pandas_ödev3.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "l3QjiJPoK7HN"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#mpg.csv dosyasını okuyun ve df değişkenine atayın.\n",
        "df = pd.read_csv('mpg.csv')\n",
        "df.head()\n",
        "\n",
        "#1 df'in içindeki sütunların birbirleriyle olan korelasyonlarına(ilişkilerine) bakın.\n",
        "df.corr()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 269
        },
        "id": "bK0W48eYLD2g",
        "outputId": "b6079675-afe4-49f6-a144-24e5c4db5db1"
      },
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   mpg  cylinders  displacement    weight  acceleration  \\\n",
              "mpg           1.000000  -0.775396     -0.804203 -0.831741      0.420289   \n",
              "cylinders    -0.775396   1.000000      0.950721  0.896017     -0.505419   \n",
              "displacement -0.804203   0.950721      1.000000  0.932824     -0.543684   \n",
              "weight       -0.831741   0.896017      0.932824  1.000000     -0.417457   \n",
              "acceleration  0.420289  -0.505419     -0.543684 -0.417457      1.000000   \n",
              "model_year    0.579267  -0.348746     -0.370164 -0.306564      0.288137   \n",
              "origin        0.563450  -0.562543     -0.609409 -0.581024      0.205873   \n",
              "\n",
              "              model_year    origin  \n",
              "mpg             0.579267  0.563450  \n",
              "cylinders      -0.348746 -0.562543  \n",
              "displacement   -0.370164 -0.609409  \n",
              "weight         -0.306564 -0.581024  \n",
              "acceleration    0.288137  0.205873  \n",
              "model_year      1.000000  0.180662  \n",
              "origin          0.180662  1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b6eb7e8b-5775-4f11-89cf-e75c41c717a3\">\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>mpg</th>\n",
              "      <th>cylinders</th>\n",
              "      <th>displacement</th>\n",
              "      <th>weight</th>\n",
              "      <th>acceleration</th>\n",
              "      <th>model_year</th>\n",
              "      <th>origin</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>mpg</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.775396</td>\n",
              "      <td>-0.804203</td>\n",
              "      <td>-0.831741</td>\n",
              "      <td>0.420289</td>\n",
              "      <td>0.579267</td>\n",
              "      <td>0.563450</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cylinders</th>\n",
              "      <td>-0.775396</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.950721</td>\n",
              "      <td>0.896017</td>\n",
              "      <td>-0.505419</td>\n",
              "      <td>-0.348746</td>\n",
              "      <td>-0.562543</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>displacement</th>\n",
              "      <td>-0.804203</td>\n",
              "      <td>0.950721</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.932824</td>\n",
              "      <td>-0.543684</td>\n",
              "      <td>-0.370164</td>\n",
              "      <td>-0.609409</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>weight</th>\n",
              "      <td>-0.831741</td>\n",
              "      <td>0.896017</td>\n",
              "      <td>0.932824</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.417457</td>\n",
              "      <td>-0.306564</td>\n",
              "      <td>-0.581024</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>acceleration</th>\n",
              "      <td>0.420289</td>\n",
              "      <td>-0.505419</td>\n",
              "      <td>-0.543684</td>\n",
              "      <td>-0.417457</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.288137</td>\n",
              "      <td>0.205873</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>model_year</th>\n",
              "      <td>0.579267</td>\n",
              "      <td>-0.348746</td>\n",
              "      <td>-0.370164</td>\n",
              "      <td>-0.306564</td>\n",
              "      <td>0.288137</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.180662</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>origin</th>\n",
              "      <td>0.563450</td>\n",
              "      <td>-0.562543</td>\n",
              "      <td>-0.609409</td>\n",
              "      <td>-0.581024</td>\n",
              "      <td>0.205873</td>\n",
              "      <td>0.180662</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b6eb7e8b-5775-4f11-89cf-e75c41c717a3')\"\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-b6eb7e8b-5775-4f11-89cf-e75c41c717a3 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-b6eb7e8b-5775-4f11-89cf-e75c41c717a3');\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": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#2 mpg sütunu ile diğer sütunların arasındaki korelasyonları özel olarak inceleyin.(Bunu göstermedik ama df.corr() çağırdıktan sonra aynı normal df'lerde olduğu gibi istediğiniz sütunu çağırabiliyorsunuz.)\n",
        "\n",
        "df.mpg.corr(df.cylinders)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "95v7sHNRNO70",
        "outputId": "2854cf82-83c7-4cd8-f9ea-eb217839b9b5"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-0.7753962854205542"
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#3 cylinders sütununda hangi unique değerler olduğuna liste halinde bakın.\n",
        "\n",
        "df.cylinders.unique()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hzk39xzUPBof",
        "outputId": "a35e761f-0866-4cf8-aaf7-ec5b3bc87c3e"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([8, 4, 6, 3, 5])"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#4 cylinders sütunundaki unique değerlerin her birinden kaçar adet olduğuna bakın.\n",
        "\n",
        "df.cylinders.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4FnmNkMWPMiv",
        "outputId": "967d247b-ce87-4abb-9feb-a020af9a81a6"
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4    204\n",
              "8    103\n",
              "6     84\n",
              "3      4\n",
              "5      3\n",
              "Name: cylinders, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#5  Arabanın modeli 75-80 yılları arasındaki arabaların hepsini getirin.(75 ve 80 dahil)\n",
        "df.head()\n",
        "\n",
        "df[df['model_year'].between(70,80)]\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "YoDdGsvbPtNC",
        "outputId": "6ed45899-d46b-429b-f22a-935994c07d88"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      mpg  cylinders  displacement horsepower  weight  acceleration  \\\n",
              "0    18.0          8         307.0        130    3504          12.0   \n",
              "1    15.0          8         350.0        165    3693          11.5   \n",
              "2    18.0          8         318.0        150    3436          11.0   \n",
              "3    16.0          8         304.0        150    3433          12.0   \n",
              "4    17.0          8         302.0        140    3449          10.5   \n",
              "..    ...        ...           ...        ...     ...           ...   \n",
              "333  32.7          6         168.0        132    2910          11.4   \n",
              "334  23.7          3          70.0        100    2420          12.5   \n",
              "335  35.0          4         122.0         88    2500          15.1   \n",
              "336  23.6          4         140.0          ?    2905          14.3   \n",
              "337  32.4          4         107.0         72    2290          17.0   \n",
              "\n",
              "     model_year  origin                       name  \n",
              "0            70       1  chevrolet chevelle malibu  \n",
              "1            70       1          buick skylark 320  \n",
              "2            70       1         plymouth satellite  \n",
              "3            70       1              amc rebel sst  \n",
              "4            70       1                ford torino  \n",
              "..          ...     ...                        ...  \n",
              "333          80       3              datsun 280-zx  \n",
              "334          80       3              mazda rx-7 gs  \n",
              "335          80       2          triumph tr7 coupe  \n",
              "336          80       1         ford mustang cobra  \n",
              "337          80       3               honda accord  \n",
