PandasEvent.ipynb

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      "cell_type": "markdown",
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        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/nksrivastavaa/ML-workshop/blob/main/PandasEvent.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wbAK0G_O8edo"
      },
      "source": [
        "# Hands on with Pandas"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/BioBytesIIITD/EventData.git"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yt5qY8Tx8vIS",
        "outputId": "1e941ace-f6ed-4c8b-d34d-baec7b813347"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "fatal: destination path 'EventData' already exists and is not an empty directory.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0muERA3v8edr"
      },
      "source": [
        "### Importing the Library, Checking Version and Aliasing it"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ebPufK3X8eds"
      },
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "YPjBfTAy8edt",
        "outputId": "296451c3-57d7-4cc9-d03a-8d4c5c4d4822"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'1.3.5'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 3
        }
      ],
      "source": [
        "pd.__version__"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GYoafLEe8edu"
      },
      "source": [
        "Knowing Version is important at times as you might find a solution for your problem on stackoverflow but it might be for a different version"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sjfoU_Hc8edu"
      },
      "source": [
        "### Reading CSV and other types of files"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "JdctxyYA8edv"
      },
      "outputs": [],
      "source": [
        "df = pd.read_csv('EventData/cooldata/csvdata.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "outputId": "5226bb96-2d1f-4c1f-d339-3e5454d479bd"
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      "outputs": [
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          "output_type": "execute_result",
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              "           DATE   INVCMRMT\n",
              "0    1997-01-01  1301161.0\n",
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              "3    1997-04-01  1319740.0\n",
              "4    1997-05-01  1327294.0\n",
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              "281  2020-06-01  2125810.0\n",
              "282  2020-07-01  2121991.0\n",
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        "df"
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VLUmKMvK8edv"
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      "outputs": [],
      "source": [
        "df2 = pd.read_excel('EventData/cooldata/exceldata.xlsx')"
      ]
    },
    {
      "cell_type": "code",
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            "text/plain": [
              "        Year  Stocks T.Bills T.Bonds\n",
              "0       1928  0.4381  0.0308  0.0084\n",
              "1       1929  -0.083  0.0316   0.042\n",
              "2       1930 -0.2512  0.0455  0.0454\n",
              "3       1931 -0.4384  0.0231 -0.0256\n",
              "4       1932 -0.0864  0.0107  0.0879\n",
              "..       ...     ...     ...     ...\n",
              "79      2007  0.0549  0.0988  0.0466\n",
              "80      2008   -0.37  0.2587   0.016\n",
              "81      2009  0.2646  -0.149   0.001\n",
              "82       NaN  stocks  tbills   bonds\n",
              "83  averages     NaN     NaN     NaN\n",
              "\n",
              "[84 rows x 4 columns]"
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              "      <td>0.0549</td>\n",
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              "      <td>0.0466</td>\n",
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              "      <th>80</th>\n",
              "      <td>2008</td>\n",
              "      <td>-0.37</td>\n",
              "      <td>0.2587</td>\n",
              "      <td>0.016</td>\n",
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              "      <th>81</th>\n",
              "      <td>2009</td>\n",
              "      <td>0.2646</td>\n",
              "      <td>-0.149</td>\n",
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              "      <th>83</th>\n",
              "      <td>averages</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "                                                     [key], {});\n",
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      "source": [
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    {
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      "metadata": {
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      "outputs": [],
      "source": [
        "df3 = pd.read_csv('EventData/cooldata/tsvdata.tsv', sep = '\\t') # We tell Pandas don't look for commas rather look for tab spaces"
      ]
    },
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        "id": "yAnTgm-X8edw",
        "outputId": "a00fed34-4373-463d-94f9-3944a21f3524"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          country continent  year  lifeExp       pop   gdpPercap\n",
              "0     Afghanistan      Asia  1952   28.801   8425333  779.445314\n",
              "1     Afghanistan      Asia  1957   30.332   9240934  820.853030\n",
              "2     Afghanistan      Asia  1962   31.997  10267083  853.100710\n",
              "3     Afghanistan      Asia  1967   34.020  11537966  836.197138\n",
              "4     Afghanistan      Asia  1972   36.088  13079460  739.981106\n",
              "...           ...       ...   ...      ...       ...         ...\n",
              "1699     Zimbabwe    Africa  1987   62.351   9216418  706.157306\n",
              "1700     Zimbabwe    Africa  1992   60.377  10704340  693.420786\n",
              "1701     Zimbabwe    Africa  1997   46.809  11404948  792.449960\n",
              "1702     Zimbabwe    Africa  2002   39.989  11926563  672.038623\n",
              "1703     Zimbabwe    Africa  2007   43.487  12311143  469.709298\n",
              "\n",
              "[1704 rows x 6 columns]"
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              "      <th>continent</th>\n",
              "      <th>year</th>\n",
              "      <th>lifeExp</th>\n",
              "      <th>pop</th>\n",
              "      <th>gdpPercap</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1952</td>\n",
              "      <td>28.801</td>\n",
              "      <td>8425333</td>\n",
              "      <td>779.445314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1957</td>\n",
              "      <td>30.332</td>\n",
              "      <td>9240934</td>\n",
              "      <td>820.853030</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1962</td>\n",
              "      <td>31.997</td>\n",
              "      <td>10267083</td>\n",
              "      <td>853.100710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1967</td>\n",
              "      <td>34.020</td>\n",
              "      <td>11537966</td>\n",
              "      <td>836.197138</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1972</td>\n",
              "      <td>36.088</td>\n",
              "      <td>13079460</td>\n",
              "      <td>739.981106</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1699</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>1987</td>\n",
              "      <td>62.351</td>\n",
              "      <td>9216418</td>\n",
              "      <td>706.157306</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1700</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>1992</td>\n",
              "      <td>60.377</td>\n",
              "      <td>10704340</td>\n",
              "      <td>693.420786</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1701</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>1997</td>\n",
              "      <td>46.809</td>\n",
              "      <td>11404948</td>\n",
              "      <td>792.449960</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1702</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>2002</td>\n",
              "      <td>39.989</td>\n",
              "      <td>11926563</td>\n",
              "      <td>672.038623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1703</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>2007</td>\n",
              "      <td>43.487</td>\n",
              "      <td>12311143</td>\n",
              "      <td>469.709298</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1704 rows × 6 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-47cb3e79-67a5-4ad3-a9a1-3ad0377ac2e6')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
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              "      height: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-47cb3e79-67a5-4ad3-a9a1-3ad0377ac2e6 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-47cb3e79-67a5-4ad3-a9a1-3ad0377ac2e6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "df3"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vG4G4W2w8edx"
      },
