price'] \n",
        "  bp = nba.at[index, 'Base_Price'] \n",
        "  bq = nba.at[index, 'Base_Units'] \n",
        "  p1 = nba.at[index, 'Price1']\n",
        "  q1 = nba.at[index, 'Units1'] \n",
        "  p2 = nba.at[index, 'Price2'] \n",
        "  q2 = nba.at[index, 'Units2'] \n",
        "  p3 = nba.at[index, 'Price3'] \n",
        "  q3 = nba.at[index, 'Units3'] \n",
        "  p4 = nba.at[index, 'Price4'] \n",
        "  q4 = nba.at[index, 'Units4'] \n",
        "  print(bp)\n",
        "  print(bq)\n",
        "  print(p1)\n",
        "  print(p2)\n",
        "  print(p3)\n",
        "  print(p4)\n",
        "  print(q1)\n",
        "  print(q2)\n",
        "  print(q3)\n",
        "  print(q4)\n",
        "  key1 = str(index) +\"_\" + str(er - p1*q1) + \"_\" + str(eq - q1)\n",
        "  key2 = str(index) +\"_\" + str(er - p2*q2) + \"_\" + str(eq - q2)\n",
        "  key3 = str(index) +\"_\" + str(er - p3*q3) + \"_\" + str(eq - q3)\n",
        "  key4 = str(index) +\"_\" + str(er - p4*q4) + \"_\" + str(eq - q4)\n",
        "  key5 = str(index) +\"_\" + str(er - bp*bq) + \"_\" + str(eq - bq)\n",
        "  if key1 in dp and dp[key1]:\n",
        "    ans[i] = 1;\n",
        "    backtrack(index-1, er - p1*q1, eq-q1)\n",
        "  elif key2 in dp and dp[key2]:\n",
        "    ans[i] = 2;\n",
        "    backtrack(index-1, er - p2*q2, eq-q2)\n",
        "  elif key3 in dp and dp[key3]:\n",
        "    ans[i] = 3\n",
        "    backtrack(index-1, er - p3*q3, eq-q3)\n",
        "  elif key4 in dp and dp[key4]:\n",
        "    ans[i] = 4;\n",
        "    backtrack(index-1,er - p4*q4,eq-q4)\n",
        "  elif key5 in dp and dp[key5]:\n",
        "    backtrack(index-1,er - bp*bq,eq-bq)\n",
        "  return"
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YMLFgeqfvVoB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 218
        },
        "outputId": "f123c420-eb4d-4f0f-b1f5-8ac1d4322ff2"
      },
      "source": [
        "solve(1000, 1000, 10)\n",
        "backtrack(10, 1000, 1000)\n",
        "\n",
        "# for i in range (0, 299): \n",
        "#     print (ans[i], end =\" \") \n",
        "# print() "
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "9    32\n",
            "Name: Base_Price, dtype: int64\n",
            "34\n",
            "244\n",
            "33\n",
            "31\n",
            "29\n",
            "28\n",
            "292\n",
            "339\n",
            "387\n",
            "434\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}