              "\n",
              "[338 rows x 9 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7bacb1ca-802b-47a2-b279-5f3668b376c6\">\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>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</td>\n",
              "      <td>3504</td>\n",
              "      <td>12.0</td>\n",
              "      <td>70</td>\n",
              "      <td>1</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</td>\n",
              "      <td>3693</td>\n",
              "      <td>11.5</td>\n",
              "      <td>70</td>\n",
              "      <td>1</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</td>\n",
              "      <td>3436</td>\n",
              "      <td>11.0</td>\n",
              "      <td>70</td>\n",
              "      <td>1</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</td>\n",
              "      <td>3433</td>\n",
              "      <td>12.0</td>\n",
              "      <td>70</td>\n",
              "      <td>1</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</td>\n",
              "      <td>3449</td>\n",
              "      <td>10.5</td>\n",
              "      <td>70</td>\n",
              "      <td>1</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>333</th>\n",
              "      <td>32.7</td>\n",
              "      <td>6</td>\n",
              "      <td>168.0</td>\n",
              "      <td>132</td>\n",
              "      <td>2910</td>\n",
              "      <td>11.4</td>\n",
              "      <td>80</td>\n",
              "      <td>3</td>\n",
              "      <td>datsun 280-zx</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>334</th>\n",
              "      <td>23.7</td>\n",
              "      <td>3</td>\n",
              "      <td>70.0</td>\n",
              "      <td>100</td>\n",
              "      <td>2420</td>\n",
              "      <td>12.5</td>\n",
              "      <td>80</td>\n",
              "      <td>3</td>\n",
              "      <td>mazda rx-7 gs</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335</th>\n",
              "      <td>35.0</td>\n",
              "      <td>4</td>\n",
              "      <td>122.0</td>\n",
              "      <td>88</td>\n",
              "      <td>2500</td>\n",
              "      <td>15.1</td>\n",
              "      <td>80</td>\n",
              "      <td>2</td>\n",
              "      <td>triumph tr7 coupe</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>336</th>\n",
              "      <td>23.6</td>\n",
              "      <td>4</td>\n",
              "      <td>140.0</td>\n",
              "      <td>?</td>\n",
              "      <td>2905</td>\n",
              "      <td>14.3</td>\n",
              "      <td>80</td>\n",
              "      <td>1</td>\n",
              "      <td>ford mustang cobra</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>337</th>\n",
              "      <td>32.4</td>\n",
              "      <td>4</td>\n",
              "      <td>107.0</td>\n",
              "      <td>72</td>\n",
              "      <td>2290</td>\n",
              "      <td>17.0</td>\n",
              "      <td>80</td>\n",
              "      <td>3</td>\n",
              "      <td>honda accord</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>338 rows × 9 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7bacb1ca-802b-47a2-b279-5f3668b376c6')\"\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-7bacb1ca-802b-47a2-b279-5f3668b376c6 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-7bacb1ca-802b-47a2-b279-5f3668b376c6');\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": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#6 horsepower'ı 155-180 arasındaki arabaların hepsini getirin.(155 dahil, 180 dahil değil)(Bu sorguyu yapabilmeniz için horsepower sütununu object durumdan float duruma getirmeniz gerekiyor.)\n",
        "df[df['horsepower'] == '?']\n",
        "df['horsepower'].replace('?' , np.nan , inplace = True)\n",
        "df['horsepower'].astype(float)\n",
        "df['horsepower'] = df['horsepower'].dropna().astype(float)\n",
        "df[df['horsepower'].between(155,180, inclusive = 'left')]\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "vDcWvYPDQNyN",
        "outputId": "61324892-56e8-4de4-b7e5-6a9325ac5175"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      mpg  cylinders  displacement  horsepower  weight  acceleration  \\\n",
              "1    15.0          8         350.0       165.0    3693          11.5   \n",
              "10   15.0          8         383.0       170.0    3563          10.0   \n",
              "11   14.0          8         340.0       160.0    3609           8.0   \n",
              "38   14.0          8         350.0       165.0    4209          12.0   \n",
              "39   14.0          8         400.0       175.0    4464          11.5   \n",
              "43   13.0          8         400.0       170.0    4746          12.0   \n",
              "44   13.0          8         400.0       175.0    5140          12.0   \n",
              "62   13.0          8         350.0       165.0    4274          12.0   \n",
              "63   14.0          8         400.0       175.0    4385          12.0   \n",
              "68   13.0          8         350.0       155.0    4502          13.5   \n",
              "69   12.0          8         350.0       160.0    4456          13.5   \n",
              "85   13.0          8         350.0       175.0    4100          13.0   \n",
              "92   13.0          8         351.0       158.0    4363          13.0   \n",
              "96   13.0          8         360.0       175.0    3821          11.0   \n",
              "104  12.0          8         400.0       167.0    4906          12.5   \n",
              "105  13.0          8         360.0       170.0    4654          13.0   \n",
              "156  16.0          8         400.0       170.0    4668          11.5   \n",
              "230  15.5          8         350.0       170.0    4165          11.4   \n",
              "263  17.7          6         231.0       165.0    3445          13.4   \n",
              "289  16.9          8         350.0       155.0    4360          14.9   \n",
              "\n",
              "     model_year  origin                             name  \n",
              "1            70       1                buick skylark 320  \n",
              "10           70       1              dodge challenger se  \n",
              "11           70       1               plymouth 'cuda 340  \n",
              "38           71       1                 chevrolet impala  \n",
              "39           71       1        pontiac catalina brougham  \n",
              "43           71       1         ford country squire (sw)  \n",
              "44           71       1              pontiac safari (sw)  \n",
              "62           72       1                 chevrolet impala  \n",
              "63           72       1                 pontiac catalina  \n",
              "68           72       1             buick lesabre custom  \n",
              "69           72       1       oldsmobile delta 88 royale  \n",
              "85           73       1                buick century 350  \n",
              "92           73       1                         ford ltd  \n",
              "96           73       1          amc ambassador brougham  \n",
              "104          73       1                     ford country  \n",
              "105          73       1           plymouth custom suburb  \n",
              "156          75       1                 pontiac catalina  \n",
              "230          77       1     chevrolet monte carlo landau  \n",
              "263          78       1  buick regal sport coupe (turbo)  \n",
              "289          79       1          buick estate wagon (sw)  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a79366e0-152d-42c8-89a4-22791015179f\">\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>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>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>1</td>\n",
              "      <td>buick skylark 320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>15.0</td>\n",
              "      <td>8</td>\n",
              "      <td>383.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>3563</td>\n",
              "      <td>10.0</td>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>dodge challenger se</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>340.0</td>\n",
