Day_4_Assignment.ipynb

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  "metadata": {
    "colab": {
      "name": "Day-4 Assignment",
      "provenance": [],
      "authorship_tag": "ABX9TyMbXfsQJWosZo1QOEQmhOsX",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Akshatpattiwar512/LetsUpgrade_Data-Science-Essentials/blob/main/Day_4_Assignment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B99IM2dVpGkS",
        "outputId": "8960d2cd-a740-4167-fa9e-4d182602137d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "#Q1\n",
        "import pandas as pd \n",
        "print(pd.__version__)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1.1.4\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PZSH4O1upWIR",
        "outputId": "89e09822-7cd9-4400-a2d5-3b973890e38f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "#Q2\n",
        "import pandas as pd \n",
        "import numpy as np\n",
        "data = np.array(['a', 'b', 'c', 'd', 'e'])\n",
        "s = pd.Series(data) \n",
        "print(s)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0    a\n",
            "1    b\n",
            "2    c\n",
            "3    d\n",
            "4    e\n",
            "dtype: object\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yFZVYos0r4_m",
        "outputId": "6a9f6f3c-3836-45fd-80d7-1a2847a0dca9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        }
      },
      "source": [
        "#Q3\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "# using numpy array value\n",
        "data = np.array(['AZ', 'BY', 'CX', 'DW', 'EV']) \n",
        "  \n",
        "# creating series from array with user index value\n",
        "series = pd.Series(data, index = [1, 2, 3, 4, 5]) \n",
        "\n",
        "# convert series to dataframe \n",
        "df = series.to_frame().reset_index() \n",
        "  \n",
        "# show the dataframe \n",
        "df"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\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>index</th>\n",
              "      <th>0</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>AZ</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>BY</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>CX</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>DW</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>EV</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   index   0\n",
              "0      1  AZ\n",
              "1      2  BY\n",
              "2      3  CX\n",
              "3      4  DW\n",
              "4      5  EV"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FPSTUAtbtkhX",
        "outputId": "03145b1d-c044-428b-dcce-35b46f26a888",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "#Q4\n",
        "import seaborn as sbn\n",
        "\n",
        "mpg=sbn.load_dataset('mpg')\n",
        "\n",
        "print(mpg)"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "      mpg  cylinders  ...  origin                       name\n",
            "0    18.0          8  ...     usa  chevrolet chevelle malibu\n",
            "1    15.0          8  ...     usa          buick skylark 320\n",
            "2    18.0          8  ...     usa         plymouth satellite\n",
            "3    16.0          8  ...     usa              amc rebel sst\n",
            "4    17.0          8  ...     usa                ford torino\n",
            "..    ...        ...  ...     ...                        ...\n",
            "393  27.0          4  ...     usa            ford mustang gl\n",
            "394  44.0          4  ...  europe                  vw pickup\n",
            "395  32.0          4  ...     usa              dodge rampage\n",
            "396  28.0          4  ...     usa                ford ranger\n",
            "397  31.0          4  ...     usa                 chevy s-10\n",
            "\n",
            "[398 rows x 9 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vgGq5qIWtkaH",
        "outputId": "5086a700-3424-4cd7-8c71-13c3c3826015",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "#Q5\n",
        "import seaborn as sbn\n",
        "import pandas as pd\n",
        "mpg=sbn.load_dataset('mpg')\n",
        "df = pd.DataFrame(mpg)\n",
        "df.origin.unique()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['usa', 'japan', 'europe'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "51m0_H2Bt4SZ",
        "outputId": "cc76a460-9398-45d8-b3bd-7c797296199c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        }
      },
      "source": [
        "#Q6\n",
        "import seaborn as sbn\n",
        "import pandas as pd\n",
        "mpg=sbn.load_dataset('mpg')\n",
        "df = pd.DataFrame(mpg)\n",
        "df[df['origin'].str.contains(\"usa\")]"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>mpg</th>\n",
              "      <th>cylinders</th>\n",
              "      <th>displacement</th>\n",
              "      <th>horsepower</th>\n",
              "      <th>weight</th>\n",
              "      <th>acceleration</th>\n",
              "      <th>model_year</th>\n",
              "      <th>origin</th>\n",