      "source": [
        "## More about them here - \n",
        "- https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html\n",
        "- https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dtFNNrmE8edx"
      },
      "source": [
        "### General Overview of Data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GC78U1oT8edx",
        "outputId": "8fca3175-2e81-402e-ae21-60b680c0120b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(283, 2)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "df.shape "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "iwD6pMFs8edx",
        "outputId": "fae8309a-b917-432f-e38e-8c67c397e2a7"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         DATE   INVCMRMT\n",
              "0  1997-01-01  1301161.0\n",
              "1  1997-02-01  1307080.0\n",
              "2  1997-03-01  1303978.0\n",
              "3  1997-04-01  1319740.0\n",
              "4  1997-05-01  1327294.0"
            ],
            "text/html": [
              "\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1997-01-01</td>\n",
              "      <td>1301161.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1997-02-01</td>\n",
              "      <td>1307080.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1997-03-01</td>\n",
              "      <td>1303978.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1997-04-01</td>\n",
              "      <td>1319740.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1997-05-01</td>\n",
              "      <td>1327294.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0f48f611-d5af-4122-8057-31bf1fb0e06e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "      </button>\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0f48f611-d5af-4122-8057-31bf1fb0e06e button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0f48f611-d5af-4122-8057-31bf1fb0e06e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "df.head() # You can see () after head as it is a function, head() is useful to see if the dataset has been loaded propely or not"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "qsJPRdki8edy",
        "outputId": "6418e3e6-2a7c-46cd-ae81-be6c30e37315"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         DATE   INVCMRMT\n",
              "0  1997-01-01  1301161.0\n",
              "1  1997-02-01  1307080.0\n",
              "2  1997-03-01  1303978.0"
            ],
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              "      <th>0</th>\n",
              "      <td>1997-01-01</td>\n",
              "      <td>1301161.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1997-02-01</td>\n",
              "      <td>1307080.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1997-03-01</td>\n",
              "      <td>1303978.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-734f7eee-186d-4f84-8ac7-75eacfc6723c')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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          "metadata": {},
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      "source": [
        "df.head(3) # You can customize number of rows you want "
      ]
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              "           DATE   INVCMRMT\n",
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              "      <th>282</th>\n",
              "      <td>2020-07-01</td>\n",
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              "                                                     [key], {});\n",
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              "\n",
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          },
          "metadata": {},
          "execution_count": 13
        }
      ],
      "source": [
        "df.tail() # Last view rows (5 by default)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2Z8gmxPY8edy",
        "outputId": "b7afc5aa-4442-4218-f03e-922acd606d45"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['DATE', 'INVCMRMT'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "df.columns # No () after columns as it is not a function but an attribute of the dataframe"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NZhBn_aV8edy",
        "outputId": "22468b98-5346-4cdb-99f5-b5d78beefc1c"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RangeIndex(start=0, stop=283, step=1)"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ],
      "source": [
        "df.index"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fuSx3cUr8edy",
        "outputId": "3d16a042-25e9-404f-eb49-381d2e3aa2b6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 283 entries, 0 to 282\n",
            "Data columns (total 2 columns):\n",
            " #   Column    Non-Null Count  Dtype  \n",
            "---  ------    --------------  -----  \n",
            " 0   DATE      283 non-null    object \n",
            " 1   INVCMRMT  283 non-null    float64\n",
            "dtypes: float64(1), object(1)\n",
            "memory usage: 4.5+ KB\n"
          ]
        }
      ],
      "source": [
        "df.info() # Concise Summary"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xjFsjZXR8edz",
        "outputId": "393503f2-f008-474e-bb32-9a578d1f91e9"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas.core.frame.DataFrame"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "type(df)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_isU6aDD8edz"
      },
      "source": [
        "Let's say you have a dataframe and you want to use it with some other library but it does not support pandas dataframe objects, a simple way is to use the df.values and convert it into a numpy array "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ErNjEmYQ8edz",
        "outputId": "5d9215fb-0f76-4191-adc5-9cdf052a1ae2"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "       ['2009-10-01', 1610476.0],\n",
              "       ['2009-11-01', 1612759.0],\n",
              "       ['2009-12-01', 1604026.0],\n",
              "       ['2010-01-01', 1602743.0],\n",
              "       ['2010-02-01', 1605271.0],\n",
              "       ['2010-03-01', 1607725.0],\n",
              "       ['2010-04-01', 1608913.0],\n",
              "       ['2010-05-01', 1606114.0],\n",
              "       ['2010-06-01', 1615168.0],\n",
              "       ['2010-07-01', 1625366.0],\n",
              "       ['2010-08-01', 1635130.0],\n",
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              "       ['2010-10-01', 1656675.0],\n",
              "       ['2010-11-01', 1656120.0],\n",
              "       ['2010-12-01', 1663852.0],\n",
              "       ['2011-01-01', 1665177.0],\n",
              "       ['2011-02-01', 1664173.0],\n",
              "       ['2011-03-01', 1672664.0],\n",
              "       ['2011-04-01', 1679090.0],\n",
              "       ['2011-05-01', 1687537.0],\n",
              "       ['2011-06-01', 1691018.0],\n",
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              "       ['2011-08-01', 1695545.0],\n",
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              "       ['2011-10-01', 1696715.0],\n",
              "       ['2011-11-01', 1703512.0],\n",
              "       ['2011-12-01', 1709421.0],\n",
              "       ['2012-01-01', 1714925.0],\n",
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              "       ['2012-03-01', 1729963.0],\n",
              "       ['2012-04-01', 1735732.0],\n",
              "       ['2012-05-01', 1743584.0],\n",
              "       ['2012-06-01', 1749502.0],\n",
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              "       ['2012-10-01', 1775242.0],\n",
              "       ['2012-11-01', 1780540.0],\n",
              "       ['2012-12-01', 1784009.0],\n",
              "       ['2013-01-01', 1799869.0],\n",
              "       ['2013-02-01', 1803481.0],\n",
              "       ['2013-03-01', 1806109.0],\n",
              "       ['2013-04-01', 1813121.0],\n",
              "       ['2013-05-01', 1815245.0],\n",
              "       ['2013-06-01', 1819522.0],\n",
              "       ['2013-07-01', 1827709.0],\n",
              "       ['2013-08-01', 1838062.0],\n",
              "       ['2013-09-01', 1848087.0],\n",
              "       ['2013-10-01', 1860310.0],\n",
              "       ['2013-11-01', 1871121.0],\n",
              "       ['2013-12-01', 1878653.0],\n",
              "       ['2014-01-01', 1884483.0],\n",
              "       ['2014-02-01', 1890844.0],\n",
              "       ['2014-03-01', 1893923.0],\n",
              "       ['2014-04-01', 1901124.0],\n",
              "       ['2014-05-01', 1908092.0],\n",
              "       ['2014-06-01', 1912524.0],\n",
              "       ['2014-07-01', 1921453.0],\n",
              "       ['2014-08-01', 1928057.0],\n",
              "       ['2014-09-01', 1930589.0],\n",
              "       ['2014-10-01', 1938554.0],\n",
              "       ['2014-11-01', 1944816.0],\n",
              "       ['2014-12-01', 1947203.0],\n",
              "       ['2015-01-01', 1954906.0],\n",
              "       ['2015-02-01', 1967795.0],\n",
              "       ['2015-03-01', 1975742.0],\n",
              "       ['2015-04-01', 1987557.0],\n",