              "      <td>160.0</td>\n",
              "      <td>3609</td>\n",
              "      <td>8.0</td>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>plymouth 'cuda 340</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>350.0</td>\n",
              "      <td>165.0</td>\n",
              "      <td>4209</td>\n",
              "      <td>12.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>chevrolet impala</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>400.0</td>\n",
              "      <td>175.0</td>\n",
              "      <td>4464</td>\n",
              "      <td>11.5</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>pontiac catalina brougham</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>13.0</td>\n",
              "      <td>8</td>\n",
              "      <td>400.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>4746</td>\n",
              "      <td>12.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>ford country squire (sw)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>13.0</td>\n",
              "      <td>8</td>\n",
              "      <td>400.0</td>\n",
              "      <td>175.0</td>\n",
              "      <td>5140</td>\n",
              "      <td>12.0</td>\n",
              "      <td>71</td>\n",
              "      <td>1</td>\n",
              "      <td>pontiac safari (sw)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>13.0</td>\n",
              "      <td>8</td>\n",
              "      <td>350.0</td>\n",
              "      <td>165.0</td>\n",
              "      <td>4274</td>\n",
              "      <td>12.0</td>\n",
              "      <td>72</td>\n",
              "      <td>1</td>\n",
              "      <td>chevrolet impala</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>63</th>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>400.0</td>\n",
              "      <td>175.0</td>\n",
              "      <td>4385</td>\n",
              "      <td>12.0</td>\n",
              "      <td>72</td>\n",
              "      <td>1</td>\n",
              "      <td>pontiac catalina</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>68</th>\n",
              "      <td>13.0</td>\n",
              "      <td>8</td>\n",
              "      <td>350.0</td>\n",
              "      <td>155.0</td>\n",
              "      <td>4502</td>\n",
              "      <td>13.5</td>\n",
              "      <td>72</td>\n",
              "      <td>1</td>\n",
              "      <td>buick lesabre custom</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>69</th>\n",
              "      <td>12.0</td>\n",
              "      <td>8</td>\n",
              "      <td>350.0</td>\n",
              "      <td>160.0</td>\n",
              "      <td>4456</td>\n",
              "      <td>13.5</td>\n",
              "      <td>72</td>\n",
              "      <td>1</td>\n",
              "      <td>oldsmobile delta 88 royale</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>85</th>\n",
              "      <td>13.0</td>\n",
              "      <td>8</td>\n",
              "      <td>350.0</td>\n",
              "      <td>175.0</td>\n",
              "      <td>4100</td>\n",
              "      <td>13.0</td>\n",
              "      <td>73</td>\n",
              "      <td>1</td>\n",
              "      <td>buick century 350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>92</th>\n",
              "      <td>13.0</td>\n",
              "      <td>8</td>\n",
              "      <td>351.0</td>\n",
              "      <td>158.0</td>\n",
              "      <td>4363</td>\n",
              "      <td>13.0</td>\n",
              "      <td>73</td>\n",
              "      <td>1</td>\n",
              "      <td>ford ltd</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>13.0</td>\n",
              "      <td>8</td>\n",
              "      <td>360.0</td>\n",
              "      <td>175.0</td>\n",
              "      <td>3821</td>\n",
              "      <td>11.0</td>\n",
              "      <td>73</td>\n",
              "      <td>1</td>\n",
              "      <td>amc ambassador brougham</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>104</th>\n",
              "      <td>12.0</td>\n",
              "      <td>8</td>\n",
              "      <td>400.0</td>\n",
              "      <td>167.0</td>\n",
              "      <td>4906</td>\n",
              "      <td>12.5</td>\n",
              "      <td>73</td>\n",
              "      <td>1</td>\n",
              "      <td>ford country</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>105</th>\n",
              "      <td>13.0</td>\n",
              "      <td>8</td>\n",
              "      <td>360.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>4654</td>\n",
              "      <td>13.0</td>\n",
              "      <td>73</td>\n",
              "      <td>1</td>\n",
              "      <td>plymouth custom suburb</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>156</th>\n",
              "      <td>16.0</td>\n",
              "      <td>8</td>\n",
              "      <td>400.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>4668</td>\n",
              "      <td>11.5</td>\n",
              "      <td>75</td>\n",
              "      <td>1</td>\n",
              "      <td>pontiac catalina</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>230</th>\n",
              "      <td>15.5</td>\n",
              "      <td>8</td>\n",
              "      <td>350.0</td>\n",
              "      <td>170.0</td>\n",
              "      <td>4165</td>\n",
              "      <td>11.4</td>\n",
              "      <td>77</td>\n",
              "      <td>1</td>\n",
              "      <td>chevrolet monte carlo landau</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>263</th>\n",
              "      <td>17.7</td>\n",
              "      <td>6</td>\n",
              "      <td>231.0</td>\n",
              "      <td>165.0</td>\n",
              "      <td>3445</td>\n",
              "      <td>13.4</td>\n",
              "      <td>78</td>\n",
              "      <td>1</td>\n",
              "      <td>buick regal sport coupe (turbo)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>289</th>\n",
              "      <td>16.9</td>\n",
              "      <td>8</td>\n",
              "      <td>350.0</td>\n",
              "      <td>155.0</td>\n",
              "      <td>4360</td>\n",
              "      <td>14.9</td>\n",
              "      <td>79</td>\n",
              "      <td>1</td>\n",
              "      <td>buick estate wagon (sw)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a79366e0-152d-42c8-89a4-22791015179f')\"\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-a79366e0-152d-42c8-89a4-22791015179f 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-a79366e0-152d-42c8-89a4-22791015179f');\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": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#7 Elinizdeki df'i horsepower'a göre büyükten küçüğe sıralayın ardından df'in indexlerini sıfırlayın.\n",
        "\n",
        "df.sort_values(by= 'horsepower' , ascending = False)\n",
        "df.reset_index()   \n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "NX_qVQiDUBLh",
        "outputId": "99733df9-595d-4134-d348-8165d7a54860"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     index   mpg  cylinders  displacement horsepower  weight  acceleration  \\\n",
              "0        0  18.0          8         307.0        130    3504          12.0   \n",
              "1        1  15.0          8         350.0        165    3693          11.5   \n",
              "2        2  18.0          8         318.0        150    3436          11.0   \n",
              "3        3  16.0          8         304.0        150    3433          12.0   \n",
              "4        4  17.0          8         302.0        140    3449          10.5   \n",
              "..     ...   ...        ...           ...        ...     ...           ...   \n",
              "393    393  27.0          4         140.0         86    2790          15.6   \n",
              "394    394  44.0          4          97.0         52    2130          24.6   \n",
              "395    395  32.0          4         135.0         84    2295          11.6   \n",
              "396    396  28.0          4         120.0         79    2625          18.6   \n",
              "397    397  31.0          4         119.0         82    2720          19.4   \n",
              "\n",