              "      <th>name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>18.0</td>\n",
              "      <td>8</td>\n",
              "      <td>307.0</td>\n",
              "      <td>130.0</td>\n",
              "      <td>3504</td>\n",
              "      <td>12.0</td>\n",
              "      <td>70</td>\n",
              "      <td>usa</td>\n",
              "      <td>chevrolet chevelle malibu</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>15.0</td>\n",
              "      <td>8</td>\n",
              "      <td>350.0</td>\n",
              "      <td>165.0</td>\n",
              "      <td>3693</td>\n",
              "      <td>11.5</td>\n",
              "      <td>70</td>\n",
              "      <td>usa</td>\n",
              "      <td>buick skylark 320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>18.0</td>\n",
              "      <td>8</td>\n",
              "      <td>318.0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>3436</td>\n",
              "      <td>11.0</td>\n",
              "      <td>70</td>\n",
              "      <td>usa</td>\n",
              "      <td>plymouth satellite</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>16.0</td>\n",
              "      <td>8</td>\n",
              "      <td>304.0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>3433</td>\n",
              "      <td>12.0</td>\n",
              "      <td>70</td>\n",
              "      <td>usa</td>\n",
              "      <td>amc rebel sst</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>17.0</td>\n",
              "      <td>8</td>\n",
              "      <td>302.0</td>\n",
              "      <td>140.0</td>\n",
              "      <td>3449</td>\n",
              "      <td>10.5</td>\n",
              "      <td>70</td>\n",
              "      <td>usa</td>\n",
              "      <td>ford torino</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>392</th>\n",
              "      <td>27.0</td>\n",
              "      <td>4</td>\n",
              "      <td>151.0</td>\n",
              "      <td>90.0</td>\n",
              "      <td>2950</td>\n",
              "      <td>17.3</td>\n",
              "      <td>82</td>\n",
              "      <td>usa</td>\n",
              "      <td>chevrolet camaro</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>393</th>\n",
              "      <td>27.0</td>\n",
              "      <td>4</td>\n",
              "      <td>140.0</td>\n",
              "      <td>86.0</td>\n",
              "      <td>2790</td>\n",
              "      <td>15.6</td>\n",
              "      <td>82</td>\n",
              "      <td>usa</td>\n",
              "      <td>ford mustang gl</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>395</th>\n",
              "      <td>32.0</td>\n",
              "      <td>4</td>\n",
              "      <td>135.0</td>\n",
              "      <td>84.0</td>\n",
              "      <td>2295</td>\n",
              "      <td>11.6</td>\n",
              "      <td>82</td>\n",
              "      <td>usa</td>\n",
              "      <td>dodge rampage</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>396</th>\n",
              "      <td>28.0</td>\n",
              "      <td>4</td>\n",
              "      <td>120.0</td>\n",
              "      <td>79.0</td>\n",
              "      <td>2625</td>\n",
              "      <td>18.6</td>\n",
              "      <td>82</td>\n",
              "      <td>usa</td>\n",
              "      <td>ford ranger</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>397</th>\n",
              "      <td>31.0</td>\n",
              "      <td>4</td>\n",
              "      <td>119.0</td>\n",
              "      <td>82.0</td>\n",
              "      <td>2720</td>\n",
              "      <td>19.4</td>\n",
              "      <td>82</td>\n",
              "      <td>usa</td>\n",
              "      <td>chevy s-10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>249 rows × 9 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      mpg  cylinders  ...  origin                       name\n",
              "0    18.0          8  ...     usa  chevrolet chevelle malibu\n",
              "1    15.0          8  ...     usa          buick skylark 320\n",
              "2    18.0          8  ...     usa         plymouth satellite\n",
              "3    16.0          8  ...     usa              amc rebel sst\n",
              "4    17.0          8  ...     usa                ford torino\n",
              "..    ...        ...  ...     ...                        ...\n",
              "392  27.0          4  ...     usa           chevrolet camaro\n",
              "393  27.0          4  ...     usa            ford mustang gl\n",
              "395  32.0          4  ...     usa              dodge rampage\n",
              "396  28.0          4  ...     usa                ford ranger\n",
              "397  31.0          4  ...     usa                 chevy s-10\n",
              "\n",
              "[249 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    }
  ]
}