              "       ['2015-05-01', 1993371.0],\n",
              "       ['2015-06-01', 2005310.0],\n",
              "       ['2015-07-01', 2011272.0],\n",
              "       ['2015-08-01', 2017750.0],\n",
              "       ['2015-09-01', 2028458.0],\n",
              "       ['2015-10-01', 2037127.0],\n",
              "       ['2015-11-01', 2037636.0],\n",
              "       ['2015-12-01', 2042724.0],\n",
              "       ['2016-01-01', 2045270.0],\n",
              "       ['2016-02-01', 2043474.0],\n",
              "       ['2016-03-01', 2052727.0],\n",
              "       ['2016-04-01', 2057515.0],\n",
              "       ['2016-05-01', 2057006.0],\n",
              "       ['2016-06-01', 2054929.0],\n",
              "       ['2016-07-01', 2051079.0],\n",
              "       ['2016-08-01', 2051927.0],\n",
              "       ['2016-09-01', 2056007.0],\n",
              "       ['2016-10-01', 2054770.0],\n",
              "       ['2016-11-01', 2065930.0],\n",
              "       ['2016-12-01', 2069867.0],\n",
              "       ['2017-01-01', 2069616.0],\n",
              "       ['2017-02-01', 2066881.0],\n",
              "       ['2017-03-01', 2068191.0],\n",
              "       ['2017-04-01', 2063455.0],\n",
              "       ['2017-05-01', 2067188.0],\n",
              "       ['2017-06-01', 2074142.0],\n",
              "       ['2017-07-01', 2077863.0],\n",
              "       ['2017-08-01', 2086790.0],\n",
              "       ['2017-09-01', 2088135.0],\n",
              "       ['2017-10-01', 2086084.0],\n",
              "       ['2017-11-01', 2093438.0],\n",
              "       ['2017-12-01', 2096385.0],\n",
              "       ['2018-01-01', 2103620.0],\n",
              "       ['2018-02-01', 2112722.0],\n",
              "       ['2018-03-01', 2111511.0],\n",
              "       ['2018-04-01', 2113456.0],\n",
              "       ['2018-05-01', 2114511.0],\n",
              "       ['2018-06-01', 2113749.0],\n",
              "       ['2018-07-01', 2122281.0],\n",
              "       ['2018-08-01', 2129534.0],\n",
              "       ['2018-09-01', 2135205.0],\n",
              "       ['2018-10-01', 2143767.0],\n",
              "       ['2018-11-01', 2143229.0],\n",
              "       ['2018-12-01', 2159894.0],\n",
              "       ['2019-01-01', 2174287.0],\n",
              "       ['2019-02-01', 2183374.0],\n",
              "       ['2019-03-01', 2182942.0],\n",
              "       ['2019-04-01', 2185718.0],\n",
              "       ['2019-05-01', 2189679.0],\n",
              "       ['2019-06-01', 2192017.0],\n",
              "       ['2019-07-01', 2200394.0],\n",
              "       ['2019-08-01', 2200320.0],\n",
              "       ['2019-09-01', 2202122.0],\n",
              "       ['2019-10-01', 2203476.0],\n",
              "       ['2019-11-01', 2202134.0],\n",
              "       ['2019-12-01', 2204873.0],\n",
              "       ['2020-01-01', 2199503.0],\n",
              "       ['2020-02-01', 2195308.0],\n",
              "       ['2020-03-01', 2192351.0],\n",
              "       ['2020-04-01', 2178236.0],\n",
              "       ['2020-05-01', 2144828.0],\n",
              "       ['2020-06-01', 2125810.0],\n",
              "       ['2020-07-01', 2121991.0]], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ],
      "source": [
        "df.values "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kXW5s9VL8edz",
        "outputId": "19ae74fd-9a89-4cd0-ce77-bc14e610da9a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "numpy.ndarray"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ],
      "source": [
        "type(df.values)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hc1-4sOs8edz"
      },
      "source": [
        "## Helpful Docs for this section \n",
        "\n",
        "- https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.shape.html\n",
        "- https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.head.html\n",
        "- https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.tail.html\n",
        "- https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.columns.html\n",
        "- https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.index.html\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IIrUT6aL8ed0"
      },
      "source": [
        "### Accessing Columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "colab": {
          "base_uri": "https://localhost:8080/",
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        "id": "xS0ujbMX8ed0",
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         DATE   INVCMRMT\n",
              "0  1997-01-01  1301161.0\n",
              "1  1997-02-01  1307080.0\n",
              "2  1997-03-01  1303978.0\n",
              "3  1997-04-01  1319740.0\n",
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              "      <td>1997-02-01</td>\n",
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              "      <td>1997-03-01</td>\n",
              "      <td>1303978.0</td>\n",
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              "      <th>3</th>\n",
              "      <td>1997-04-01</td>\n",
              "      <td>1319740.0</td>\n",
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              "    <tr>\n",
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              "      <td>1997-05-01</td>\n",
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              "                                                     [key], {});\n",
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          "metadata": {},
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      "source": [
        "df.head()"
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CKusrpXw8ed0",
        "outputId": "930c4355-faf5-4a0b-c0f9-64452e38d099"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      1997-01-01\n",
              "1      1997-02-01\n",
              "2      1997-03-01\n",
              "3      1997-04-01\n",
              "4      1997-05-01\n",
              "          ...    \n",
              "278    2020-03-01\n",
              "279    2020-04-01\n",
              "280    2020-05-01\n",
              "281    2020-06-01\n",
              "282    2020-07-01\n",
              "Name: DATE, Length: 283, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ],
      "source": [
        "df['DATE']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zaUCJN-x8ed0",
        "outputId": "1158c850-ae43-4da5-c048-f634d7c93095"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    1997-01-01\n",
              "1    1997-02-01\n",
              "2    1997-03-01\n",
              "3    1997-04-01\n",
              "4    1997-05-01\n",
              "Name: DATE, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ],
      "source": [
        "df['DATE'].head() # Using Multiple Functions at Once"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KRAfIxHh8ed0"
      },
      "source": [
        "### How to get multiple columns?"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
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        },
        "id": "biz2ncNt8ed0",
        "outputId": "41f29717-4f3d-4b36-9841-4bcec7835f0a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        Year  Stocks T.Bills T.Bonds\n",
              "0       1928  0.4381  0.0308  0.0084\n",
              "1       1929  -0.083  0.0316   0.042\n",
              "2       1930 -0.2512  0.0455  0.0454\n",
              "3       1931 -0.4384  0.0231 -0.0256\n",
              "4       1932 -0.0864  0.0107  0.0879\n",
              "..       ...     ...     ...     ...\n",
              "79      2007  0.0549  0.0988  0.0466\n",
              "80      2008   -0.37  0.2587   0.016\n",
              "81      2009  0.2646  -0.149   0.001\n",
              "82       NaN  stocks  tbills   bonds\n",
              "83  averages     NaN     NaN     NaN\n",
              "\n",
              "[84 rows x 4 columns]"
            ],
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              "      <th>4</th>\n",
              "      <td>1932</td>\n",
              "      <td>-0.0864</td>\n",
              "      <td>0.0107</td>\n",
              "      <td>0.0879</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>79</th>\n",
              "      <td>2007</td>\n",
              "      <td>0.0549</td>\n",
              "      <td>0.0988</td>\n",
              "      <td>0.0466</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>80</th>\n",
              "      <td>2008</td>\n",
              "      <td>-0.37</td>\n",
              "      <td>0.2587</td>\n",
              "      <td>0.016</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>81</th>\n",
              "      <td>2009</td>\n",
              "      <td>0.2646</td>\n",
              "      <td>-0.149</td>\n",
              "      <td>0.001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>82</th>\n",
              "      <td>NaN</td>\n",
              "      <td>stocks</td>\n",
              "      <td>tbills</td>\n",
              "      <td>bonds</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>83</th>\n",
