Project_Meteorite.ipynb

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    "colab": {
      "name": "Project_Meteorite.ipynb",
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      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/abhinav-bhardwaj/Meteorite-Landings-Data-Analysis/blob/master/Project_Meteorite.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rOEt4Cn0_3sV"
      },
      "source": [
        "# **Data Analysis Project on Meteorite Landings Dataset (Recorded by The Meteorical Society and Provided by NASA)**\n",
        "\n",
        "**Abhinav Dubey**\n",
        "\n",
        "https://data.nasa.gov/Space-Science/Meteorite-Landings/gh4g-9sfh\n",
        "\n",
        "https://www.kaggle.com/nasa/meteorite-landings"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_mf0e_TZPfzl"
      },
      "source": [
        "***Metadata***\n",
        "* name: the name of the meteorite\n",
        "\n",
        "* id: a unique identifier for the meteorite\n",
        "* nametype: one of:\n",
        "-- valid: a typical meteorite\n",
        "-- relict: a meteorite that has been highly degraded by weather on Earth\n",
        "* recclass: the class of the meteorite (see the Wikipedia article on meteorite classification)\n",
        "* mass: the mass of the meteorite, in grams\n",
        "* fall: whether the meteorite was seen falling, or was discovered after its impact; one of:\n",
        "-- Fell: the meteorite's fall was observed\n",
        "-- Found: the meteorite's fall was not observed\n",
        "* year: the year the meteorite fell, or the year it was found (Any year before 860 CE or 2016 are in BCE)\n",
        "* reclat: the latitude of the meteorite's landing\n",
        "* reclong: the longitude of the meteorite's landing\n",
        "* GeoLocation: a parentheses-enclose, comma-separated tuple that combines reclat and reclong"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z8o1EFSRA0fc"
      },
      "source": [
        "***Importing Libraries***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QZkvXper0-Mz"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn import preprocessing"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Rtj1XOPIA8rp"
      },
      "source": [
        "***Importing Dataset***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nWI6sNbH4RXu"
      },
      "source": [
        "data = pd.read_csv('Meteorite_Landings.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NN3inbZ3MSBM"
      },
      "source": [
        "***Dataset***"
      ]
    },
    {
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        "id": "5O8qAbtD4YlW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "outputId": "359d0ec6-69f1-4d91-cbe9-871de8b7809b"
      },
      "source": [
        "data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Aachen</td>\n",
              "      <td>1</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L5</td>\n",
              "      <td>21.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1880.0</td>\n",
              "      <td>50.77500</td>\n",
              "      <td>6.08333</td>\n",
              "      <td>(50.775000, 6.083330)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Aarhus</td>\n",
              "      <td>2</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H6</td>\n",
              "      <td>720.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1951.0</td>\n",
              "      <td>56.18333</td>\n",
              "      <td>10.23333</td>\n",
              "      <td>(56.183330, 10.233330)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Abee</td>\n",
              "      <td>6</td>\n",
              "      <td>Valid</td>\n",
              "      <td>EH4</td>\n",
              "      <td>107000.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1952.0</td>\n",
              "      <td>54.21667</td>\n",
              "      <td>-113.00000</td>\n",
              "      <td>(54.216670, -113.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Acapulco</td>\n",
              "      <td>10</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Acapulcoite</td>\n",
              "      <td>1914.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1976.0</td>\n",
              "      <td>16.88333</td>\n",
              "      <td>-99.90000</td>\n",
              "      <td>(16.883330, -99.900000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Achiras</td>\n",
              "      <td>370</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L6</td>\n",
              "      <td>780.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1902.0</td>\n",
              "      <td>-33.16667</td>\n",
              "      <td>-64.95000</td>\n",
              "      <td>(-33.166670, -64.950000)</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>45711</th>\n",
              "      <td>Zillah 002</td>\n",
              "      <td>31356</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Eucrite</td>\n",
              "      <td>172.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>1990.0</td>\n",
              "      <td>29.03700</td>\n",
              "      <td>17.01850</td>\n",
              "      <td>(29.037000, 17.018500)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45712</th>\n",
              "      <td>Zinder</td>\n",
              "      <td>30409</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Pallasite, ungrouped</td>\n",
              "      <td>46.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>1999.0</td>\n",
              "      <td>13.78333</td>\n",
              "      <td>8.96667</td>\n",
              "      <td>(13.783330, 8.966670)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45713</th>\n",
              "      <td>Zlin</td>\n",
              "      <td>30410</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H4</td>\n",
              "      <td>3.3</td>\n",
              "      <td>Found</td>\n",
              "      <td>1939.0</td>\n",
              "      <td>49.25000</td>\n",
              "      <td>17.66667</td>\n",
              "      <td>(49.250000, 17.666670)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45714</th>\n",
              "      <td>Zubkovsky</td>\n",
              "      <td>31357</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L6</td>\n",
              "      <td>2167.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>2003.0</td>\n",
              "      <td>49.78917</td>\n",
              "      <td>41.50460</td>\n",
              "      <td>(49.789170, 41.504600)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45715</th>\n",
              "      <td>Zulu Queen</td>\n",
              "      <td>30414</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L3.7</td>\n",
              "      <td>200.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>1976.0</td>\n",
              "      <td>33.98333</td>\n",
              "      <td>-115.68333</td>\n",
              "      <td>(33.983330, -115.683330)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>45716 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             name     id  ...    reclong               GeoLocation\n",
              "0          Aachen      1  ...    6.08333     (50.775000, 6.083330)\n",
              "1          Aarhus      2  ...   10.23333    (56.183330, 10.233330)\n",
              "2            Abee      6  ... -113.00000  (54.216670, -113.000000)\n",
              "3        Acapulco     10  ...  -99.90000   (16.883330, -99.900000)\n",
              "4         Achiras    370  ...  -64.95000  (-33.166670, -64.950000)\n",
              "...           ...    ...  ...        ...                       ...\n",
              "45711  Zillah 002  31356  ...   17.01850    (29.037000, 17.018500)\n",
              "45712      Zinder  30409  ...    8.96667     (13.783330, 8.966670)\n",
              "45713        Zlin  30410  ...   17.66667    (49.250000, 17.666670)\n",
              "45714   Zubkovsky  31357  ...   41.50460    (49.789170, 41.504600)\n",
              "45715  Zulu Queen  30414  ... -115.68333  (33.983330, -115.683330)\n",
              "\n",
              "[45716 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PtKH9MmdBPeC"
      },
      "source": [
        "***Converting year column from float data type to integer data type***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Rq2i-sGIBO_1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d82986a5-e265-4985-ec6b-bc31fa73b049"
      },
      "source": [
        "data['year'].dtype"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dtype('float64')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qom0B_a3BsYh"
      },
      "source": [
        "data['year'] = data['year'].astype(pd.Int64Dtype())"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aBThcW-7Brkt",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cc409eda-e444-41c0-9983-2ca5efdd1f2f"
      },
      "source": [