              "     model_year  origin                       name  \n",
              "0            70       1  chevrolet chevelle malibu  \n",
              "1            70       1          buick skylark 320  \n",
              "2            70       1         plymouth satellite  \n",
              "3            70       1              amc rebel sst  \n",
              "4            70       1                ford torino  \n",
              "..          ...     ...                        ...  \n",
              "393          82       1            ford mustang gl  \n",
              "394          82       2                  vw pickup  \n",
              "395          82       1              dodge rampage  \n",
              "396          82       1                ford ranger  \n",
              "397          82       1                 chevy s-10  \n",
              "\n",
              "[398 rows x 10 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1c06c6b9-ce1b-421c-ac73-9449b2dd27b8\">\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>index</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>0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>8</td>\n",
              "      <td>307.0</td>\n",
              "      <td>130</td>\n",
              "      <td>3504</td>\n",
              "      <td>12.0</td>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>chevrolet chevelle malibu</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>15.0</td>\n",
              "      <td>8</td>\n",
              "      <td>350.0</td>\n",
              "      <td>165</td>\n",
              "      <td>3693</td>\n",
              "      <td>11.5</td>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>buick skylark 320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>18.0</td>\n",
              "      <td>8</td>\n",
              "      <td>318.0</td>\n",
              "      <td>150</td>\n",
              "      <td>3436</td>\n",
              "      <td>11.0</td>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>plymouth satellite</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>16.0</td>\n",
              "      <td>8</td>\n",
              "      <td>304.0</td>\n",
              "      <td>150</td>\n",
              "      <td>3433</td>\n",
              "      <td>12.0</td>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>amc rebel sst</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>17.0</td>\n",
              "      <td>8</td>\n",
              "      <td>302.0</td>\n",
              "      <td>140</td>\n",
              "      <td>3449</td>\n",
              "      <td>10.5</td>\n",
              "      <td>70</td>\n",
              "      <td>1</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",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>393</th>\n",
              "      <td>393</td>\n",
              "      <td>27.0</td>\n",
              "      <td>4</td>\n",
              "      <td>140.0</td>\n",
              "      <td>86</td>\n",
              "      <td>2790</td>\n",
              "      <td>15.6</td>\n",
              "      <td>82</td>\n",
              "      <td>1</td>\n",
              "      <td>ford mustang gl</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>394</th>\n",
              "      <td>394</td>\n",
              "      <td>44.0</td>\n",
              "      <td>4</td>\n",
              "      <td>97.0</td>\n",
              "      <td>52</td>\n",
              "      <td>2130</td>\n",
              "      <td>24.6</td>\n",
              "      <td>82</td>\n",
              "      <td>2</td>\n",
              "      <td>vw pickup</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>395</th>\n",
              "      <td>395</td>\n",
              "      <td>32.0</td>\n",
              "      <td>4</td>\n",
              "      <td>135.0</td>\n",
              "      <td>84</td>\n",
              "      <td>2295</td>\n",
              "      <td>11.6</td>\n",
              "      <td>82</td>\n",
              "      <td>1</td>\n",
              "      <td>dodge rampage</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>396</th>\n",
              "      <td>396</td>\n",
              "      <td>28.0</td>\n",
              "      <td>4</td>\n",
              "      <td>120.0</td>\n",
              "      <td>79</td>\n",
              "      <td>2625</td>\n",
              "      <td>18.6</td>\n",
              "      <td>82</td>\n",
              "      <td>1</td>\n",
              "      <td>ford ranger</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>397</th>\n",
              "      <td>397</td>\n",
              "      <td>31.0</td>\n",
              "      <td>4</td>\n",
              "      <td>119.0</td>\n",
              "      <td>82</td>\n",
              "      <td>2720</td>\n",
              "      <td>19.4</td>\n",
              "      <td>82</td>\n",
              "      <td>1</td>\n",
              "      <td>chevy s-10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>398 rows × 10 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1c06c6b9-ce1b-421c-ac73-9449b2dd27b8')\"\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-1c06c6b9-ce1b-421c-ac73-9449b2dd27b8 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-1c06c6b9-ce1b-421c-ac73-9449b2dd27b8');\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": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#8 Elinizdeki df'den en küçük 5 acceralation'a sahip olan arabaları getirin.\n",
        "\n",
        "df.nsmallest(columns= ['acceleration'] , n = 5)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "_-kQIFlEUxrW",
        "outputId": "957d1a4f-8320-454a-dfea-348553eea9be"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      mpg  cylinders  displacement horsepower  weight  acceleration  \\\n",
              "268  14.0          8         340.0        160    3609           8.0   \n",
              "237  14.0          8         440.0        215    4312           8.5   \n",
              "246  15.0          8         390.0        190    3850           8.5   \n",
              "235  14.0          8         454.0        220    4354           9.0   \n",
              "231  16.0          8         400.0        230    4278           9.5   \n",
              "\n",
              "     model_year  origin                name  \n",
              "268          70       1  plymouth 'cuda 340  \n",
              "237          70       1   plymouth fury iii  \n",
              "246          70       1  amc ambassador dpl  \n",
              "235          70       1    chevrolet impala  \n",
              "231          73       1  pontiac grand prix  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-145efd71-be3b-4d33-b63a-cc1a94ec3ad7\">\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>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>268</th>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>340.0</td>\n",
              "      <td>160</td>\n",
              "      <td>3609</td>\n",
              "      <td>8.0</td>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>plymouth 'cuda 340</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237</th>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>440.0</td>\n",
              "      <td>215</td>\n",
              "      <td>4312</td>\n",
              "      <td>8.5</td>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>plymouth fury iii</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>246</th>\n",
              "      <td>15.0</td>\n",
              "      <td>8</td>\n",
              "      <td>390.0</td>\n",
              "      <td>190</td>\n",
              "      <td>3850</td>\n",
              "      <td>8.5</td>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>amc ambassador dpl</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>235</th>\n",
              "      <td>14.0</td>\n",
              "      <td>8</td>\n",
              "      <td>454.0</td>\n",
              "      <td>220</td>\n",
              "      <td>4354</td>\n",
              "      <td>9.0</td>\n",
              "      <td>70</td>\n",
              "      <td>1</td>\n",
              "      <td>chevrolet impala</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>231</th>\n",
              "      <td>16.0</td>\n",
              "      <td>8</td>\n",
              "      <td>400.0</td>\n",
              "      <td>230</td>\n",
              "      <td>4278</td>\n",
              "      <td>9.5</td>\n",
              "      <td>73</td>\n",
              "      <td>1</td>\n",