              "      <td>averages</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>84 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-16804c1a-e5f6-4cd5-ba15-065f65cca2ad')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-16804c1a-e5f6-4cd5-ba15-065f65cca2ad button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-16804c1a-e5f6-4cd5-ba15-065f65cca2ad');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ],
      "source": [
        "df2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "A8eM-G398ed0"
      },
      "outputs": [],
      "source": [
        "df_subset = df2[['Year', 'Stocks']] # Pass a list of all the columns which you want"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "Nou56uxl8ed1",
        "outputId": "9cb7e59f-d712-42dd-a099-0af12e1ff10b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Year  Stocks\n",
              "0  1928  0.4381\n",
              "1  1929  -0.083"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-930e1827-8517-48a5-9921-aea02892deed\">\n",
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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>Stocks</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1928</td>\n",
              "      <td>0.4381</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1929</td>\n",
              "      <td>-0.083</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-930e1827-8517-48a5-9921-aea02892deed')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-930e1827-8517-48a5-9921-aea02892deed button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-930e1827-8517-48a5-9921-aea02892deed');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ],
      "source": [
        "df_subset.head(2)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hJai49ZW8ed1"
      },
      "source": [
        "### Accessing Rows "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "qWubn3xZ8ed1",
        "outputId": "7443e1d1-78ac-4f4a-fb6e-ede3d6ce33f7"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         DATE   INVCMRMT\n",
              "0  1997-01-01  1301161.0\n",
              "1  1997-02-01  1307080.0\n",
              "2  1997-03-01  1303978.0\n",
              "3  1997-04-01  1319740.0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b96370a8-415e-4b71-8e77-133100fe0029\">\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>DATE</th>\n",
              "      <th>INVCMRMT</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1997-01-01</td>\n",
              "      <td>1301161.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1997-02-01</td>\n",
              "      <td>1307080.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1997-03-01</td>\n",
              "      <td>1303978.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1997-04-01</td>\n",
              "      <td>1319740.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b96370a8-415e-4b71-8e77-133100fe0029')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-b96370a8-415e-4b71-8e77-133100fe0029 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-b96370a8-415e-4b71-8e77-133100fe0029');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ],
      "source": [
        "df.head(4)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7EAcF9rt8ed1"
      },
      "source": [
        "### Using loc"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "67NRpXvD8ed1",
        "outputId": "c7fcded3-4a4d-4ef7-e1fe-4758c0ceeb53"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DATE        1997-03-01\n",
              "INVCMRMT     1303978.0\n",
              "Name: 2, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ],
      "source": [
        "df.loc[2] # Picks Index from the index of the dataframe which matches the input parameter and not like the second value itself"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rBjHOWVT8ed1"
      },
      "outputs": [],
      "source": [
        "specdf = pd.read_excel('EventData/cooldata/loc.xlsx', index_col = 0) # index_col tells which col to use as index"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "iKc-gzMZ8ed2",
        "outputId": "0af719f9-50b6-41c8-f47f-3bc456e8af2e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   B  C\n",
              "A      \n",
              "0  2  3\n",
              "1  4  5\n",
              "2  4  4\n",
              "3  3  4\n",
              "1  2  3"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-91b045ee-2982-40ef-9858-abb16ad87101\">\n",
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              "      <div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>B</th>\n",
              "      <th>C</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>A</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-91b045ee-2982-40ef-9858-abb16ad87101')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-91b045ee-2982-40ef-9858-abb16ad87101 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-91b045ee-2982-40ef-9858-abb16ad87101');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ],
      "source": [
        "specdf # Special data to showcase loc"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "MBukidWq8ed2",
        "outputId": "49527c72-09ad-46d0-c65a-d673ae660b21"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   B  C\n",
              "A      \n",
              "1  4  5\n",
              "1  2  3"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b080d455-c731-4640-9f2d-beb971a8d9a1\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>B</th>\n",
              "      <th>C</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>A</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b080d455-c731-4640-9f2d-beb971a8d9a1')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-b080d455-c731-4640-9f2d-beb971a8d9a1 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-b080d455-c731-4640-9f2d-beb971a8d9a1');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ],
      "source": [
        "specdf.loc[1] # As you can see you get all possible matches where index is 1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1fBZrztg8ed2"
      },
      "source": [
        "### Get Multiple Rows using loc"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "9KfJ_dlS8ed2",
        "outputId": "c9383b8b-6b0f-4514-b1f0-6735685517cb"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          DATE   INVCMRMT\n",
              "0   1997-01-01  1301161.0\n",
              "11  1997-12-01  1378022.0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-26ea2a21-12c8-4208-ad70-0d04612345e5\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>DATE</th>\n",
              "      <th>INVCMRMT</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1997-01-01</td>\n",
              "      <td>1301161.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>1997-12-01</td>\n",
              "      <td>1378022.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-26ea2a21-12c8-4208-ad70-0d04612345e5')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-26ea2a21-12c8-4208-ad70-0d04612345e5 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-26ea2a21-12c8-4208-ad70-0d04612345e5');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ],
      "source": [
        "df.loc[[0,11]] # Similar to getting multiple columns"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Cz5j8nBA8ed2"
      },
      "source": [
        "### Using iloc (Index based matching instead of matching key to values in loc)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hv_Tq4r48ed2",
        "outputId": "cd32e614-47c1-48e8-f266-3d304198e99a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DATE        1997-03-01\n",
              "INVCMRMT     1303978.0\n",
              "Name: 2, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ],
      "source": [
        "df.iloc[2]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "FMXE7HnR8ed2",
        "outputId": "aa7fb75a-7f8e-4fb2-c9a9-ce3fec7e4d26"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   B  C\n",
              "A      \n",
              "0  2  3\n",
              "1  4  5\n",
              "2  4  4\n",
              "3  3  4\n",
              "1  2  3"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f6040168-38e0-48ee-b4f9-846b30b9584d\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>B</th>\n",
              "      <th>C</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>A</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f6040168-38e0-48ee-b4f9-846b30b9584d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
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              "          document.querySelector('#df-f6040168-38e0-48ee-b4f9-846b30b9584d button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f6040168-38e0-48ee-b4f9-846b30b9584d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ],
      "source": [
        "specdf"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CwQYkjkO8ed3",
        "outputId": "ad23c379-3ce9-4d0d-a56c-8dff72c9b0c7"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "B    2\n",
              "C    3\n",
              "Name: 1, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ],
      "source": [
        "specdf.iloc[4] #Now you get value at index 4 and not all places where index column value matches 4"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fG8hl8fZ8ed3"