        "data['year'].dtype"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Int64Dtype()"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DWPEO2JQBnAP"
      },
      "source": [
        "#Sorting dataset on basis of year in ascending order\n",
        "data.sort_values(by=['year'],inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RnL_1w6PBlIp",
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          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "outputId": "8aca8f1a-f02e-45e2-cd98-0d6b60cd6b81"
      },
      "source": [
        "data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>16356</th>\n",
              "      <td>Havana</td>\n",
              "      <td>11857</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron, IAB complex</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Found</td>\n",
              "      <td>301</td>\n",
              "      <td>40.33333</td>\n",
              "      <td>-90.05000</td>\n",
              "      <td>(40.333330, -90.050000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38301</th>\n",
              "      <td>Wietrzno-Bobrka</td>\n",
              "      <td>24259</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron</td>\n",
              "      <td>376.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>601</td>\n",
              "      <td>49.41667</td>\n",
              "      <td>21.70000</td>\n",
              "      <td>(49.416670, 21.700000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>703</th>\n",
              "      <td>Nogata</td>\n",
              "      <td>16988</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L6</td>\n",
              "      <td>472.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>860</td>\n",
              "      <td>33.72500</td>\n",
              "      <td>130.75000</td>\n",
              "      <td>(33.725000, 130.750000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>678</th>\n",
              "      <td>Narni</td>\n",
              "      <td>16914</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Stone-uncl</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Fell</td>\n",
              "      <td>920</td>\n",
              "      <td>42.51667</td>\n",
              "      <td>12.51667</td>\n",
              "      <td>(42.516670, 12.516670)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>278</th>\n",
              "      <td>Elbogen</td>\n",
              "      <td>7823</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron, IID</td>\n",
              "      <td>107000.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1399</td>\n",
              "      <td>50.18333</td>\n",
              "      <td>12.73333</td>\n",
              "      <td>(50.183330, 12.733330)</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>38128</th>\n",
              "      <td>Um-Hadid</td>\n",
              "      <td>24114</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Mesosiderite</td>\n",
              "      <td>15400.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>21.69500</td>\n",
              "      <td>50.59667</td>\n",
              "      <td>(21.695000, 50.596670)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38201</th>\n",
              "      <td>Valencia</td>\n",
              "      <td>24147</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H5</td>\n",
              "      <td>33500.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>39.00000</td>\n",
              "      <td>-0.03333</td>\n",
              "      <td>(39.000000, -0.033330)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38224</th>\n",
              "      <td>Villa Regina</td>\n",
              "      <td>53827</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron, IIIAB</td>\n",
              "      <td>5030.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>-39.10000</td>\n",
              "      <td>-67.06667</td>\n",
              "      <td>(-39.100000, -67.066670)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38328</th>\n",
              "      <td>Wiltshire</td>\n",
              "      <td>56143</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H5</td>\n",
              "      <td>92750.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>51.14967</td>\n",
              "      <td>-1.81000</td>\n",
              "      <td>(51.149670, -1.810000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45700</th>\n",
              "      <td>Zaragoza</td>\n",
              "      <td>48916</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron, IVA-an</td>\n",
              "      <td>162000.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>&lt;NA&gt;</td>\n",
              "      <td>41.65000</td>\n",
              "      <td>-0.86667</td>\n",
              "      <td>(41.650000, -0.866670)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>45716 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                  name     id  ...    reclong               GeoLocation\n",
              "16356           Havana  11857  ...  -90.05000   (40.333330, -90.050000)\n",
              "38301  Wietrzno-Bobrka  24259  ...   21.70000    (49.416670, 21.700000)\n",
              "703             Nogata  16988  ...  130.75000   (33.725000, 130.750000)\n",
              "678              Narni  16914  ...   12.51667    (42.516670, 12.516670)\n",
              "278            Elbogen   7823  ...   12.73333    (50.183330, 12.733330)\n",
              "...                ...    ...  ...        ...                       ...\n",
              "38128         Um-Hadid  24114  ...   50.59667    (21.695000, 50.596670)\n",
              "38201         Valencia  24147  ...   -0.03333    (39.000000, -0.033330)\n",
              "38224     Villa Regina  53827  ...  -67.06667  (-39.100000, -67.066670)\n",
              "38328        Wiltshire  56143  ...   -1.81000    (51.149670, -1.810000)\n",
              "45700         Zaragoza  48916  ...   -0.86667    (41.650000, -0.866670)\n",
              "\n",
              "[45716 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ni8RQPHGBN9l"
      },
      "source": [
        "***Checking abnormality specific to the Dataset***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3-4bDkopA-kS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        },
        "outputId": "5f500f2e-e956-43b2-a20e-92292cb5c7d7"
      },
      "source": [
        "#This dataset has data till 2016\n",
        "data[data['year']>2016]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>30679</th>\n",
              "      <td>Northwest Africa 7701</td>\n",
              "      <td>57150</td>\n",
              "      <td>Valid</td>\n",
              "      <td>CK6</td>\n",
              "      <td>55.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>2101</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>(0.000000, 0.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38188</th>\n",
              "      <td>Ur</td>\n",
              "      <td>24125</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Found</td>\n",
              "      <td>2501</td>\n",
              "      <td>30.9</td>\n",
              "      <td>46.01667</td>\n",
              "      <td>(30.900000, 46.016670)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        name     id  ...   reclong             GeoLocation\n",
              "30679  Northwest Africa 7701  57150  ...   0.00000    (0.000000, 0.000000)\n",
              "38188                     Ur  24125  ...  46.01667  (30.900000, 46.016670)\n",
              "\n",
              "[2 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "29qhX6eNBBDw"
      },
      "source": [
        "#Dataset has rows which are >2016 but it is in BCE (Before Common Era), though it is not correct still it is abnormailty in our dataset\n",
        "data.drop(data[data['year']>2016].index, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N5ZfnEn5BEaD",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 48
        },
        "outputId": "db723f2a-09a4-4a71-e6fa-2be78bd8bb0c"
      },
      "source": [
        "#Assuring\n",
        "data[data['year']>2016]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [name, id, nametype, recclass, mass, fall, year, reclat, reclong, GeoLocation]\n",
              "Index: []"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LsrZ3ryVOY0a"
      },
      "source": [
        "***Checking for Null Values***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CrifqwIXOTb6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "outputId": "a8927010-d518-42b5-8509-707cd02d7fef"
      },
      "source": [