              "      <td>pontiac grand prix</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-145efd71-be3b-4d33-b63a-cc1a94ec3ad7')\"\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-145efd71-be3b-4d33-b63a-cc1a94ec3ad7 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-145efd71-be3b-4d33-b63a-cc1a94ec3ad7');\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
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#--- CIA_Country_Facts.csv dosyasını okuyun ve yeniden df değişkenine atayın.(Artık eski df ile işimiz kalmadığı için aynı ismi verebiliriz.)\n",
        "#9) Elimizdeki CIA'in ülkeler hakkında topladığı basit açık kaynak verileri df'inde kaç ülkenin verisi olduğunu bulun.\n",
        "\n",
        "df = pd.read_csv('CIA_Country_Facts.csv')\n",
        "df.head()\n",
        "df.Country.nunique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_xNJOosvYStu",
        "outputId": "93ee112c-f6f3-4019-9d9e-dca556517dc2"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "227"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#10 Elimizdeki sütunlardan hangilerinde kaçar tane nan veri olduğunu bulun.\n",
        "\n",
        "df.isna().sum()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r1_WWZ76aeqb",
        "outputId": "a4ecc923-92ee-4f24-aa43-e23e975b819e"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Country                                0\n",
              "Region                                 0\n",
              "Population                             0\n",
              "Area (sq. mi.)                         0\n",
              "Pop. Density (per sq. mi.)             0\n",
              "Coastline (coast/area ratio)           0\n",
              "Net migration                          3\n",
              "Infant mortality (per 1000 births)     3\n",
              "GDP ($ per capita)                     1\n",
              "Literacy (%)                          18\n",
              "Phones (per 1000)                      4\n",
              "Arable (%)                             2\n",
              "Crops (%)                              2\n",
              "Other (%)                              2\n",
              "Climate                               22\n",
              "Birthrate                              3\n",
              "Deathrate                              4\n",
              "Agriculture                           15\n",
              "Industry                              16\n",
              "Service                               15\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#11 Elimizde tamamen nan değerlerden oluşan bir satır varsa o satırı düşürün.(Tamamen nan değerlerden oluşan bir satır olup olmadığını, herhangi bir satırın düşüp düşmediğini kontrol edin)\n",
        "\n",
        "df.dropna(how = 'all')\n",
        "## 227 satır kaldığına göre tüm değerleri NaN olan bir değer yok"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 782
        },
        "id": "BT-Pd6y8ayeq",
        "outputId": "d74f9878-dde9-46fa-ffe6-67c405afa6bd"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Country                               Region  Population  \\\n",
              "0       Afghanistan        ASIA (EX. NEAR EAST)             31056997   \n",
              "1           Albania  EASTERN EUROPE                          3581655   \n",
              "2           Algeria  NORTHERN AFRICA                        32930091   \n",
              "3    American Samoa  OCEANIA                                   57794   \n",
              "4           Andorra  WESTERN EUROPE                            71201   \n",
              "..              ...                                  ...         ...   \n",
              "222       West Bank  NEAR EAST                               2460492   \n",
              "223  Western Sahara  NORTHERN AFRICA                          273008   \n",
              "224           Yemen  NEAR EAST                              21456188   \n",
              "225          Zambia  SUB-SAHARAN AFRICA                     11502010   \n",
              "226        Zimbabwe  SUB-SAHARAN AFRICA                     12236805   \n",
              "\n",
              "     Area (sq. mi.)  Pop. Density (per sq. mi.)  Coastline (coast/area ratio)  \\\n",
              "0            647500                        48.0                          0.00   \n",
              "1             28748                       124.6                          1.26   \n",
              "2           2381740                        13.8                          0.04   \n",
              "3               199                       290.4                         58.29   \n",
              "4               468                       152.1                          0.00   \n",
              "..              ...                         ...                           ...   \n",
              "222            5860                       419.9                          0.00   \n",
              "223          266000                         1.0                          0.42   \n",
              "224          527970                        40.6                          0.36   \n",
              "225          752614                        15.3                          0.00   \n",
              "226          390580                        31.3                          0.00   \n",
              "\n",
              "     Net migration  Infant mortality (per 1000 births)  GDP ($ per capita)  \\\n",
              "0            23.06                              163.07               700.0   \n",
              "1            -4.93                               21.52              4500.0   \n",
              "2            -0.39                               31.00              6000.0   \n",
              "3           -20.71                                9.27              8000.0   \n",
              "4             6.60                                4.05             19000.0   \n",
              "..             ...                                 ...                 ...   \n",
              "222           2.98                               19.62               800.0   \n",
              "223            NaN                                 NaN                 NaN   \n",
              "224           0.00                               61.50               800.0   \n",
              "225           0.00                               88.29               800.0   \n",
              "226           0.00                               67.69              1900.0   \n",
              "\n",
              "     Literacy (%)  Phones (per 1000)  Arable (%)  Crops (%)  Other (%)  \\\n",
              "0            36.0                3.2       12.13       0.22      87.65   \n",
              "1            86.5               71.2       21.09       4.42      74.49   \n",
              "2            70.0               78.1        3.22       0.25      96.53   \n",
              "3            97.0              259.5       10.00      15.00      75.00   \n",
              "4           100.0              497.2        2.22       0.00      97.78   \n",
              "..            ...                ...         ...        ...        ...   \n",
              "222           NaN              145.2       16.90      18.97      64.13   \n",
              "223           NaN                NaN        0.02       0.00      99.98   \n",
              "224          50.2               37.2        2.78       0.24      96.98   \n",
              "225          80.6                8.2        7.08       0.03      92.90   \n",
              "226          90.7               26.8        8.32       0.34      91.34   \n",
              "\n",
              "     Climate  Birthrate  Deathrate  Agriculture  Industry  Service  \n",
              "0        1.0      46.60      20.34        0.380     0.240    0.380  \n",
              "1        3.0      15.11       5.22        0.232     0.188    0.579  \n",
              "2        1.0      17.14       4.61        0.101     0.600    0.298  \n",
              "3        2.0      22.46       3.27          NaN       NaN      NaN  \n",
              "4        3.0       8.71       6.25          NaN       NaN      NaN  \n",
              "..       ...        ...        ...          ...       ...      ...  \n",
              "222      3.0      31.67       3.92        0.090     0.280    0.630  \n",
              "223      1.0        NaN        NaN          NaN       NaN    0.400  \n",
              "224      1.0      42.89       8.30        0.135     0.472    0.393  \n",