      },
      "source": [
        "### ix is another way however since it is a deprecated practice it won't be covered you can read about it in the docs if you're interested"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qz6lHoNt8ed3"
      },
      "source": [
        "### Subsetting both columns and rows"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
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        "id": "Qc2xW-lR8ed3",
        "outputId": "e8f3f747-1900-4322-b2a9-5226a82da8e3"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Year  Stocks T.Bills T.Bonds\n",
              "0  1928  0.4381  0.0308  0.0084\n",
              "1  1929  -0.083  0.0316   0.042\n",
              "2  1930 -0.2512  0.0455  0.0454\n",
              "3  1931 -0.4384  0.0231 -0.0256\n",
              "4  1932 -0.0864  0.0107  0.0879"
            ],
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              "\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1930</td>\n",
              "      <td>-0.2512</td>\n",
              "      <td>0.0455</td>\n",
              "      <td>0.0454</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1931</td>\n",
              "      <td>-0.4384</td>\n",
              "      <td>0.0231</td>\n",
              "      <td>-0.0256</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1932</td>\n",
              "      <td>-0.0864</td>\n",
              "      <td>0.0107</td>\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ],
      "source": [
        "df2.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BgLss-Fx8ed3"
      },
      "outputs": [],
      "source": [
        "subset = df2.loc[:,['Year', 'Stocks']] # Before comma we add the rows. after comma we add the columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "jg6YUyvh8ed3",
        "outputId": "ccd4cf2d-dbff-489d-9560-05a9e6be78f9"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Year  Stocks\n",
              "0  1928  0.4381\n",
              "1  1929  -0.083\n",
              "2  1930 -0.2512\n",
              "3  1931 -0.4384\n",
              "4  1932 -0.0864"
            ],
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              "\n",
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              "      <td>1928</td>\n",
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              "      <th>1</th>\n",
              "      <td>1929</td>\n",
              "      <td>-0.083</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1930</td>\n",
              "      <td>-0.2512</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1931</td>\n",
              "      <td>-0.4384</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1932</td>\n",
              "      <td>-0.0864</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ffa5f7f2-236b-42e4-9f99-8b5092ae872b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-ffa5f7f2-236b-42e4-9f99-8b5092ae872b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ffa5f7f2-236b-42e4-9f99-8b5092ae872b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ],
      "source": [
        "subset.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9-GKgbto8ed3",
        "outputId": "690015ca-518a-4bb5-9ee0-e62d19ec283a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0     False\n",
              "1     False\n",
              "2      True\n",
              "3     False\n",
              "4     False\n",
              "      ...  \n",
              "79    False\n",
              "80    False\n",
              "81    False\n",
              "82    False\n",
              "83    False\n",
              "Name: Year, Length: 84, dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ],
      "source": [
        "df2['Year']==1930"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "SMAAYxNb8ed4"
      },
      "outputs": [],
      "source": [
        "advsubset = df2.loc[df2['Year']==1930, ['T.Bills', 'T.Bonds']] # Using booleans to check"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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              "  T.Bills T.Bonds\n",
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              "0     False\n",
              "1     False\n",
              "2      True\n",
              "3     False\n",
              "4     False\n",
              "      ...  \n",
              "79    False\n",
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              "Name: Year, Length: 84, dtype: bool"
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        "df2['Year']==1930"
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              "   Year  Stocks T.Bills T.Bonds\n",
              "2  1930 -0.2512  0.0455  0.0454"
            ],
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      "source": [
        "df2[df2['Year']==1930] # Returns those rows where there is a True"
      ]
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yETiRxw28ed4"
      },
      "source": [
        "### Using Multiple Boolean Conditions"
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Year Stocks T.Bills T.Bonds\n",
              "1  1929 -0.083  0.0316   0.042"
            ],
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              "                                                     [key], {});\n",
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              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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          "metadata": {},
          "execution_count": 43
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      "source": [
        "df2[(df2['Year']==1929) & (df2['T.Bills'] == 0.0316)]"
      ]
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Year  Stocks T.Bills T.Bonds\n",
              "1  1929  -0.083  0.0316   0.042\n",
              "2  1930 -0.2512  0.0455  0.0454"
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              "      <th>1</th>\n",
              "      <td>1929</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-544a58f2-bfbe-48ac-90b0-bd2bb12e26b1')\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-544a58f2-bfbe-48ac-90b0-bd2bb12e26b1 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-544a58f2-bfbe-48ac-90b0-bd2bb12e26b1');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ],
      "source": [
        "df2[(df2['Year']==1930) | (df2['T.Bills'] == 0.0316)]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KTDyZvJf8ed5"
      },
      "source": [
        "### We use '&' and '|' over traditional python operators like 'and' and 'or' is because it does bitwise comparisons"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZjGRgtfb8ed5"
      },
      "source": [
        "### Wide and Long Data\n",
        "![Diff Types of Data](cooldata/longwide.png)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7clODKlN8ed5"
      },
      "outputs": [],
      "source": [
        "surveydf = pd.read_csv('EventData/cooldata/surveydata.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "r9flQ1Kd8ed5",
        "outputId": "e6e6e2d5-0d96-4f00-c469-18e9e08c45c9"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             religion  <$10k  $10-20k  $20-30k  $30-40k  $40-50k  $50-75k  \\\n",
              "0            Agnostic     27       34       60       81       76      137   \n",
              "1             Atheist     12       27       37       52       35       70   \n",
              "2            Buddhist     27       21       30       34       33       58   \n",
              "3            Catholic    418      617      732      670      638     1116   \n",
              "4  Don’t know/refused     15       14       15       11       10       35   \n",
              "\n",
              "   $75-100k  $100-150k  >150k  Don't know/refused  \n",
              "0       122        109     84                  96  \n",
              "1        73         59     74                  76  \n",
              "2        62         39     53                  54  \n",
              "3       949        792    633                1489  \n",
              "4        21         17     18                 116  "
            ],
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              "      <th></th>\n",
              "      <th>religion</th>\n",
              "      <th>&lt;$10k</th>\n",
              "      <th>$10-20k</th>\n",
              "      <th>$20-30k</th>\n",
              "      <th>$30-40k</th>\n",
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              "      <th>&gt;150k</th>\n",
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              "      <th>0</th>\n",
              "      <td>Agnostic</td>\n",
              "      <td>27</td>\n",
              "      <td>34</td>\n",
              "      <td>60</td>\n",
              "      <td>81</td>\n",
              "      <td>76</td>\n",
              "      <td>137</td>\n",
              "      <td>122</td>\n",
              "      <td>109</td>\n",
              "      <td>84</td>\n",
              "      <td>96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Atheist</td>\n",
              "      <td>12</td>\n",
              "      <td>27</td>\n",
              "      <td>37</td>\n",
              "      <td>52</td>\n",