        "data.isnull()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>16356</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38301</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>703</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>678</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>278</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</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>38128</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38201</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38224</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38328</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45700</th>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>True</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "      <td>False</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>45714 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        name     id  nametype  recclass  ...   year  reclat  reclong  GeoLocation\n",
              "16356  False  False     False     False  ...  False   False    False        False\n",
              "38301  False  False     False     False  ...  False   False    False        False\n",
              "703    False  False     False     False  ...  False   False    False        False\n",
              "678    False  False     False     False  ...  False   False    False        False\n",
              "278    False  False     False     False  ...  False   False    False        False\n",
              "...      ...    ...       ...       ...  ...    ...     ...      ...          ...\n",
              "38128  False  False     False     False  ...   True   False    False        False\n",
              "38201  False  False     False     False  ...   True   False    False        False\n",
              "38224  False  False     False     False  ...   True   False    False        False\n",
              "38328  False  False     False     False  ...   True   False    False        False\n",
              "45700  False  False     False     False  ...   True   False    False        False\n",
              "\n",
              "[45714 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pQCdKkb6Olrl",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7aedb3e5-1ce5-44f5-b4f5-3e57f7b682f3"
      },
      "source": [
        "data.isnull().any()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name           False\n",
              "id             False\n",
              "nametype       False\n",
              "recclass       False\n",
              "mass            True\n",
              "fall           False\n",
              "year            True\n",
              "reclat          True\n",
              "reclong         True\n",
              "GeoLocation     True\n",
              "dtype: bool"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u7TWU7o1PL6O"
      },
      "source": [
        "***Counting Null Values in each column***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "us-WMJWXOpwj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0c5ed134-5ba3-478a-a238-07fdbef15b5b"
      },
      "source": [
        "#Count of null values\n",
        "data.isnull().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name              0\n",
              "id                0\n",
              "nametype          0\n",
              "recclass          0\n",
              "mass            130\n",
              "fall              0\n",
              "year            288\n",
              "reclat         7315\n",
              "reclong        7315\n",
              "GeoLocation    7315\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2-divFjzdrAo"
      },
      "source": [
        "***Removing Null values from the Dataset***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "frwayCuvk5Pq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3ca4c9eb-dc81-4ccd-b41a-63b37bae9b89"
      },
      "source": [
        "#Dataset count row-wise for each column before removing null values\n",
        "data.count()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name           45714\n",
              "id             45714\n",
              "nametype       45714\n",
              "recclass       45714\n",
              "mass           45584\n",
              "fall           45714\n",
              "year           45426\n",
              "reclat         38399\n",
              "reclong        38399\n",
              "GeoLocation    38399\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BywpdnRYdqTn"
      },
      "source": [
        "#Dropping null values from the Dataset\n",
        "data.dropna(inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5lrOdE8-PY-m",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8d33a362-6151-4b6f-9977-09c73b57bc89"
      },
      "source": [
        "#Count of null values after dropping null values\n",
        "data.isnull().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name           0\n",
              "id             0\n",
              "nametype       0\n",
              "recclass       0\n",
              "mass           0\n",
              "fall           0\n",
              "year           0\n",
              "reclat         0\n",
              "reclong        0\n",
              "GeoLocation    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5TozcvD4kyEM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "26a43244-e56e-4c6c-fed7-4558db8e6b28"
      },
      "source": [
        "#Dataset count row-wise for each column after removing null values\n",
        "data.count()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name           38115\n",
              "id             38115\n",
              "nametype       38115\n",
              "recclass       38115\n",
              "mass           38115\n",
              "fall           38115\n",
              "year           38115\n",
              "reclat         38115\n",
              "reclong        38115\n",
              "GeoLocation    38115\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-KL-2OHfKIcr"
      },
      "source": [
        "***Dropping rows where mass is zero***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wE49cl-SKKxE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "51d08a5a-88ad-4090-a5d9-db9545a4b594"
      },
      "source": [
        "#Counting rows where mass is zero before dropping\n",
        "data[data['mass']==0].count()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name           19\n",
              "id             19\n",
              "nametype       19\n",
              "recclass       19\n",
              "mass           19\n",
              "fall           19\n",
              "year           19\n",
              "reclat         19\n",
              "reclong        19\n",
              "GeoLocation    19\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "46mNz5vZKiQo"
      },
      "source": [
        "#Dropping rows where mass is zero\n",
        "data.drop(data[data['mass']==0].index, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KAwCTvefK2EC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "728337f7-5da3-477a-d88b-42db23558cb1"
      },
      "source": [
        "#Counting rows where mass is zero after dropping\n",
        "data[data['mass']==0].count()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name           0\n",
              "id             0\n",
              "nametype       0\n",
              "recclass       0\n",
              "mass           0\n",
              "fall           0\n",
              "year           0\n",
              "reclat         0\n",
              "reclong        0\n",
              "GeoLocation    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B9O29lmePlHI"
      },
      "source": [
        "***Checking for GeoLocation Coordinates***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "724Nq--QPw2K",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "outputId": "69efa2ac-4c2f-4f35-cb6a-980675df4fce"
      },
      "source": [
        "#Checking GeoLocations\n",
        "print(data[data['GeoLocation']=='(0.000000, 0.000000)'].count())\n",
        "data[data['GeoLocation']=='(0.000000, 0.000000)']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "name           6184\n",
            "id             6184\n",
            "nametype       6184\n",
            "recclass       6184\n",
            "mass           6184\n",
            "fall           6184\n",
            "year           6184\n",
            "reclat         6184\n",
            "reclong        6184\n",
            "GeoLocation    6184\n",
            "dtype: int64\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>26374</th>\n",
              "      <td>New York</td>\n",
              "      <td>55760</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron, IIIAB</td>\n",
              "      <td>2950.00</td>\n",
              "      <td>Found</td>\n",
              "      <td>1965</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>(0.000000, 0.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44893</th>\n",
              "      <td>Yamato 983064</td>\n",
              "      <td>39686</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L6</td>\n",
              "      <td>40.94</td>\n",
              "      <td>Found</td>\n",