              "225      2.0      41.00      19.93        0.220     0.290    0.489  \n",
              "226      2.0      28.01      21.84        0.179     0.243    0.579  \n",
              "\n",
              "[227 rows x 20 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-02a59ee0-db71-4a07-aa2e-14a7e83c69a1\">\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>Country</th>\n",
              "      <th>Region</th>\n",
              "      <th>Population</th>\n",
              "      <th>Area (sq. mi.)</th>\n",
              "      <th>Pop. Density (per sq. mi.)</th>\n",
              "      <th>Coastline (coast/area ratio)</th>\n",
              "      <th>Net migration</th>\n",
              "      <th>Infant mortality (per 1000 births)</th>\n",
              "      <th>GDP ($ per capita)</th>\n",
              "      <th>Literacy (%)</th>\n",
              "      <th>Phones (per 1000)</th>\n",
              "      <th>Arable (%)</th>\n",
              "      <th>Crops (%)</th>\n",
              "      <th>Other (%)</th>\n",
              "      <th>Climate</th>\n",
              "      <th>Birthrate</th>\n",
              "      <th>Deathrate</th>\n",
              "      <th>Agriculture</th>\n",
              "      <th>Industry</th>\n",
              "      <th>Service</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>ASIA (EX. NEAR EAST)</td>\n",
              "      <td>31056997</td>\n",
              "      <td>647500</td>\n",
              "      <td>48.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>23.06</td>\n",
              "      <td>163.07</td>\n",
              "      <td>700.0</td>\n",
              "      <td>36.0</td>\n",
              "      <td>3.2</td>\n",
              "      <td>12.13</td>\n",
              "      <td>0.22</td>\n",
              "      <td>87.65</td>\n",
              "      <td>1.0</td>\n",
              "      <td>46.60</td>\n",
              "      <td>20.34</td>\n",
              "      <td>0.380</td>\n",
              "      <td>0.240</td>\n",
              "      <td>0.380</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Albania</td>\n",
              "      <td>EASTERN EUROPE</td>\n",
              "      <td>3581655</td>\n",
              "      <td>28748</td>\n",
              "      <td>124.6</td>\n",
              "      <td>1.26</td>\n",
              "      <td>-4.93</td>\n",
              "      <td>21.52</td>\n",
              "      <td>4500.0</td>\n",
              "      <td>86.5</td>\n",
              "      <td>71.2</td>\n",
              "      <td>21.09</td>\n",
              "      <td>4.42</td>\n",
              "      <td>74.49</td>\n",
              "      <td>3.0</td>\n",
              "      <td>15.11</td>\n",
              "      <td>5.22</td>\n",
              "      <td>0.232</td>\n",
              "      <td>0.188</td>\n",
              "      <td>0.579</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Algeria</td>\n",
              "      <td>NORTHERN AFRICA</td>\n",
              "      <td>32930091</td>\n",
              "      <td>2381740</td>\n",
              "      <td>13.8</td>\n",
              "      <td>0.04</td>\n",
              "      <td>-0.39</td>\n",
              "      <td>31.00</td>\n",
              "      <td>6000.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>78.1</td>\n",
              "      <td>3.22</td>\n",
              "      <td>0.25</td>\n",
              "      <td>96.53</td>\n",
              "      <td>1.0</td>\n",
              "      <td>17.14</td>\n",
              "      <td>4.61</td>\n",
              "      <td>0.101</td>\n",
              "      <td>0.600</td>\n",
              "      <td>0.298</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>American Samoa</td>\n",
              "      <td>OCEANIA</td>\n",
              "      <td>57794</td>\n",
              "      <td>199</td>\n",
              "      <td>290.4</td>\n",
              "      <td>58.29</td>\n",
              "      <td>-20.71</td>\n",
              "      <td>9.27</td>\n",
              "      <td>8000.0</td>\n",
              "      <td>97.0</td>\n",
              "      <td>259.5</td>\n",
              "      <td>10.00</td>\n",
              "      <td>15.00</td>\n",
              "      <td>75.00</td>\n",
              "      <td>2.0</td>\n",
              "      <td>22.46</td>\n",
              "      <td>3.27</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Andorra</td>\n",
              "      <td>WESTERN EUROPE</td>\n",
              "      <td>71201</td>\n",
              "      <td>468</td>\n",
              "      <td>152.1</td>\n",
              "      <td>0.00</td>\n",
              "      <td>6.60</td>\n",
              "      <td>4.05</td>\n",
              "      <td>19000.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>497.2</td>\n",
              "      <td>2.22</td>\n",
              "      <td>0.00</td>\n",
              "      <td>97.78</td>\n",
              "      <td>3.0</td>\n",
              "      <td>8.71</td>\n",
              "      <td>6.25</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <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>222</th>\n",
              "      <td>West Bank</td>\n",
              "      <td>NEAR EAST</td>\n",
              "      <td>2460492</td>\n",
              "      <td>5860</td>\n",
              "      <td>419.9</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.98</td>\n",
              "      <td>19.62</td>\n",
              "      <td>800.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>145.2</td>\n",
              "      <td>16.90</td>\n",
              "      <td>18.97</td>\n",
              "      <td>64.13</td>\n",
              "      <td>3.0</td>\n",
              "      <td>31.67</td>\n",
              "      <td>3.92</td>\n",
              "      <td>0.090</td>\n",
              "      <td>0.280</td>\n",
              "      <td>0.630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>223</th>\n",
              "      <td>Western Sahara</td>\n",
              "      <td>NORTHERN AFRICA</td>\n",
              "      <td>273008</td>\n",
              "      <td>266000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.42</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.00</td>\n",
              "      <td>99.98</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>224</th>\n",
              "      <td>Yemen</td>\n",
              "      <td>NEAR EAST</td>\n",
              "      <td>21456188</td>\n",
              "      <td>527970</td>\n",
              "      <td>40.6</td>\n",
              "      <td>0.36</td>\n",
              "      <td>0.00</td>\n",
              "      <td>61.50</td>\n",
              "      <td>800.0</td>\n",
              "      <td>50.2</td>\n",
              "      <td>37.2</td>\n",
              "      <td>2.78</td>\n",
              "      <td>0.24</td>\n",
              "      <td>96.98</td>\n",
              "      <td>1.0</td>\n",
              "      <td>42.89</td>\n",
              "      <td>8.30</td>\n",
              "      <td>0.135</td>\n",
              "      <td>0.472</td>\n",
              "      <td>0.393</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>225</th>\n",
              "      <td>Zambia</td>\n",
              "      <td>SUB-SAHARAN AFRICA</td>\n",
              "      <td>11502010</td>\n",
              "      <td>752614</td>\n",
              "      <td>15.3</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>88.29</td>\n",
              "      <td>800.0</td>\n",
              "      <td>80.6</td>\n",
              "      <td>8.2</td>\n",
              "      <td>7.08</td>\n",
              "      <td>0.03</td>\n",
              "      <td>92.90</td>\n",
              "      <td>2.0</td>\n",
              "      <td>41.00</td>\n",
              "      <td>19.93</td>\n",
              "      <td>0.220</td>\n",
              "      <td>0.290</td>\n",
              "      <td>0.489</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>226</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>SUB-SAHARAN AFRICA</td>\n",
              "      <td>12236805</td>\n",
              "      <td>390580</td>\n",
              "      <td>31.3</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>67.69</td>\n",
              "      <td>1900.0</td>\n",
              "      <td>90.7</td>\n",
              "      <td>26.8</td>\n",
              "      <td>8.32</td>\n",
              "      <td>0.34</td>\n",
              "      <td>91.34</td>\n",
              "      <td>2.0</td>\n",