              "      <td>35</td>\n",
              "      <td>70</td>\n",
              "      <td>73</td>\n",
              "      <td>59</td>\n",
              "      <td>74</td>\n",
              "      <td>76</td>\n",
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              "    <tr>\n",
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              "      <td>Buddhist</td>\n",
              "      <td>27</td>\n",
              "      <td>21</td>\n",
              "      <td>30</td>\n",
              "      <td>34</td>\n",
              "      <td>33</td>\n",
              "      <td>58</td>\n",
              "      <td>62</td>\n",
              "      <td>39</td>\n",
              "      <td>53</td>\n",
              "      <td>54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Catholic</td>\n",
              "      <td>418</td>\n",
              "      <td>617</td>\n",
              "      <td>732</td>\n",
              "      <td>670</td>\n",
              "      <td>638</td>\n",
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              "      <td>949</td>\n",
              "      <td>792</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Don’t know/refused</td>\n",
              "      <td>15</td>\n",
              "      <td>14</td>\n",
              "      <td>15</td>\n",
              "      <td>11</td>\n",
              "      <td>10</td>\n",
              "      <td>35</td>\n",
              "      <td>21</td>\n",
              "      <td>17</td>\n",
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              "\n",
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              "\n",
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              "\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-23522373-106f-4659-b129-7ee07cf18561');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ],
      "source": [
        "surveydf.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "f0aaoWtx8ed5"
      },
      "outputs": [],
      "source": [
        "longdf = pd.melt(surveydf, id_vars='religion') "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l--cZsJX8ed5"
      },
      "source": [
        "### id_vars tells us which columns to leave as it is, there is another parameter called value_vars anything not in id_vars goes to value_vars"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "Oa7_Vcko8ed5",
        "outputId": "717773b2-e0f8-464d-a958-4fc09cf6777d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  religion            variable  value\n",
              "0                 Agnostic               <$10k     27\n",
              "1                  Atheist               <$10k     12\n",
              "2                 Buddhist               <$10k     27\n",
              "3                 Catholic               <$10k    418\n",
              "4       Don’t know/refused               <$10k     15\n",
              "..                     ...                 ...    ...\n",
              "175               Orthodox  Don't know/refused     73\n",
              "176        Other Christian  Don't know/refused     18\n",
              "177           Other Faiths  Don't know/refused     71\n",
              "178  Other World Religions  Don't know/refused      8\n",
              "179           Unaffiliated  Don't know/refused    597\n",
              "\n",
              "[180 rows x 3 columns]"
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              "      <td>18</td>\n",
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              "    <tr>\n",
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              "      <td>Don't know/refused</td>\n",
              "      <td>71</td>\n",
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          "metadata": {},
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      "source": [
        "longdf"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "8bggJ7Go8ed5"
      },
      "outputs": [],
      "source": [
        "longdfbetter = pd.melt(surveydf, id_vars='religion', var_name='income', value_name='count') "
      ]
    },
    {
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              "                  religion              income  count\n",
              "0                 Agnostic               <$10k     27\n",
              "1                  Atheist               <$10k     12\n",
              "2                 Buddhist               <$10k     27\n",
              "3                 Catholic               <$10k    418\n",
              "4       Don’t know/refused               <$10k     15\n",
              "..                     ...                 ...    ...\n",
              "175               Orthodox  Don't know/refused     73\n",
              "176        Other Christian  Don't know/refused     18\n",
              "177           Other Faiths  Don't know/refused     71\n",
              "178  Other World Religions  Don't know/refused      8\n",
              "179           Unaffiliated  Don't know/refused    597\n",
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          "metadata": {},
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      "source": [
        "longdfbetter # Better Column Names"
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    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "OJFjI94U8ed6"
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      "source": [
        "billdf = pd.read_csv('EventData/cooldata/billboard.csv')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "id": "0RDWIZiu8ed6",
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            "text/plain": [
              "     year            artist                    track  time date.entered  wk1  \\\n",
              "0    2000             2 Pac  Baby Don't Cry (Keep...  4:22   2000-02-26   87   \n",
              "1    2000           2Ge+her  The Hardest Part Of ...  3:15   2000-09-02   91   \n",
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              "313  2000  Yearwood, Trisha          Real Live Woman  3:55   2000-04-01   85   \n",
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              "315  2000     Zombie Nation            Kernkraft 400  3:30   2000-09-02   99   \n",
              "316  2000   matchbox twenty                     Bent  4:12   2000-04-29   60   \n",
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              "\n",
              "     wk74  wk75  wk76  \n",
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              "      <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>312</th>\n",
              "      <td>2000</td>\n",
              "      <td>Yankee Grey</td>\n",
              "      <td>Another Nine Minutes</td>\n",
              "      <td>3:10</td>\n",
              "      <td>2000-04-29</td>\n",
              "      <td>86</td>\n",
              "      <td>83.0</td>\n",
              "      <td>77.0</td>\n",
              "      <td>74.0</td>\n",
              "      <td>83.0</td>\n",
              "      <td>...</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>313</th>\n",
              "      <td>2000</td>\n",
              "      <td>Yearwood, Trisha</td>\n",
              "      <td>Real Live Woman</td>\n",
              "      <td>3:55</td>\n",
              "      <td>2000-04-01</td>\n",
              "      <td>85</td>\n",
              "      <td>83.0</td>\n",
              "      <td>83.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>81.0</td>\n",
              "      <td>...</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>314</th>\n",
              "      <td>2000</td>\n",
              "      <td>Ying Yang Twins</td>\n",
              "      <td>Whistle While You Tw...</td>\n",
              "      <td>4:19</td>\n",
              "      <td>2000-03-18</td>\n",
              "      <td>95</td>\n",
              "      <td>94.0</td>\n",
              "      <td>91.0</td>\n",
              "      <td>85.0</td>\n",
              "      <td>84.0</td>\n",
              "      <td>...</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>315</th>\n",
              "      <td>2000</td>\n",
              "      <td>Zombie Nation</td>\n",
              "      <td>Kernkraft 400</td>\n",
              "      <td>3:30</td>\n",
              "      <td>2000-09-02</td>\n",
              "      <td>99</td>\n",
              "      <td>99.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</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>316</th>\n",
              "      <td>2000</td>\n",
              "      <td>matchbox twenty</td>\n",
              "      <td>Bent</td>\n",
              "      <td>4:12</td>\n",
              "      <td>2000-04-29</td>\n",
              "      <td>60</td>\n",
              "      <td>37.0</td>\n",
              "      <td>29.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>...</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",
              "  </tbody>\n",
              "</table>\n",
              "<p>317 rows × 81 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bc5ce9e9-8530-4653-af5f-5ee2bad5cb58')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-bc5ce9e9-8530-4653-af5f-5ee2bad5cb58 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-bc5ce9e9-8530-4653-af5f-5ee2bad5cb58');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ],