              "      <td>1998</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>(0.000000, 0.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44892</th>\n",
              "      <td>Yamato 983063</td>\n",
              "      <td>39685</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL3</td>\n",
              "      <td>3.38</td>\n",
              "      <td>Found</td>\n",
              "      <td>1998</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>(0.000000, 0.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44891</th>\n",
              "      <td>Yamato 983056</td>\n",
              "      <td>39678</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H5</td>\n",
              "      <td>362.40</td>\n",
              "      <td>Found</td>\n",
              "      <td>1998</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>(0.000000, 0.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45095</th>\n",
              "      <td>Yamato 983366</td>\n",
              "      <td>39988</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Eucrite-unbr</td>\n",
              "      <td>138.90</td>\n",
              "      <td>Found</td>\n",
              "      <td>1998</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>(0.000000, 0.000000)</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>30773</th>\n",
              "      <td>Northwest Africa 7857</td>\n",
              "      <td>57422</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL6</td>\n",
              "      <td>246.00</td>\n",
              "      <td>Found</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>(0.000000, 0.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30774</th>\n",
              "      <td>Northwest Africa 7858</td>\n",
              "      <td>57423</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H4</td>\n",
              "      <td>459.00</td>\n",
              "      <td>Found</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>(0.000000, 0.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30776</th>\n",
              "      <td>Northwest Africa 7861</td>\n",
              "      <td>57425</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L5</td>\n",
              "      <td>611.00</td>\n",
              "      <td>Found</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>(0.000000, 0.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30777</th>\n",
              "      <td>Northwest Africa 7862</td>\n",
              "      <td>57426</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L4/5</td>\n",
              "      <td>317.00</td>\n",
              "      <td>Found</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>(0.000000, 0.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30759</th>\n",
              "      <td>Northwest Africa 7812</td>\n",
              "      <td>57258</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Angrite</td>\n",
              "      <td>46.20</td>\n",
              "      <td>Found</td>\n",
              "      <td>2013</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>(0.000000, 0.000000)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>6184 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                        name     id  ... reclong           GeoLocation\n",
              "26374               New York  55760  ...     0.0  (0.000000, 0.000000)\n",
              "44893          Yamato 983064  39686  ...     0.0  (0.000000, 0.000000)\n",
              "44892          Yamato 983063  39685  ...     0.0  (0.000000, 0.000000)\n",
              "44891          Yamato 983056  39678  ...     0.0  (0.000000, 0.000000)\n",
              "45095          Yamato 983366  39988  ...     0.0  (0.000000, 0.000000)\n",
              "...                      ...    ...  ...     ...                   ...\n",
              "30773  Northwest Africa 7857  57422  ...     0.0  (0.000000, 0.000000)\n",
              "30774  Northwest Africa 7858  57423  ...     0.0  (0.000000, 0.000000)\n",
              "30776  Northwest Africa 7861  57425  ...     0.0  (0.000000, 0.000000)\n",
              "30777  Northwest Africa 7862  57426  ...     0.0  (0.000000, 0.000000)\n",
              "30759  Northwest Africa 7812  57258  ...     0.0  (0.000000, 0.000000)\n",
              "\n",
              "[6184 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0aojH_yfSaT-"
      },
      "source": [
        "#Dropping abnormal GeoLocations\n",
        "data.drop(data[data['GeoLocation']=='(0.000000, 0.000000)'].index, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iEsOytCbSoV0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "outputId": "9453814a-814f-4501-dadf-e46b10217374"
      },
      "source": [
        "#Assuring\n",
        "print(data[data['GeoLocation']=='(0.000000, 0.000000)'].count())\n",
        "data[data['GeoLocation']=='(0.000000, 0.000000)']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "name           0\n",
            "id             0\n",
            "nametype       0\n",
            "recclass       0\n",
            "mass           0\n",
            "fall           0\n",
            "year           0\n",
            "reclat         0\n",
            "reclong        0\n",
            "GeoLocation    0\n",
            "dtype: int64\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [name, id, nametype, recclass, mass, fall, year, reclat, reclong, GeoLocation]\n",
              "Index: []"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3e42rb19GcK2"
      },
      "source": [
        "***Reset Index after removing Null values, Zero Mass Rows, Invalid GeoLocations***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4txjy8zYGio6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0d606a60-3514-4df7-cb8c-e6f9e7e116f0"
      },
      "source": [
        "#Displaying index of Dataset before reindexing\n",
        "data.index"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Int64Index([38301,   703,   278,   852,   283,  5329,   174, 26166,   410,\n",
              "              956,\n",
              "            ...\n",
              "              965,  3403,  5371,    86, 17387, 17386, 37733, 36403, 30514,\n",
              "              194],\n",
              "           dtype='int64', length=31912)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K5va6iBg-rtd"
      },
      "source": [
        "#Reset index of Dataset\n",
        "data.reset_index(inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9_AEzEmt_k5O",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f26a7e8b-e05e-4df7-a465-4aabf51adadb"
      },
      "source": [
        "#Displaying index of Dataset after reindexing\n",
        "data.index"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RangeIndex(start=0, stop=31912, step=1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cuI71dLKMNDV"
      },
      "source": [
        "#Deleting previous index row\n",
        "del data['index']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LAIq6SMkImeB",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "outputId": "a49ee9b6-e020-4108-c1e3-01f83a6d9ae6"
      },
      "source": [
        "data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Wietrzno-Bobrka</td>\n",
              "      <td>24259</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron</td>\n",
              "      <td>376.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>601</td>\n",
              "      <td>49.41667</td>\n",
              "      <td>21.70000</td>\n",
              "      <td>(49.416670, 21.700000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Nogata</td>\n",
              "      <td>16988</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L6</td>\n",
              "      <td>472.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>860</td>\n",
              "      <td>33.72500</td>\n",
              "      <td>130.75000</td>\n",
              "      <td>(33.725000, 130.750000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Elbogen</td>\n",
              "      <td>7823</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron, IID</td>\n",
              "      <td>107000.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1399</td>\n",
              "      <td>50.18333</td>\n",
              "      <td>12.73333</td>\n",
              "      <td>(50.183330, 12.733330)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Rivolta de Bassi</td>\n",
              "      <td>22614</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Stone-uncl</td>\n",
              "      <td>103.3</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1490</td>\n",
              "      <td>45.48333</td>\n",
              "      <td>9.51667</td>\n",
              "      <td>(45.483330, 9.516670)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Ensisheim</td>\n",
              "      <td>10039</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL6</td>\n",