              "      <td>28.01</td>\n",
              "      <td>21.84</td>\n",
              "      <td>0.179</td>\n",
              "      <td>0.243</td>\n",
              "      <td>0.579</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>227 rows × 20 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-02a59ee0-db71-4a07-aa2e-14a7e83c69a1')\"\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-02a59ee0-db71-4a07-aa2e-14a7e83c69a1 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-02a59ee0-db71-4a07-aa2e-14a7e83c69a1');\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": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#12 Her Bölgedeki(Region) toplam kişi sayısına bakın.\n",
        "df.groupby(\"Region\").sum()[\"Population\"]\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "56V8Uqa8bnge",
        "outputId": "74742287-6470-46fc-c653-4dab86a54891"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Region\n",
              "ASIA (EX. NEAR EAST)                   3687982236\n",
              "BALTICS                                   7184974\n",
              "C.W. OF IND. STATES                     280081548\n",
              "EASTERN EUROPE                          119914717\n",
              "LATIN AMER. & CARIB                     561824599\n",
              "NEAR EAST                               195068377\n",
              "NORTHERN AFRICA                         161407133\n",
              "NORTHERN AMERICA                        331672307\n",
              "OCEANIA                                  33131662\n",
              "SUB-SAHARAN AFRICA                      749437000\n",
              "WESTERN EUROPE                          396339998\n",
              "Name: Population, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#13 Climate değerleri nan olanlar, tüm df'in ortalama climate değeriyle doldurun.(Gerçek bir analiz yapıyor olsaydık bu çok mantıklı bir hareket olmazdı, belki her bulunduğu bölgenin ortalama climate değeriyle doldurmak daha mantıklı bir hareket olurdu. Fakat şimdilik bu kadar kasmaya gerek yok. nan değerleri tüm climate ortalamalarıyla doldursanız yeterli.)\n",
        "\n",
        "df.Climate.fillna(df.Climate.mean() , axis = 0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BErOdOlLfK2F",
        "outputId": "da6325fb-0f0e-4347-8884-f73663f79f5c"
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      1.0\n",
              "1      3.0\n",
              "2      1.0\n",
              "3      2.0\n",
              "4      3.0\n",
              "      ... \n",
              "222    3.0\n",
              "223    1.0\n",
              "224    1.0\n",
              "225    2.0\n",
              "226    2.0\n",
              "Name: Climate, Length: 227, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#14 Bölgeler ve Ülkelere göre gruplama yapın ardından Doğum miktarlarına bakın.\n",
        "\n",
        "df.groupby([\"Region\" , \"Country\"]).sum()[\"Birthrate\"]\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qolDQd1Lh1Ni",
        "outputId": "9e42f9c9-ff78-4f69-da23-5e0b3a3d7c95"
      },
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Region                               Country       \n",
              "ASIA (EX. NEAR EAST)                 Afghanistan       46.60\n",
              "                                     Bangladesh        29.80\n",
              "                                     Bhutan            33.65\n",
              "                                     Brunei            18.79\n",
              "                                     Burma             17.91\n",
              "                                                       ...  \n",
              "WESTERN EUROPE                       San Marino        10.02\n",
              "                                     Spain             10.06\n",
              "                                     Sweden            10.27\n",
              "                                     Switzerland        9.71\n",
              "                                     United Kingdom    10.71\n",
              "Name: Birthrate, Length: 227, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#15 Veriyi istediğiniz şekilde inceleyerek bu zamana kadar öğrendiğiniz bilgilerle anlamlı 5 adet yargı cümlesi çıkartın. ( En çok insan Asya kıtasında yaşıyor, En çok insan Afrinın sahralarında ölüyor, Ortalama en yüksek telefon sahibi Kuzey Amerikada, En çok okuma yazma oranına sahip ülkeler Baltık ülkeleri vb.)\n",
        "#15.1 en çok doğum oranı olan ülke \n",
        "df[df.Birthrate == df.Birthrate.max()].Country\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BwlNyzC6jTqM",
        "outputId": "f1bf2536-5bdf-4d96-db52-acae2f15d89a"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "151    Niger\n",
              "Name: Country, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#15.2 kıyı şeridi olan ülkeler \n",
        "df.sort_values(\"Coastline (coast/area ratio)\" , ascending = False).head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "ehVVsTmInWDK",
        "outputId": "302d3821-585a-448d-e6eb-39bb25bb842c"
      },
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  Country                               Region  Population  \\\n",
              "136  Micronesia, Fed. St.  OCEANIA                                  108004   \n",
              "157                 Palau  OCEANIA                                   20579   \n",
              "153    N. Mariana Islands  OCEANIA                                   82459   \n",
              "127              Maldives        ASIA (EX. NEAR EAST)               359008   \n",
              "138                Monaco  WESTERN EUROPE                            32543   \n",
              "\n",
              "     Area (sq. mi.)  Pop. Density (per sq. mi.)  Coastline (coast/area ratio)  \\\n",
              "136             702                       153.9                        870.66   \n",
              "157             458                        44.9                        331.66   \n",
              "153             477                       172.9                        310.69   \n",
              "127             300                      1196.7                        214.67   \n",
              "138               2                     16271.5                        205.00   \n",
              "\n",
              "     Net migration  Infant mortality (per 1000 births)  GDP ($ per capita)  \\\n",
              "136         -20.99                               30.21              2000.0   \n",
              "157           2.85                               14.84              9000.0   \n",
              "153           9.61                                7.11             12500.0   \n",
              "127           0.00                               56.52              3900.0   \n",
              "138           7.75                                5.43             27000.0   \n",
              "\n",
              "     Literacy (%)  Phones (per 1000)  Arable (%)  Crops (%)  Other (%)  \\\n",
              "136          89.0              114.8        5.71      45.71      48.58   \n",
              "157          92.0              325.6        8.70       4.35      86.95   \n",
              "153          97.0              254.7       13.04       4.35      82.61   \n",
              "127          97.2               90.0       13.33      16.67      70.00   \n",
              "138          99.0             1035.6        0.00       0.00     100.00   \n",
              "\n",
              "     Climate  Birthrate  Deathrate  Agriculture  Industry  Service  \n",
              "136      2.0      24.68       4.75        0.289     0.152    0.559  \n",
              "157      2.0      18.03       6.80        0.062     0.120    0.818  \n",
              "153      2.0      19.43       2.29          NaN       NaN      NaN  \n",
              "127      2.0      34.81       7.06        0.200     0.180    0.620  \n",
              "138      NaN       9.19      12.91        0.170       NaN      NaN  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-20e6d628-78a1-46b8-8bf9-1f0535c3b47f\">\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>Country</th>\n",
              "      <th>Region</th>\n",
              "      <th>Population</th>\n",
              "      <th>Area (sq. mi.)</th>\n",
              "      <th>Pop. Density (per sq. mi.)</th>\n",
              "      <th>Coastline (coast/area ratio)</th>\n",
              "      <th>Net migration</th>\n",
              "      <th>Infant mortality (per 1000 births)</th>\n",