      "source": [
        "billdf #Too Many Columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "UCpONicB8ed6"
      },
      "outputs": [],
      "source": [
        "billdfbetter = pd.melt(billdf, id_vars=['year', 'artist', 'track', 'time', 'date.entered'], var_name = 'week', value_name = 'rating')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "0eTkiPBw8ed6",
        "outputId": "9ef5b86e-1082-4d62-ad4b-c59aaff7f00f"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       year            artist                    track  time date.entered  \\\n",
              "0      2000             2 Pac  Baby Don't Cry (Keep...  4:22   2000-02-26   \n",
              "1      2000           2Ge+her  The Hardest Part Of ...  3:15   2000-09-02   \n",
              "2      2000      3 Doors Down               Kryptonite  3:53   2000-04-08   \n",
              "3      2000      3 Doors Down                    Loser  4:24   2000-10-21   \n",
              "4      2000          504 Boyz            Wobble Wobble  3:35   2000-04-15   \n",
              "...     ...               ...                      ...   ...          ...   \n",
              "24087  2000       Yankee Grey     Another Nine Minutes  3:10   2000-04-29   \n",
              "24088  2000  Yearwood, Trisha          Real Live Woman  3:55   2000-04-01   \n",
              "24089  2000   Ying Yang Twins  Whistle While You Tw...  4:19   2000-03-18   \n",
              "24090  2000     Zombie Nation            Kernkraft 400  3:30   2000-09-02   \n",
              "24091  2000   matchbox twenty                     Bent  4:12   2000-04-29   \n",
              "\n",
              "       week  rating  \n",
              "0       wk1    87.0  \n",
              "1       wk1    91.0  \n",
              "2       wk1    81.0  \n",
              "3       wk1    76.0  \n",
              "4       wk1    57.0  \n",
              "...     ...     ...  \n",
              "24087  wk76     NaN  \n",
              "24088  wk76     NaN  \n",
              "24089  wk76     NaN  \n",
              "24090  wk76     NaN  \n",
              "24091  wk76     NaN  \n",
              "\n",
              "[24092 rows x 7 columns]"
            ],
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              "      <th></th>\n",
              "      <th>year</th>\n",
              "      <th>artist</th>\n",
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              "      <th>date.entered</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2000</td>\n",
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              "      <td>Baby Don't Cry (Keep...</td>\n",
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              "      <td>2000-02-26</td>\n",
              "      <td>wk1</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2000</td>\n",
              "      <td>2Ge+her</td>\n",
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              "      <td>3:15</td>\n",
              "      <td>2000-09-02</td>\n",
              "      <td>wk1</td>\n",
              "      <td>91.0</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2000</td>\n",
              "      <td>3 Doors Down</td>\n",
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              "      <td>3:53</td>\n",
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              "      <td>wk1</td>\n",
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              "      <th>3</th>\n",
              "      <td>2000</td>\n",
              "      <td>3 Doors Down</td>\n",
              "      <td>Loser</td>\n",
              "      <td>4:24</td>\n",
              "      <td>2000-10-21</td>\n",
              "      <td>wk1</td>\n",
              "      <td>76.0</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2000</td>\n",
              "      <td>504 Boyz</td>\n",
              "      <td>Wobble Wobble</td>\n",
              "      <td>3:35</td>\n",
              "      <td>2000-04-15</td>\n",
              "      <td>wk1</td>\n",
              "      <td>57.0</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",
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              "      <th>24087</th>\n",
              "      <td>2000</td>\n",
              "      <td>Yankee Grey</td>\n",
              "      <td>Another Nine Minutes</td>\n",
              "      <td>3:10</td>\n",
              "      <td>2000-04-29</td>\n",
              "      <td>wk76</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24088</th>\n",
              "      <td>2000</td>\n",
              "      <td>Yearwood, Trisha</td>\n",
              "      <td>Real Live Woman</td>\n",
              "      <td>3:55</td>\n",
              "      <td>2000-04-01</td>\n",
              "      <td>wk76</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24089</th>\n",
              "      <td>2000</td>\n",
              "      <td>Ying Yang Twins</td>\n",
              "      <td>Whistle While You Tw...</td>\n",
              "      <td>4:19</td>\n",
              "      <td>2000-03-18</td>\n",
              "      <td>wk76</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24090</th>\n",
              "      <td>2000</td>\n",
              "      <td>Zombie Nation</td>\n",
              "      <td>Kernkraft 400</td>\n",
              "      <td>3:30</td>\n",
              "      <td>2000-09-02</td>\n",
              "      <td>wk76</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24091</th>\n",
              "      <td>2000</td>\n",
              "      <td>matchbox twenty</td>\n",
              "      <td>Bent</td>\n",
              "      <td>4:12</td>\n",
              "      <td>2000-04-29</td>\n",
              "      <td>wk76</td>\n",
              "      <td>NaN</td>\n",
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              "  </tbody>\n",
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              "<p>24092 rows × 7 columns</p>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5f10ec28-4080-4b4d-b226-469daf19d1c7')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-5f10ec28-4080-4b4d-b226-469daf19d1c7 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5f10ec28-4080-4b4d-b226-469daf19d1c7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ],
      "source": [
        "billdfbetter"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c8S3Ob5X8ed6"
      },
      "source": [
        "### .apply()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "id": "VIPyyUsb8ed6",
        "outputId": "ff0f3dff-1cd3-49b7-8599-6bdf0e3791ac"
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      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           DATE   INVCMRMT\n",
              "0    1997-01-01  1301161.0\n",
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              "3    1997-04-01  1319740.0\n",
              "4    1997-05-01  1327294.0\n",
              "..          ...        ...\n",
              "278  2020-03-01  2192351.0\n",
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              "280  2020-05-01  2144828.0\n",
              "281  2020-06-01  2125810.0\n",
              "282  2020-07-01  2121991.0\n",
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              "      <td>1997-04-01</td>\n",
              "      <td>1319740.0</td>\n",
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              "      <th>4</th>\n",
              "      <td>1997-05-01</td>\n",
              "      <td>1327294.0</td>\n",
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              "      <th>...</th>\n",
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              "      <th>279</th>\n",
              "      <td>2020-04-01</td>\n",
              "      <td>2178236.0</td>\n",
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              "      <th>280</th>\n",
              "      <td>2020-05-01</td>\n",
              "      <td>2144828.0</td>\n",
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              "    <tr>\n",
              "      <th>281</th>\n",
              "      <td>2020-06-01</td>\n",
              "      <td>2125810.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>282</th>\n",
              "      <td>2020-07-01</td>\n",
              "      <td>2121991.0</td>\n",
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              "  </tbody>\n",
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              "<p>283 rows × 2 columns</p>\n",
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              "\n",
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              "\n",
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              "          const element = document.querySelector('#df-b2cf3e47-0184-4544-a967-f9555f5bd1c4');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
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          "metadata": {},
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        }
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      "source": [
        "df"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "d1JZi_-N8ed6"
      },
      "outputs": [],