              "      <td>127000.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1491</td>\n",
              "      <td>47.86667</td>\n",
              "      <td>7.35000</td>\n",
              "      <td>(47.866670, 7.350000)</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>31907</th>\n",
              "      <td>Ksar Ghilane 010</td>\n",
              "      <td>55605</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L5</td>\n",
              "      <td>50.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>32.80600</td>\n",
              "      <td>9.83300</td>\n",
              "      <td>(32.806000, 9.833000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31908</th>\n",
              "      <td>Stewart Valley 012</td>\n",
              "      <td>55528</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H6</td>\n",
              "      <td>130.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>36.23500</td>\n",
              "      <td>-116.18358</td>\n",
              "      <td>(36.235000, -116.183580)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31909</th>\n",
              "      <td>Rosamond</td>\n",
              "      <td>57434</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL3</td>\n",
              "      <td>11.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>34.82793</td>\n",
              "      <td>-118.14640</td>\n",
              "      <td>(34.827930, -118.146400)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31910</th>\n",
              "      <td>Northwest Africa 7496</td>\n",
              "      <td>56314</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Eucrite-pmict</td>\n",
              "      <td>788.4</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>22.94781</td>\n",
              "      <td>-13.38527</td>\n",
              "      <td>(22.947810, -13.385270)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31911</th>\n",
              "      <td>Chelyabinsk</td>\n",
              "      <td>57165</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL5</td>\n",
              "      <td>100000.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>2013</td>\n",
              "      <td>54.81667</td>\n",
              "      <td>61.11667</td>\n",
              "      <td>(54.816670, 61.116670)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>31912 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                        name     id  ...    reclong               GeoLocation\n",
              "0            Wietrzno-Bobrka  24259  ...   21.70000    (49.416670, 21.700000)\n",
              "1                     Nogata  16988  ...  130.75000   (33.725000, 130.750000)\n",
              "2                    Elbogen   7823  ...   12.73333    (50.183330, 12.733330)\n",
              "3           Rivolta de Bassi  22614  ...    9.51667     (45.483330, 9.516670)\n",
              "4                  Ensisheim  10039  ...    7.35000     (47.866670, 7.350000)\n",
              "...                      ...    ...  ...        ...                       ...\n",
              "31907       Ksar Ghilane 010  55605  ...    9.83300     (32.806000, 9.833000)\n",
              "31908     Stewart Valley 012  55528  ... -116.18358  (36.235000, -116.183580)\n",
              "31909               Rosamond  57434  ... -118.14640  (34.827930, -118.146400)\n",
              "31910  Northwest Africa 7496  56314  ...  -13.38527   (22.947810, -13.385270)\n",
              "31911            Chelyabinsk  57165  ...   61.11667    (54.816670, 61.116670)\n",
              "\n",
              "[31912 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DLezBrrAUHcO"
      },
      "source": [
        "***Mean, Median, Mode, Std. Deviation of Mass***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5I8cAW7OUG89",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d1dc24fe-313a-43a0-ffbf-8c4969f8b673"
      },
      "source": [
        "#Mean\n",
        "data['mass'].mean()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "18552.775309444856"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CVu-AgxZaxHH",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "82435983-63aa-4171-faeb-5cccdaac6505"
      },
      "source": [
        "#Median\n",
        "data['mass'].median()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "29.685000000000002"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RMxwN6opeePi",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6100d1c6-d215-46b9-d76f-a1e50c176e5f"
      },
      "source": [
        "#Mode\n",
        "data['mass'].mode()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    1.3\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "flFPNNX4a5kk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e7f39b14-3e48-4b7c-9659-2cf228e9f44f"
      },
      "source": [
        "#Standard Deviation\n",
        "data['mass'].std()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "687032.3021663561"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f6iMUpOTb_y_"
      },
      "source": [
        "***Correlation, Covariance***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "x7mmtJ4ma947",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bed078b9-ef9f-44b2-911f-e5196d3341bd"
      },
      "source": [
        "#Correaltion between mass and year\n",
        "data['mass'].corr(data['year'].astype('float'))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-0.1190632136920269"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aEbzPyNGd57n",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "91748f9e-435c-48bd-d8d2-6b9c5e8bf752"
      },
      "source": [
        "#Covariance between mass and year\n",
        "data['mass'].cov(data['year'].astype('float'))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-2276223.2176983864"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_e8AaRvU3jbW"
      },
      "source": [
        " ***Type of Meteorite*** (Should not be confused with Classification)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mW9GmX7_mDu6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5df3d626-8a78-4970-ed84-7a92ee7371a4"
      },
      "source": [
        "data['nametype'].unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Valid', 'Relict'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YS_sfIcV8aAH",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7e34c4c6-5e13-42ad-e36a-2d48cb3bd458"
      },
      "source": [
        "#Counting based on types of Meteorites\n",
        "data['nametype'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Valid     31909\n",
              "Relict        3\n",
              "Name: nametype, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QPjIVSJofmSv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 368
        },
        "outputId": "4af4ea3c-46b6-4736-a3d5-24018638ac33"
      },
      "source": [
        "#Plotting Histogram Plot for 'Nametype' Column\n",
        "fig = plt.figure(figsize=(10,5))\n",
        "sns.histplot(data=data['nametype'],color='b').set_title('Count of different type of Meteorites')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Count of different type of Meteorites')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pJGuVkVkfZyM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 500
        },
        "outputId": "335bcce8-7326-4503-ad8f-02c0d77bca31"
      },
      "source": [
        "#Plotting Piechart for 'Nametype' Column\n",
        "fig=plt.figure(figsize=(10,5))\n",
        "ax=fig.add_axes([0,0,1,1])\n",
        "ax.pie(data['nametype'].value_counts(),labels=data['nametype'].unique(),autopct='%0.2f%%',shadow=True,colors=['r','b'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "([<matplotlib.patches.Wedge at 0x7f4e261d4da0>,\n",
              "  <matplotlib.patches.Wedge at 0x7f4e261df940>],\n",
              " [Text(-1.0999999520392434, 0.0003248286662686357, 'Valid'),\n",
              "  Text(1.0999999520514863, -0.00032478720397173923, 'Relict')],\n",
              " [Text(-0.5999999738395873, 0.0001771792725101649, '99.99%'),\n",