              "      <th>GDP ($ per capita)</th>\n",
              "      <th>Literacy (%)</th>\n",
              "      <th>Phones (per 1000)</th>\n",
              "      <th>Arable (%)</th>\n",
              "      <th>Crops (%)</th>\n",
              "      <th>Other (%)</th>\n",
              "      <th>Climate</th>\n",
              "      <th>Birthrate</th>\n",
              "      <th>Deathrate</th>\n",
              "      <th>Agriculture</th>\n",
              "      <th>Industry</th>\n",
              "      <th>Service</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>136</th>\n",
              "      <td>Micronesia, Fed. St.</td>\n",
              "      <td>OCEANIA</td>\n",
              "      <td>108004</td>\n",
              "      <td>702</td>\n",
              "      <td>153.9</td>\n",
              "      <td>870.66</td>\n",
              "      <td>-20.99</td>\n",
              "      <td>30.21</td>\n",
              "      <td>2000.0</td>\n",
              "      <td>89.0</td>\n",
              "      <td>114.8</td>\n",
              "      <td>5.71</td>\n",
              "      <td>45.71</td>\n",
              "      <td>48.58</td>\n",
              "      <td>2.0</td>\n",
              "      <td>24.68</td>\n",
              "      <td>4.75</td>\n",
              "      <td>0.289</td>\n",
              "      <td>0.152</td>\n",
              "      <td>0.559</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>157</th>\n",
              "      <td>Palau</td>\n",
              "      <td>OCEANIA</td>\n",
              "      <td>20579</td>\n",
              "      <td>458</td>\n",
              "      <td>44.9</td>\n",
              "      <td>331.66</td>\n",
              "      <td>2.85</td>\n",
              "      <td>14.84</td>\n",
              "      <td>9000.0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>325.6</td>\n",
              "      <td>8.70</td>\n",
              "      <td>4.35</td>\n",
              "      <td>86.95</td>\n",
              "      <td>2.0</td>\n",
              "      <td>18.03</td>\n",
              "      <td>6.80</td>\n",
              "      <td>0.062</td>\n",
              "      <td>0.120</td>\n",
              "      <td>0.818</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>153</th>\n",
              "      <td>N. Mariana Islands</td>\n",
              "      <td>OCEANIA</td>\n",
              "      <td>82459</td>\n",
              "      <td>477</td>\n",
              "      <td>172.9</td>\n",
              "      <td>310.69</td>\n",
              "      <td>9.61</td>\n",
              "      <td>7.11</td>\n",
              "      <td>12500.0</td>\n",
              "      <td>97.0</td>\n",
              "      <td>254.7</td>\n",
              "      <td>13.04</td>\n",
              "      <td>4.35</td>\n",
              "      <td>82.61</td>\n",
              "      <td>2.0</td>\n",
              "      <td>19.43</td>\n",
              "      <td>2.29</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>127</th>\n",
              "      <td>Maldives</td>\n",
              "      <td>ASIA (EX. NEAR EAST)</td>\n",
              "      <td>359008</td>\n",
              "      <td>300</td>\n",
              "      <td>1196.7</td>\n",
              "      <td>214.67</td>\n",
              "      <td>0.00</td>\n",
              "      <td>56.52</td>\n",
              "      <td>3900.0</td>\n",
              "      <td>97.2</td>\n",
              "      <td>90.0</td>\n",
              "      <td>13.33</td>\n",
              "      <td>16.67</td>\n",
              "      <td>70.00</td>\n",
              "      <td>2.0</td>\n",
              "      <td>34.81</td>\n",
              "      <td>7.06</td>\n",
              "      <td>0.200</td>\n",
              "      <td>0.180</td>\n",
              "      <td>0.620</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>138</th>\n",
              "      <td>Monaco</td>\n",
              "      <td>WESTERN EUROPE</td>\n",
              "      <td>32543</td>\n",
              "      <td>2</td>\n",
              "      <td>16271.5</td>\n",
              "      <td>205.00</td>\n",
              "      <td>7.75</td>\n",
              "      <td>5.43</td>\n",
              "      <td>27000.0</td>\n",
              "      <td>99.0</td>\n",
              "      <td>1035.6</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>100.00</td>\n",
              "      <td>NaN</td>\n",
              "      <td>9.19</td>\n",
              "      <td>12.91</td>\n",
              "      <td>0.170</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-20e6d628-78a1-46b8-8bf9-1f0535c3b47f')\"\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-20e6d628-78a1-46b8-8bf9-1f0535c3b47f 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-20e6d628-78a1-46b8-8bf9-1f0535c3b47f');\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": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#15.3 Tarıma en elverişli 3 bölge\n",
        "\n",
        "df.groupby(\"Region\")[\"Arable (%)\"].max().head(3)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MharozZUnYkt",
        "outputId": "4bed9ea3-4761-4c8d-9aae-3f60e788988e"
      },
      "execution_count": 73,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Region\n",
              "ASIA (EX. NEAR EAST)                   62.11\n",
              "BALTICS                                45.22\n",
              "C.W. OF IND. STATES                    56.21\n",
              "Name: Arable (%), dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#15.4 Nüfusuna Oranla En Az Okur-Yazarlığı Olan 2 batı avrpa Ülkesi\n",
        "\n",
        "df[\"sonuc\"] = np.floor(((df.Population * df[\"Literacy (%)\"]) / 100)) / df.Population\n",
        "df[\"sonuc\"] = df[\"sonuc\"].dropna()\n",
        "df[df.Region == \"WESTERN EUROPE \"].sort_values(\"sonuc\").head(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 192
        },
        "id": "Z51i9ZJuoPGa",
        "outputId": "7b3ad945-cdc8-4f6a-f7c8-467ac208335e"
      },
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [Country, Region, Population, Area (sq. mi.), Pop. Density (per sq. mi.), Coastline (coast/area ratio), Net migration, Infant mortality (per 1000 births), GDP ($ per capita), Literacy (%), Phones (per 1000), Arable (%), Crops (%), Other (%), Climate, Birthrate, Deathrate, Agriculture, Industry, Service, Test, sonuc]\n",
              "Index: []\n",
              "\n",
              "[0 rows x 22 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b1910012-1dca-491d-81f0-9d24dd450daf\">\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>Country</th>\n",
              "      <th>Region</th>\n",
              "      <th>Population</th>\n",
              "      <th>Area (sq. mi.)</th>\n",
              "      <th>Pop. Density (per sq. mi.)</th>\n",
              "      <th>Coastline (coast/area ratio)</th>\n",
              "      <th>Net migration</th>\n",
              "      <th>Infant mortality (per 1000 births)</th>\n",
              "      <th>GDP ($ per capita)</th>\n",
              "      <th>Literacy (%)</th>\n",
              "      <th>...</th>\n",
              "      <th>Crops (%)</th>\n",
              "      <th>Other (%)</th>\n",
              "      <th>Climate</th>\n",
              "      <th>Birthrate</th>\n",
              "      <th>Deathrate</th>\n",
              "      <th>Agriculture</th>\n",
              "      <th>Industry</th>\n",
              "      <th>Service</th>\n",
              "      <th>Test</th>\n",
              "      <th>sonuc</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>0 rows × 22 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b1910012-1dca-491d-81f0-9d24dd450daf')\"\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-b1910012-1dca-491d-81f0-9d24dd450daf 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-b1910012-1dca-491d-81f0-9d24dd450daf');\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": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#15.5 refah seviyesi en düşük olan ülkeler\n",
        "\n",
        "df[df[\"GDP ($ per capita)\"] == df[\"GDP ($ per capita)\"].min()].Country"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dZjeDALdpDLo",
        "outputId": "a269f80b-cd18-4dbd-ebcf-76f9cecad175"
      },
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "58       East Timor\n",
              "183    Sierra Leone\n",
              "188         Somalia\n",
              "Name: Country, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 82
        }
      ]
    }
  ]
}