      "source": [
        "def do_computation(x):\n",
        "    x = int(x)*0.1\n",
        "    return x"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GUr5MRF18ed7"
      },
      "outputs": [],
      "source": [
        "df['INVCMRMT'] = df['INVCMRMT'].apply(do_computation)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "NyoUU0Fr8ed7",
        "outputId": "802d26bf-b55a-49c6-c920-3ca659810695"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           DATE  INVCMRMT\n",
              "0    1997-01-01  130116.1\n",
              "1    1997-02-01  130708.0\n",
              "2    1997-03-01  130397.8\n",
              "3    1997-04-01  131974.0\n",
              "4    1997-05-01  132729.4\n",
              "..          ...       ...\n",
              "278  2020-03-01  219235.1\n",
              "279  2020-04-01  217823.6\n",
              "280  2020-05-01  214482.8\n",
              "281  2020-06-01  212581.0\n",
              "282  2020-07-01  212199.1\n",
              "\n",
              "[283 rows x 2 columns]"
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              "      <td>212581.0</td>\n",
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              "      <th>282</th>\n",
              "      <td>2020-07-01</td>\n",
              "      <td>212199.1</td>\n",
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              "<p>283 rows × 2 columns</p>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-826f7669-79e9-4d03-97b0-7c983cdb2bd2 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-826f7669-79e9-4d03-97b0-7c983cdb2bd2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ],
      "source": [
        "df"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MAmz8VEI8ed7"
      },
      "source": [
        "### Writing to CSV Files\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ED_54umD8ed7"
      },
      "outputs": [],
      "source": [
        "billdfbetter.to_csv(r'EventData/cooldata/written.csv')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EQsm8ixB8ed7"
      },
      "source": [
        "### Some functions which will help you in the challenges. You can use other alternatives too, these are just to give you an idea (descriptions have been copied from their documentation alongside examples)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gifSL9CQ8ed7"
      },
      "outputs": [],
      "source": [
        "import numpy as np # imported to be able to use np.NaN"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IwAOCxT98ed7"
      },
      "source": [
        "### isna() \n",
        "Detect missing values.\n",
        "Return a boolean same-sized object indicating if the values are NA. NA values, such as None or numpy.NaN, gets mapped to True values. Everything else gets mapped to False values. Characters such as empty strings '' or numpy.inf are not considered NA values (unless you set pandas.options.mode.use_inf_as_na = True).\n",
        "\n",
        "https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.isna.html"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_tSNYejO8ed7"
      },
      "outputs": [],
      "source": [
        "ser = pd.Series([5, 6, np.NaN])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1maDF90v8ed8",
        "outputId": "24d15be2-f70e-4271-ed2f-5d7f73cc0dd5"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    5.0\n",
              "1    6.0\n",
              "2    NaN\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ],
      "source": [
        "ser"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "klaVvDw_8ed8",
        "outputId": "e807042c-30c7-4e33-eb3b-df7e9de6812d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    False\n",
              "1    False\n",
              "2     True\n",
              "dtype: bool"
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ],
      "source": [
        "ser.isna()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_hXUuVnY8ed8"
      },
      "source": [
        "### .unique\n",
        "Hash table-based unique. Uniques are returned in order of appearance. This does NOT sort.\n",
        "Significantly faster than numpy.unique. Includes NA values.\n",
        "\n",
        "https://pandas.pydata.org/docs/reference/api/pandas.unique.html"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kbqIEbtH8ed8",
        "outputId": "f991a480-2457-4f86-bd7c-08462c0a1a8e"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([2, 1, 3])"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ],
      "source": [
        "pd.unique(pd.Series([2, 1, 3, 3]))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Wjo0VNRr8ed8"
      },
      "source": [
        "### value_counts()\n",
        "Return a Series containing counts of unique values.\n",
        "The resulting object will be in descending order so that the first element is the most frequently-occurring element. Excludes NA values by default.\n",
        "\n",
        "https://pandas.pydata.org/docs/reference/api/pandas.Series.value_counts.html"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vKDPmYdS8ed8",
        "outputId": "742683f8-9df0-4042-9d3b-dca94ac60c7c"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    3.0\n",
              "1    1.0\n",
              "2    2.0\n",
              "3    3.0\n",
              "4    4.0\n",
              "5    NaN\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ],
      "source": [
        "s = pd.Series([3, 1, 2, 3, 4, np.nan])\n",
        "s"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PQa6wiPD8ed8",
        "outputId": "198682ef-274e-4476-9c8c-3afc42cc1094"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3.0    2\n",
              "1.0    1\n",
              "2.0    1\n",
              "4.0    1\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ],
      "source": [
        "s.value_counts()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ERpXvN-z8ed8"
      },
      "source": [
        "### to_numeric\n",
        "Convert argument to a numeric type.\n",
        "The default return dtype is float64 or int64 depending on the data supplied. Use the downcast parameter to obtain other dtypes.\n",
        "\n",
        "https://pandas.pydata.org/docs/reference/api/pandas.to_numeric.html"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "DxqMqXOh8ed9"
      },
      "outputs": [],
      "source": [
        "s = pd.Series(['1.0', '2', -3])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lkF1e1JY8ed9",
        "outputId": "af4c9c00-f225-4bde-a168-160550753281"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    1.0\n",
              "1    2.0\n",
              "2   -3.0\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ],
      "source": [
        "pd.to_numeric(s)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SHMUOp2c8ed9"
      },
      "source": [
        "### any\n",
        "Return whether any element is True, potentially over an axis.\n",
        "Returns False unless there is at least one element within a series or along a Dataframe axis that is True or equivalent (e.g. non-zero or non-empty).\n",
        "\n",
        "Important Parameter - \n",
        "\n",
        "axis {0 or ‘index’, 1 or ‘columns’, None}, default is set to 0\n",
        "Indicate which axis or axes should be reduced.\n",
        "\n",
        "- 0 / ‘index’ : reduce the index, return a Series whose index is the original column labels.\n",
        "\n",
        "- 1 / ‘columns’ : reduce the columns, return a Series whose index is the original index.\n",
        "\n",
        "- None : reduce all axes, return a scalar.\n",
        "\n",
        "https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.any.html"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fpS5_gY18ed9",
        "outputId": "1af57c60-b173-46d8-9e91-bfa1fef0dc1a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 69
        }
      ],
      "source": [
        "pd.Series([False, False]).any()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IQNIcbVT8ed9",
        "outputId": "7b569f37-3cf2-4dd1-c587-6eb7c55cb67f"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ],
      "source": [
        "pd.Series([True, False]).any()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bFTYumlB8ed-",
        "outputId": "c5dda9eb-70d0-4ec9-91c4-baeaec68e810"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-71-88c2952c0302>:1: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.\n",
            "  pd.Series([]).any()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ],
      "source": [
        "pd.Series([]).any()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GO8Ga29H8ed-"
      },
      "source": [
        "### For more pratice refer to this awesome github repository\n",
        "https://github.com/guipsamora/pandas_exercises\n",
        "\n",
        "### For more insights explore the docs here \n",
        "https://pandas.pydata.org/docs/index.html\n",
        "\n",
        "### Here's a 10 minute guide to Pandas\n",
        "https://pandas.pydata.org/docs/user_guide/10min.html#min\n",
        "\n",
        "### Finally a cheat sheet for you\n",
        "https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf"
      ]
    }
  ],
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