              "  Text(0.5999999738462652, -0.00017715665671185773, '0.01%')])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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df4CKeNUuIslRFbqAQug0QM3sITM7sd22y8zsVzt4/T/M7JDo47+Y2cAOXnOlmX25G7W26eaxMg//a4H9gXcAP422zQOOAN4JnAas24V9O9v/UeAA4BDg1WhbPTCVvKOlyC64D792+gTgBx18vgk4O/r8YcAb0fZVwHvxf6yXtHv9+/Hv61/mbb8IeKaAdZdIj8LfzFrMbK6ZPW9m93SUk+1evzUzzew7ZnZ8J6890MxO7kodOwvQ6cC0dtumRds75Zw72TlX35Uiuqgy/0k5t/yfB24AnsIH9r3AAuAC/B/Sv4DTgR/twr50sv9/A3/BHyj+J9r2XeD/Uca/JClbLcDngL8CL+L/2F9s95rf4GdfLAC+CPxntL038F/Aj9u9fiZwFPAccHO0bV70vWJ4a6yetvw3OucOdM7tD6zG/7q7xDn3TefcA5285ECgIOE/AzjFzGoAzGw8/gKHc8zsaTN7wcy+3dGOZvaGmQ2NPr7CzOab2SP4BkV3tKm1nFv+L+FbQ33x75JjgDuB+cDR0WtOAO7YhX3pZP9q/N1tGqOPXwMWAccW6OeRdHkK36LfE6jBt/bubveau4GPRx+fCfwdPxjXDx/yvdu9Pvce3RK9DuAb+ANFDBVyvPFxYDSAme1lZveZ2Rwze9jMJrV/sZndaGZnRh9PMbPHzGyemT1lZgOA7wBnR2cWZ3f2jTsNUOfcavx74aRo0zTgj8AVzrlD8L0Nx5jZATv6GmY2Odovd0Sa0tn37MTWlr/5wst2Rc/9gYfxp8CN+Fb5Inw3Tu6P6PZoW1f3pZP9vwacB3wff6p9Bb7lL9IdbwO75z0fE23b0Wuq8PdTXdXJ1zwB3zV0OPAFIItv8cf0UtmC9PmbWSXwPvyvA+B64PPOucnAl2nbQ9Z+3xrgNuBS59y7gOOBDcA3gduiM4vbOvv+Xfkhcl0/d0f/ng+cZWYXRfuPBPbDn9F15D3AXc65xqjo7A5etzMVRIFfVcatfoB98afBU/EtoQPxR67f4t/4/wVk8K2qru5LJ/sfCDwRfTwL/x/i8H2y1fhuoeGF+uFSwHWy3XXQ5nCY62h73uc73LyjfXb0fTrbZ0ffx3VjnwaaaaK1op5eLf75lopNtFruucNoobGqnt7N/aI/xRY2VK+h72aLnq9jS0UjLRWr6N2c2+e66OtvwfFhGqtvpu+Wi2mqfItWO4ualpOobjNE1cnvp5Pf3Q5/1g736eR33WYfBxVV2OYqf/LS1MO/pz5mNhff4n8JuN/8MtFHArebba2nVydfYyKwxDk32xfq1gHk7btTXQn/u4GfmNnB+N6I1fij0hTn3Bozu5Htz/KKYWvgux3/fZaN86MH+L73McAk4G/RtvnAn3dhX7qwv8O3+G8FPg9cjW9tXQdc1b0fI5V29OezNQa247pzFlq2Z64T8S2+gTRXgJ88sFfec4CxwHoaqwcBzfj7qk5gQ03uh+qPD4shbNmujXMtfvxqAetrRuGbt8fRXPHx9i8sP7mc29TDr7PROXegmfXFD4d8DrgRqHfOHdjDr91lO21BO+cagIfwDc/p+P/XDcBaMxvOti6hHZkFfNDM+phZHX6iSo9qbQZX7um/PPr3TXyf/UfytrXiQ/rTu7Bv/vYd7f97fL/aYHyXUUX0aOzuDyGpNAU/a+x1/BWVt+LPNPNlgJuij2cAx9G1o9ka/CSG89j2HjVgY4+rLqkthfgiUW/IF4Av4X8dr5vZhwHMe1cnu78CjDSzKdHr68ysClhPF1c/6Gr3yXTgXcB059w84FngZeAW/EzDHXLOPYPvm5qHn0Awu4vfs6Nat76/XJnPYjwD3xd2GvAL/KXJ04F98C34UcAno9cupu3wfEf70sn+4N85N7Jt2sB/RF/zMnZ8kBHpSBXwc+BEfDfkWfjxpm+yrXP6fHwf/wTgGtpOBx2Pf//diD9rzZ8p9B38mFRF9PUfxk9d/lgxfpDiaS7UF3LOPYvvMj8H+ChwvpnNA14APtDJfpvxPbs/i15/P/7M5CFgv64M+Jor+za0l/EDx58lGue8E66oSsjFFiISK8txLvbDaGU9cNpOu8Gg8m75i0hiFazlH1Lcwt/lPVH4i0gICv8Sa8l/opa/iARSkAHf0OIU/m3Cvil2EwREJCHWhi6gEGIb/hv8lCYRkVJbHLqAQoht+Df460pEREptSegCCiFO4d+mm2edWv4iEobCv8TWk3eR11q1/EUkDHX7lFgDeeG/Wi1/EQlDLf9SyjrXjF9TqBpghVr+IhKGWv4BrCFayXipWv4iEoZa/gGsJlrjepHCX0RKrxVYFrqIQohb+K8gavmvgqbmhFxmLSKxsQLfBR17sQ1/gEa1/kWktBLR5QPxC/91+U8aNegrIqWViMFeiF/4rydvZc8GtfxFpLTU8g+kgbzw11W+IlJiCv9A2oT9ElgZqhARSaX5oQsolLiFfwNQmXvyUoKOwiISC3NCF1AosQr/rL9p8Uaie/c+Dct0Ry8RKZENwMuhiyiUWIV/ZBHQD6ARmtf46Z8iIsU2F+cS09iMY/i/DNTlnixN0NQrESlrienygXiG/xvk1b1Q/f4iUhoK/8CWkDfdU4O+IlIiCv/AVgAtRLN+5sDS1ryDgYhIESRqsBdiGP5Z51rwXT+1AA3QXK9BXxEprrn47EmM2IV/RIO+IlJKierygfiG/xto0FdESkfhXybaD/qq5S8ixaTwLxPL8Vf25gZ9l2nQV0SKpJGEDfZCTMO//aDvetiiQV8RKZLEDfZCTMM/8jJR+AP8G14LWIuIJNcDoQsohjiH/xvkrfD5BLwSrhQRSbB7QhdQDHEO/zaDvA/Boia/4qeISKG8TQIHeyHe4b8Mf0/f3gBboPUNWBC0IhFJmntxLpGTSWIb/lm/tOrjwODctmfV9SMihZUNXUCxxDb8I/OIbuwCcB8saNHNXUSkMDYAfw9dRLHEPfz/DTQTHQBWQ9MSWBi2JBFJiPtxril0EcUS6/CPbus4l7yun+fV9SMihZHYLh+IefhHniIa9AV4UOEvIj3XCtwbuohiSkL4z4/+NYCXoX61X/5BRKS7nsC5RK8aEPvwzzq3Dt/3PyC3bf62A4KISHckussHEhD+kceA/rknj6rrR0R6JpFX9eZLSvi/RNTtA/AwvL3RT9MSEdlVC3DuxdBFFFtSwn8psAroC9AK7lV/QBAR2VV3hi6gFBIR/ll/+fXjwKDctr/CM+EqEpEY+23oAkohEeEfeY68VT4fhSUr/RmBiEhXzcK5VIwZJin8X8f382+d8/9kQlfjE5GiuT50AaWSmPDPOteMv+nCbrltt8O/mmFLuKpEJEbWAHeELqJUEhP+kSfwP5OBX+tnPrwQtiQRiYmbcW5T6CJKJVHhn3VuGX6Wz9a1fu5T14+IdM0NoQsopUSFf+QB8u7t+w94SwO/IrITs3Du+dBFlFISw/95/O0ca3IbZvnuIBGRHbk2dAGllrjwj5Z5fhAYltt2GzyvK35FZAcWAneHLqLUEhf+kUfIG/jdCC3PqO9fRDr2c5xrCV1EqSUy/LPOLcVf9LV12uetMFu3eBSRfM73CPw6dB0hJDL8IzOBPrknC6FhgaZ9ikgeg5twrj50HSEkOfxfAZYBdbkNd8JjLlw9IlJGHLSQwoHenMSGf9a5Vvya3Fvn/D8OS9X6FxEAgxtxLrU3fkps+EfmAJvIm/b5O3iwVX3/IqnmfC5cGbqOkBId/ll/qfZ9wIjctudh9fNa7lkk1Qx+hnNvha4jpESHf+TvQBN5q33eAP/Ugm8i6dQK64Dvh64jtMSHf9a5BvydeYbnti2Ehtm66lcklSrg+zi3JnQdoSU+/COz8Ef7frkN18OjTX4ZCBFJiVa/zldqZ/jkS0X4Z51rAm4j76KvVdD0iL8SWERSogK+hXNq9JGS8I88hZ/3PyC34QZ4qsGfEYhIwrXCAlJyf96uSE34R3f6mk7eTd4bofkB+EewokSkZCrga/gcEFIU/pHngH8DQ3Ibfg9z62FluJJEpNhaYQ7OzQhdRzlJVfhHV/3eBvQnWvGzGdw9fjqoiCRUBVweuoZyk6rwj8wH5pG33v/t8PIySPUFHyJJ1Qr349yDoesoN6kL/6xzDrgDv+Ln1p//BrhXSz6LJEsrNFXAJaHrKEepC3+ArHMLgcfIW/bhKVj2KPwzXFUiUmgOrkjz4m2dSWX4R+4GqoDq3IZr4ZGVsCRcSSJSKI3wTCX8JHQd5Sq14Z91bhlwFzA6t20LtP4K/qTuH5F4a4Yt1TANP8lDOpDa8I/cBywChuY2zIbl6v4RibcN8K1q514NXUc5S3X4Z53bAtyAX/NH3T8iCdAAcwfAD0LXUe5SHf4AWefexK/62VH3T0u4ykRkVzXD5l5wJn5Wn3Qi9eEfuQ94k+27f2aFK0lEdtUG+Ga1c6+FriMOFP5s7f75NR10/6xQ949ILDTAswPg6tB1xIXCPxJ1/9yBun9EYkfdPbtO4d/WTNp1/zwNyx/R7B+RsrYBvl7t3L9D1xEnCv88ed0/fcnr/rkOHl0ObwcrTER2aD3MHgA/Dl1H3Cj829nR7J+r4LZGaAhXmYi0twFWV8Mp6u7ZdQr/js0EFpLX/fM6rP8l3Kr+f5HysAW2LIJMb+dWhK4ljhT+Hcjr/ukD9M5tnwVv/wnuCVaYiADggGfhiknOPRq6lrhS+O9A1rlFwG+AUUBlbvtNMG82PB6sMBHhOZjxXfXz94jCv3OPA/cCY/M3XgX3L/Q3gxaREnsd5t0I52TVz98jCv9ORG+uO4G55A0At4K7EmbUw6pQtYmk0QpY/iBM/YluxN5jCv+dyPo32Q34oN86ALwKmn4M05tgU7DiRFKkETY+Dqec79zy0LUkgcK/C7LONQDX4m/+Upvb/hys+j3MaPXjTyJSJM3Q+gRcnHHu6dC1JIXCv4uyzi0BfoZv/W+9AOweeO1BuD9YYSIpMAd+epxzN4euI0kU/rsg69wLwC3A7oDltl8Hj78I84IVJpJgL8EDV8GXQ9eRNAr/XXc/8A/azQD6NtyzxK8LJCIFsghenQEZzewpPIX/LorehH8AXgNG5LZvhJavwh+0BpBIYSyCt6fDsd9wbmPoWpJI4d8NWeeagF/gZ/oMzG1fA5u/Cv+7EpYGK04kAd6C5b+GEy93bnHoWpJK4d9NWefW4GcA9SNvBtBK2HQF3LwaNB1NpBsWw6qfwrRv+zE2KRKFfw9knXsduAYYhD8IALAEGr8Bv9dFYCK7ZhmsuQY+9WPnHgpdS9Ip/Hso69xLwE/wU0D75rYvgg3fgpvWwepgxYnEyAqovwYunq/FE0tC4V8AWeeeB64DhuFXAgX8MtBfhxvrYWWw4kRiYCmsuRo+9xLM0Mye0jD9ngsnYzYF+Bz+pu9Nue1joN934bzB/uAgInnehpU/hC++AX9Q8JeOwr/AMmZHAhfjDwBb1/0ZAX2+Bx8bCiODFSdSZhbB8qvgK4vhZgV/aSn8iyBjdjjwaWAZsHWO8lDo/QM4d1jeCqEiafU6LP0ufGkFTFfwl57Cv0gyZocAl+CnfDbmtg+Cmu/BtNGwR7DiRAKbD29/Hy5bBXco+MNQ+BdRxuxdwKX4KZ8bcturoeIb8P4DYUqw4kQCmQUv/hQub4a/KPjDUfgXWcZsf+CLwBqgIf9zF8Hkk+DkSs26khRohuZb4MkZcCXwdwV/WAr/EsiYTcIfADbT7sKvE2DchXBW77xrBESSZgM0XAOzZsPVWef+GboeUfiXTMZsDHAZ0B9os17JRBj4NZg2GIYHKU6kiJbC8u/A397ywf+v0PWIp/AvoYxZf/wsoP3wyz+35j7XH6q/DafvBfuGqk+k0J6DBd+DbCNck3VOK96WEYV/iWXMqoGzgBPxyz9vvRjMgMvh2CPhGNvB/iJx0AruL/DM9TAduD7r3PrQNUlbCv8AMmYGHAN8HL/2T5s/jLNhv7Phg1V5t4sUiYsmaLoeHr0fbsAv19AcuibZnsI/oIzZROAL+EZ/myWgD4cRX4BptTAgSHEi3VAP9d+Dh16G/wYe04ye8qXwDyxjNgx/ABgJvAVs/Q8ZA/2+Bh/aHfYMVZ9IV70KC6+CmavhR1nnFoSuRzqn8IfOCRoAAAgVSURBVC8DGbO+wKfwF30tAtqcJl8Ik0+EqTVQE6I+kc40waYZMPs2eBD4edY5rWIbAwr/MpExqwROAz6EXxSuzX1L94EBl0FmjM4CpIy8AQt+CHPfhgeAm7LObdrZPlIeFP5lJloW+kL8NNDt7gV8ERxyIpxQrbMACagJNt0FD9/ir1m5Hfhr1rnWne0n5UPhX4aicYBPAO/A/3E15X9+Igy8DDJaHE5CeAMWXA3PvAVv4Kdxvha4JOkGhX+ZyphVAEcDH8WPASzL/7zhzwKm6ixASmQzNN0Fs/7gGyT3AvdknWva2X5SnhT+ZW5nZwGT/FnAB0bB+NJXJ2mx0Pftz3kLFqLWfiIo/GMgGgw+GvgI0EK7sQADLoYpJ/izAF0YJgWzGZr+BA//b9vWvgZ1E0DhHyMZs+HAJ/Hr/2x3FrAvDLoQjp/g1w4S6TYHzIcXroMXFvm+/Rs0dz9ZFP4xk3cWkBsL2G5G0NEw+hw4frS6gqQb3oQFv4On5vj3l1r7CaXwj6noLOBTwCQ6OAsAOA32Oh2OHwojSl2fxM9yePs2eOh+H/rLUWs/0RT+MRadBRyDXyW0Gn8WsCX/NQZ8BPY/CY7rD4NKX6WUu3pYmYUHZ8BaoAr4C3CvWvvJpvBPgIxZHTAVOAnfXbsUPzC8VQ1UfAomvxeO6QP9ApQpZWYDrLsf/nkTLG6B3sCjwN1Z55bvbF+JP4V/gmTMhgCnAsfibxm5lLyF4sDfNOYiOOJwOLIGepW+SgmtCTY+Ao9cDws2+tuHPodfevnN0LVJ6Sj8EyhjNgo4Hb9Q3AZgRfvXjIS+F8F7DoQplVBZ6hql9Jphy9Pw5K/guTX+7O814DbgVS29nD4K/wTLmO2JHw+YhO/PXdP+NeOgdhpMORgmqzsomRqh4WmYfQu8tNj/Hy/F32HrX1qPJ70U/gkX3TVsP+AcYHdgJe3uHAbQByqnwTuPhsOGaHZQIiyHt/8BT/4RXtsMu+EbALcBs3V3LVH4p0Q0M+gg/EFgMB3cPjLnBBh3Mhy2B0ysgIoSlik91AKtr8GL98CT//QH+uHAJmAG8IjW4pEchX/KZMxqgEOADD4YNuLHBLZ7I4yHujPgwIPh4DoYWNJCZZeshVVPwzN3wLy3/EJ/A/AH9z8DD2ed2xC2Qik3Cv+UilYNnQicCLwLPzV0Ge2uEwB/rcDJsOf7YPIeMKlSZwNloRmaX4OX7oc5f/N3gBuGn8G1ELgHeC7r3Hb/nyKg8BcgYzYCPz30OPzFYmuAdR29dgz0Ox3euT9MGg5jK/yxQUqkFVqXwJvPwUt3wr+W+d//EPy/T+DvqPW6Zu/Izij8ZauMWT/8uMCJwBi23Uegw8HB4dDnRNj7QJg4FvbSdQPF0QSbFsKCZ+GVmbBgpb+GYzf8hVn1wN+AJ7POrQ5aqMSKwl+2E80QGge8J3pU4c8E1tLB2ABAb6h8H4w7FCbuDRNrfZ+zdNM6WPMqvPIkvPJ3eHOLv61nLX6wHuBp4B/AK1nnWnb0dUR2ROEvncqY9QUOAE7A3zbS8BeOraHdEhL5DoXhR8PEfWHiUBilvqHOtYJbDm+9CK/MgvnP+EF4wx9E+0cvWwnMBOZknasPVaskg8JfuixjNhA/SHwo/oBQie8SWkUHq4rmjIPaE2CffWDcCBjVH4akfaygFdxaWLkUlrwMr8+E+YuhEX+WNRjfpQPwKvA48DKwTH35UigKf+mWjFlvYC/8GMFh+CtHHf6MoKGzfQdAzRQYMQlGjYWRST8gtIKrhxVLYcmbPuwXPw1L122bWdUHH/iV+G3P4Lt15med6/BaDJGeUvhLj0XTRscC+wNHAiOjT63HD0judAmBAVBziD8gjBwLo0bAyAEwNG4HhFZorYcVS2DJQlj8MiyZA8vWt51Ca/iunNy4SD2+df8c8G9Nz5RSUPhLQUWDxUPw6wkdge8msujRgj8gNNCFA0J/qD4ERoyBQYOgdiDU9Ye6WqjtC3V9oa7U9yzeDJs3wvoN0NAA69fB+rXQsBrWL4TVT8Oyxrazowy/cmYdfjZUa7TtDeAx4CVgsbpzpNQU/lJUGbMq/JXEI/HdRPvgzxJyF4q1sgsHhPYGQc3uUDcS6oZC7WCoiw4StTVQUwEVeY/K3MfRN27t4NGyCZrWw/r6KNRXQMNiWL/Ih31nrXLDd3/V0jboFwPzgQXRx0t1oxQJTeEvJRcdEIYBo/AziCbhDwiGD+YW/LITTfg57eXWDVKFX0KhBt9fX822KbCLgVfwyyXngl7r6UjZUfhLWcg7IIwE9gRG4wdBB+Fb0q1sC9jcWcPmvEcTPT9IVLMt1HtF/xJ939z3rsQvlLYGvzjeEtoG/eYe1iBSEgp/KXvRgaEW329eF308AH+V61D8QWJwtB3aXojm2DZonP9xjuX9m7t+YVX0WIG/sC3XLbUeaFBLXpJA4S+JES1bXYM/M8g9KvM+zg06t3bw2Kw17iVNFP4iIimkpXlFRFJI4S8ikkIKfxGRFFL4i4ikkMJfRCSFFP4iIimk8BcRSSGFv4hICin8RURSSOEvIpJCCn8RkRRS+IuIpJDCX0QkhRT+IiIppPAXEUkhhb+ISAop/EVEUkjhLyKSQgp/EZEUUviLiKSQwl9EJIUU/iIiKaTwFxFJIYW/iEgKKfxFRFJI4S8ikkIKfxGRFFL4i4ikkMJfRCSFFP4iIimk8BcRSSGFv4hICin8RURSSOEvIpJCCn8RkRRS+IuIpJDCX0QkhRT+IiIp9H9dmYQ9dA2y9AAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "68bK8OTV8mWt"
      },
      "source": [
        "***Classification of Meteorites***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "64dt0Poj8lze",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "69a0e222-ab21-4cf6-dc44-785e28db3d0b"
      },
      "source": [
        "#Showing Unique Classes\n",
        "data['recclass'].unique()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Iron', 'L6', 'Iron, IID', 'Stone-uncl', 'LL6', 'Iron, IAB-MG',\n",
              "       'Iron, IIIAB', 'L', 'H6', 'H', 'Iron, IIAB', 'L5', 'Iron, IVA-an',\n",
              "       'Pallasite, PMG-an', 'H5', 'H3-5', 'L/LL4', 'H4', 'Iron, IAB-sLL',\n",
              "       'Iron, IAB?', 'Iron, IC', 'Iron, ungrouped', 'Iron, IVB', 'LL5',\n",
              "       'LL4', 'Howardite', 'Iron, IAB complex', 'H5-7', 'CI1',\n",
              "       'Eucrite-mmict', 'Pallasite, PMG', 'OC', 'Martian (chassignite)',\n",
