pd_reading_csv.ipynb

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      "name": "pd reading csv.ipynb",
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        "<a href=\"https://colab.research.google.com/github/Jarvood11/Antilink-spam-system/blob/master/pd_reading_csv.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "code",
      "metadata": {
        "id": "YuiPDigbJQ7Z"
      },
      "source": [
        "import pandas as pd"
      ],
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      "outputs": []
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    {
      "cell_type": "markdown",
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        "id": "7mPfVLoNWOnT"
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        ""
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      "source": [
        "df = pd.read_excel(\"Чеки71.xlsx\")"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>Waterman Ручка роллер Expert Black CT черная к...</td>\n",
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              "      <td>Berlingo Ручка шариковая PR-05 синяя</td>\n",
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              "      <td>Алексеевский</td>\n",
              "      <td>Waterman Ручка роллер Exception Slim Black CT ...</td>\n",
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              "      <td>59</td>\n",
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              "      <td>4130</td>\n",
              "      <td>24</td>\n",
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              "    ID       District  ... Ранг num\n",
              "0  254  Академический  ...  428   1\n",
              "1  144  Академический  ...  428   1\n",
              "2  815  Академический  ...  568   1\n",
              "3  652   Алексеевский  ...   24   2\n",
              "4  935   Алексеевский  ...   50   2\n",
              "\n",
              "[5 rows x 9 columns]"
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        ""
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      "source": [
        "districts = {v: i + 1 for i, v in enumerate(list(df[\"District\"].unique()))}"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
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      "source": [
        "rangs = {v: len(df) - i for i, v in enumerate(sorted(list(df[\"Quantity\"])))}"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
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      "source": [
        "df[\"num_1\"] = df[\"District\"].map(districts)\n",
        "df[\"Ранг_1\"] = df[\"Quantity\"].map(rangs)"
      ],
      "execution_count": null,
      "outputs": []
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      "source": [
        "df.head()"
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              "      <td>Waterman Ручка роллер Expert Black CT черная к...</td>\n",
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              "      <td>4130</td>\n",
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            "text/plain": [
              "    ID       District  ... num_1 Ранг_1\n",
              "0  254  Академический  ...     1    428\n",
              "1  144  Академический  ...     1    428\n",
              "2  815  Академический  ...     1    568\n",
              "3  652   Алексеевский  ...     2     24\n",
              "4  935   Алексеевский  ...     2     50\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
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          "execution_count": 55
        }
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        "outputId": "cc007f90-f38b-4900-a67e-195d2a1c0aa7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 145
        }
      },
      "source": [
        "test_item = \"Berlingo Ручка шариковая PR-05 синяя\"\n",
        "idx = [1, 51]\n",
        "\n",
        "def check_num_in_idx(df, idx: list):\n",
        "  mask = df[\"num\"] == idx[0]\n",
        "  for id in idx[1:]:\n",
        "    mask |= df[\"num\"] == id\n",
        "  return mask\n",
        "\n",
        "df.loc[(check_num_in_idx(df, idx)) & (df[\"Item\"] == test_item)]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>District</th>\n",
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              "      <th>Tip_item</th>\n",
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              "      <th>num</th>\n",
              "      <th>num_1</th>\n",
              "      <th>Ранг_1</th>\n",
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              "  <tbody>\n",
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              "      <th>1</th>\n",
              "      <td>144</td>\n",
              "      <td>Академический</td>\n",
              "      <td>Berlingo Ручка шариковая PR-05 синяя</td>\n",
              "      <td>Ручки</td>\n",
              "      <td>39</td>\n",
              "      <td>93</td>\n",
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              "      <th>326</th>\n",
              "      <td>173</td>\n",
              "      <td>Крюково</td>\n",
              "      <td>Berlingo Ручка шариковая PR-05 синяя</td>\n",
              "      <td>Ручки</td>\n",
              "      <td>50</td>\n",
              "      <td>32</td>\n",
              "      <td>1600</td>\n",
              "      <td>196</td>\n",
              "      <td>51</td>\n",
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              "      <td>196</td>\n",
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            "text/plain": [
              "      ID       District  ... num_1 Ранг_1\n",
              "1    144  Академический  ...     1    428\n",
              "326  173        Крюково  ...    51    196\n",
              "\n",
              "[2 rows x 11 columns]"
            ]
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          "execution_count": 65
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      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}