              "       'H?', 'L4', 'Iron, IIIE', 'Eucrite-pmict', 'CR2', 'Iron, IVA',\n",
              "       'Pallasite', 'Iron, IAB-ung', 'Aubrite', 'H4/5', 'CM2', 'LL7',\n",
              "       'Mesosiderite-A1', 'Diogenite', 'Iron, IIE-an', 'Pallasite?',\n",
              "       'Iron, IIC', 'H3/4', 'L3.7', 'Iron, IAB-sLH', 'Iron, IIIAB?',\n",
              "       'H/L3.9', 'Iron, IIIF', 'Mesosiderite-A4', 'Mesosiderite-B4',\n",
              "       'CV3', 'LL3.6', 'Iron, IIG', 'Iron, IAB-sHL', 'EL6',\n",
              "       'Martian (shergottite)', 'L/LL5', 'Lodranite', 'Ureilite', 'CO3.4',\n",
              "       'Angrite', 'L/LL6', 'CO3.5', 'Eucrite-cm', 'Iron, IIE', 'CO3.7',\n",
              "       'H/L3.6', 'Mesosiderite-A3/4', 'Pallasite, PES', 'Mesosiderite-B2',\n",
              "       'Iron, IC-an', 'L5-6', 'Iron, IAB-sHH', 'Mesosiderite-A3',\n",
              "       'Iron, IAB-sLM', 'K3', 'EH4', 'H3.7', 'LL3.15', 'H3-4', 'CO3.3',\n",
              "       'EH5', 'Iron, IIIAB-an', 'EH3', 'LL4-6', 'LL3.4', 'Iron, IID-an',\n",
              "       'L3.7-6', 'Iron, IIF', 'L3.6', 'Martian (nakhlite)', 'L3.9', 'LL',\n",
              "       'H3.8', 'Achondrite-ung', 'Mesosiderite?', 'LL3.3',\n",
              "       'Mesosiderite-B1', 'Iron, IAB-an', 'H3.4', 'LL3.8', 'H3',\n",
              "       'Mesosiderite-A', 'CBa', 'L3', 'L5/6', 'Winonaite', 'CK4',\n",
              "       'H3.8-an', 'L3.5', 'L3-6', 'H3-6', 'H3.6', 'R3.8-6', 'H4-an',\n",
              "       'L6/7', 'CO3.2', 'C4-ung', 'H5-6', 'LL3.00', 'LL3-6',\n",
              "       'Mesosiderite', 'EH4/5', 'L3-4', 'Aubrite-an', 'L3.4', 'LL3.2',\n",
              "       'H3.5', 'L4-6', 'Diogenite-pm', 'EH3/4-an', 'Mesosiderite-A2',\n",
              "       'C2-ung', 'CR2-an', 'Lunar (anorth)', 'LL3.1', 'Ureilite-pmict',\n",
              "       'L-imp melt', 'L3.8-an', 'L/LL3.4', 'L/LL4/5', 'H(5?)', 'CK4/5',\n",
              "       'L5-7', 'CO3.8', 'H4-6', 'EL6/7', 'C5/6-ung', 'H4/6',\n",
              "       'Chondrite-ung', 'H5/6', 'H/L4', 'Brachinite', 'LL3.0', 'CK4-an',\n",
              "       'E5', 'LL3', 'Acapulcoite', 'CO3', 'Lodranite-an', 'H-an', 'H4-5',\n",
              "       'R3.8', 'EH', 'CO3.0', 'L4/5', 'H3.2-6', 'LL3.9', 'H7', 'H3.9',\n",
              "       'L3.2', 'L3.8', 'L/LL3', 'L3.7-3.9', 'LL3.7', 'Iron, IIIE-an',\n",
              "       'CO3.6', 'L(?)3', 'LL3.5', 'E3', 'E5-an', 'H(?)4', 'R4', 'H3.3',\n",
              "       'H3.2-an', 'Lunar (bas/anor)', 'C', 'L3.7-4', 'Eucrite',\n",
              "       'Lunar (gabbro)', 'E4', 'EH6-an', 'E', 'L3.5-3.8',\n",
              "       'Mesosiderite-an', 'L3/4', 'LL5/6', 'L3.1', 'Eucrite-unbr',\n",
              "       'H3.2-3.7', 'Eucrite-br', 'L/LL6-an', 'L3.6-4', 'L3.3', 'CV3-an',\n",
              "       'C1/2-ung', 'L3.5-3.7', 'CK5', 'Stone-ung', 'R3.9', 'L7', 'CM1/2',\n",
              "       'LL3.1-3.5', 'CK6', 'EH-imp melt', 'Iron, IIAB-an', 'L3.3-3.7',\n",
              "       'C3-ung', 'L3.4-3.7', 'CM1', 'L3.3-3.6', 'L3.2-3.6', 'LL6(?)',\n",
              "       'Pallasite, ungrouped', 'EH6', 'Acapulcoite/Lodranite', 'LL7(?)',\n",
              "       'Martian (OPX)', 'R3.6', 'EL3', 'CH3', 'H3.5-4', 'Eucrite-Mg rich',\n",
              "       'L3.0-3.9', 'L/LL', 'C4', 'L3.3-3.5', 'L3.5-3.9', 'L3.2-3.5',\n",
              "       'L3.0', 'L3.0-3.7', 'C6', 'E3-an', 'K', 'Chondrite-fusion crust',\n",
              "       'Mesosiderite-B', 'Lunar (basalt)', 'CK5/6', 'E6', 'Ureilite-an',\n",
              "       'H-metal', 'H3.1', 'H3.7-6', 'H3.0', 'EL7', 'LL5-6', 'H3.9/4',\n",
              "       'L3.5-5', 'H3.8/4', 'L/LL5/6', 'H3.10', 'L3.05', 'EH7-an', 'L4-5',\n",
              "       'L3-5', 'LL3.8-6', 'CK3', 'L/LL(?)3', 'H3.9-6', 'L/LL3.10',\n",
              "       'H3.9-5', 'LL4/5', 'H3.8-5', 'H3.6-6', 'R3.8-5', 'R3-6', 'L3.9/4',\n",
              "       'L/LL5-6', 'CK3-an', 'EL5', 'CV2', 'C2', 'LL3.9/4', 'LL5-7',\n",
              "       'H3.2', 'H3-an', 'CBb', 'L4-an', 'EH7', 'EL4', 'LL4-5', 'H4(?)',\n",
              "       'Diogenite-an', 'R3', 'CR1', 'H3.8-4', 'R3.5-6', 'C4/5', 'L/LL3.2',\n",
              "       'L3.10', 'H/L3', 'H/L3.5', 'EL4/5', 'L/LL3-5', 'L/LL3-6', 'H~5',\n",
              "       'H~6', 'L3.9-6', 'L~5', 'H~4', 'H~4/5', 'Lunar (feldsp. breccia)',\n",
              "       'H/L6', 'R3-4', 'H5-an', 'CR', 'Enst achon-ung', 'Lunar', 'L~6',\n",
              "       'LL~6', 'H3.4/3.5', 'H-imp melt', 'E-an', 'L-metal', 'H3.0-3.4',\n",
              "       'Lunar (norite)', 'CR-an', 'LL3/4', 'L(LL)3.05', 'Fusion crust',\n",
              "       'Lunar (bas. breccia)', 'L~3', 'LL(L)3', 'L/LL3.6/3.7', 'LL~5',\n",
              "       'L(LL)3', 'H/L5', 'L3.8-6', 'CM-an', 'H(L)3-an', 'R5',\n",
              "       'H-melt rock', 'Mesosiderite-C2', 'R', 'L/LL~6', 'L-melt rock',\n",
              "       'H/L4-5', 'L~4', 'CH/CBb', 'H5 ', 'L5 ', 'L6 ', 'H4 ', 'H3.8/3.9',\n",
              "       'L(LL)5', 'L(LL)6', 'L4 ', 'H(L)3', 'H/L~4', 'H5-melt breccia',\n",
              "       'H6-melt breccia', 'H3 ', 'LL3-5', 'Mesosiderite-C', 'Eucrite-an',\n",
              "       'L6-melt breccia', 'L/LL4-6', 'H6 ', 'LL6 ', 'LL3.7-6', 'H3.7-5',\n",
              "       'LL~3', 'L-melt breccia', 'H3.7/3.8', 'L3.7/3.8', 'L/LL~5',\n",
              "       'L/LL~4', 'Diogenite-olivine', 'L3.9-5', 'H3.8-6', 'H3.4-5',\n",
              "       'L(LL)3.5-3.7'], dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PI7qLQnM9A2l",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4599661c-ba76-49f4-f9c9-4db8ec9c8a7c"
      },
      "source": [
        "#No. of Meteorites for each Unique Class\n",
        "data['recclass'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "L6           6523\n",
              "H5           5586\n",
              "H4           3324\n",
              "H6           3231\n",
              "L5           2723\n",
              "             ... \n",
              "L3.7/3.8        1\n",
              "LL6(?)          1\n",
              "LL3.1-3.5       1\n",
              "H3.8/3.9        1\n",
              "L3.6-4          1\n",
              "Name: recclass, Length: 390, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KAHN7iZNKd9a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "003fb825-7e96-4c8d-ec7e-f9ebc5fb11ed"
      },
      "source": [
        "#Sample Data from Original Class Data\n",
        "sample_recclass = data.loc[:100,'recclass']\n",
        "sample_recclass.value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "L6                       19\n",
              "Stone-uncl               10\n",
              "H6                        9\n",
              "H5                        9\n",
              "Iron, IIIAB               5\n",
              "Iron, ungrouped           4\n",
              "H4                        4\n",
              "L5                        3\n",
              "L                         3\n",
              "Eucrite-mmict             3\n",
              "Iron, IID                 2\n",
              "Howardite                 2\n",
              "Iron, IVA-an              2\n",
              "LL6                       2\n",
              "Iron                      2\n",
              "Iron, IC                  2\n",
              "H5-7                      1\n",
              "H?                        1\n",
              "LL5                       1\n",
              "H                         1\n",
              "Iron, IIAB                1\n",
              "Iron, IAB complex         1\n",
              "L4                        1\n",
              "LL4                       1\n",
              "Martian (chassignite)     1\n",
              "Iron, IAB-MG              1\n",
              "Iron, IIIE                1\n",
              "OC                        1\n",
              "Iron, IAB?                1\n",
              "Iron, IVB                 1\n",
              "Pallasite, PMG-an         1\n",
              "H3-5                      1\n",
              "L/LL4                     1\n",
              "Iron, IAB-sLL             1\n",
              "CI1                       1\n",
              "Pallasite, PMG            1\n",
              "Name: recclass, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QdLno3FVZ8BZ"
      },
      "source": [
        "***Plotting of Sample Classification Data of Meteorites***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NX19FOLAg6l-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        },
        "outputId": "cc99a62e-4b72-4735-be8b-857063805050"
      },
      "source": [
        "%matplotlib inline\n",
        "fig = plt.figure(figsize=(15,5))\n",
        "ax = fig.add_axes([0,0,1,1])\n",
        "ax.plot(sample_recclass.value_counts(),linewidth=4)\n",
        "ax.set_title('Classification of Meteorites')\n",
        "labels = ax.set_xticklabels(sample_recclass.value_counts().index,rotation=90)\n",
        "ax.set_xlabel('Classifiers')\n",
        "ax.set_ylabel('Counts')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Counts')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TzccBnU5TiDz",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 565
        },
        "outputId": "3260f5c6-0a3f-4dc2-ba20-bf103791e270"
      },
      "source": [
        "#Plotting Histogram from Sample Classification Data\n",
        "fig = plt.figure(figsize=(10,5))\n",
        "recclass_plot = sns.countplot(data=data,x=sample_recclass.value_counts())\n",
        "recclass_plot.set_title('Sample Classification of Meteorites')\n",
        "recclass_plot.set_xticklabels(labels=sample_recclass.value_counts().index,rotation=90)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Text(0, 0, 'L6'),\n",
              " Text(0, 0, 'Stone-uncl'),\n",
              " Text(0, 0, 'H6'),\n",
              " Text(0, 0, 'H5'),\n",
              " Text(0, 0, 'Iron, IIIAB'),\n",
              " Text(0, 0, 'Iron, ungrouped'),\n",
              " Text(0, 0, 'H4'),\n",
              " Text(0, 0, 'L5')]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W2xIUO-uPJNh"
      },
      "source": [
        "***How many Meteorites Fall was observed (fell) and not observed (found)***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y9lDtlSnae6p",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4c1ca050-a2fc-478e-9268-ef7d2c4e67f2"
      },
      "source": [
        "#Count based on Fell and Found\n",
        "data['fall'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Found    30848\n",
              "Fell      1064\n",
              "Name: fall, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qpxSp6mqdsK-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "outputId": "9121c007-bda9-48a8-c221-f529b8fa7c51"
      },
      "source": [
        "#Plotting Histogram on the Categorical data of Column 'fall'\n",
        "sns.histplot(data=data['fall'],color='b',alpha=0.5).set_title('Count of Meteorid Fell Vs Found')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Count of Meteorid Fell Vs Found')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JJ26NElog-d2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 500
        },
        "outputId": "7e46e882-bac6-4180-ced9-79a7dc40d31a"
      },
      "source": [
        "#Plotting Piechart on the data of Column 'fall'\n",
        "fig=plt.figure(figsize=(5,5))\n",
        "ax=fig.add_axes([0,0,1,1])\n",
        "ax.pie(data['fall'].value_counts(),labels=data['fall'].unique(),autopct='%0.2f%%',shadow=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "([<matplotlib.patches.Wedge at 0x7f4e260702e8>,\n",
              "  <matplotlib.patches.Wedge at 0x7f4e26070cf8>],\n",
              " [Text(-1.0939710601874346, 0.11501008422038683, 'Found'),\n",
              "  Text(1.0939710548034227, -0.11501013543286864, 'Fell')],\n",
              " [Text(-0.5967114873749643, 0.06273277321112009, '96.67%'),\n",
              "  Text(0.5967114844382305, -0.06273280114520106, '3.33%')])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Dzr2pFWTMjgQ"
      },
      "source": [
        "***Oldest and Latest Meteorite (fell or found)***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4w8iykL5M5IZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 78
        },
        "outputId": "d0864868-28e8-4d91-f944-632e5cb2b31a"
      },
      "source": [
        "#Latest Meteorite Fell or Found\n",
        "data[data['year']==data['year'].max()]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>31911</th>\n",
              "      <td>Chelyabinsk</td>\n",
              "      <td>57165</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL5</td>\n",
              "      <td>100000.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>2013</td>\n",
              "      <td>54.81667</td>\n",
              "      <td>61.11667</td>\n",
              "      <td>(54.816670, 61.116670)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              name     id nametype  ...    reclat   reclong             GeoLocation\n",
              "31911  Chelyabinsk  57165    Valid  ...  54.81667  61.11667  (54.816670, 61.116670)\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RD9lYkd0Op_B",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 78
        },
        "outputId": "db8b2047-d923-47b5-9f57-16632c892159"
      },
      "source": [
        "#Latest Meteorite Fell (Fall Observed)\n",
        "data[(data['year']==data['year'].max()) & (data['fall']=='Fell')]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>31911</th>\n",
              "      <td>Chelyabinsk</td>\n",
              "      <td>57165</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL5</td>\n",
              "      <td>100000.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>2013</td>\n",
              "      <td>54.81667</td>\n",
              "      <td>61.11667</td>\n",
              "      <td>(54.816670, 61.116670)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              name     id nametype  ...    reclat   reclong             GeoLocation\n",
              "31911  Chelyabinsk  57165    Valid  ...  54.81667  61.11667  (54.816670, 61.116670)\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kG7MuIoLMmzp",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 408
        },
        "outputId": "9ab04b04-8904-460f-bed4-561109dcb04b"
      },
      "source": [
        "#Latest Meteorite Found (Fall not Observed)\n",
        "found = data[data['fall']=='Found']\n",
        "data[(data['year']==found['year'].max()) & (data['fall']=='Found')]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>31897</th>\n",
              "      <td>Jiddat al Harasis 799</td>\n",
              "      <td>57428</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL6</td>\n",
              "      <td>212.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>19.77278</td>\n",
              "      <td>56.38982</td>\n",
              "      <td>(19.772780, 56.389820)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31898</th>\n",
              "      <td>Johannesburg</td>\n",
              "      <td>55765</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H4</td>\n",
              "      <td>63.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>35.37788</td>\n",
              "      <td>-117.63728</td>\n",
              "      <td>(35.377880, -117.637280)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31899</th>\n",
              "      <td>Los Vientos 028</td>\n",
              "      <td>57338</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H~5</td>\n",
              "      <td>12110.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>-24.68333</td>\n",
              "      <td>-69.76667</td>\n",
              "      <td>(-24.683330, -69.766670)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31900</th>\n",
              "      <td>Tupelo</td>\n",
              "      <td>56551</td>\n",
              "      <td>Valid</td>\n",
              "      <td>EL6</td>\n",
              "      <td>280.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>34.24216</td>\n",
              "      <td>-88.77594</td>\n",
              "      <td>(34.242160, -88.775940)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31901</th>\n",
              "      <td>Mandalay Spring</td>\n",
              "      <td>57454</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L6</td>\n",
              "      <td>2854.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>40.89201</td>\n",
              "      <td>-118.55319</td>\n",
              "      <td>(40.892010, -118.553190)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31903</th>\n",
              "      <td>Antelope</td>\n",
              "      <td>57455</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H4</td>\n",
              "      <td>754.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>40.90183</td>\n",
              "      <td>-118.54465</td>\n",
              "      <td>(40.901830, -118.544650)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31904</th>\n",
              "      <td>Catalina 009</td>\n",
              "      <td>57173</td>\n",
              "      <td>Valid</td>\n",
              "      <td>CR2</td>\n",
              "      <td>5.2</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>-25.23333</td>\n",
              "      <td>-69.71667</td>\n",
              "      <td>(-25.233330, -69.716670)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31906</th>\n",
              "      <td>Ksar Ghilane 011</td>\n",
              "      <td>55606</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L4</td>\n",
              "      <td>25.6</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>32.89100</td>\n",
              "      <td>9.91300</td>\n",
              "      <td>(32.891000, 9.913000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31907</th>\n",
              "      <td>Ksar Ghilane 010</td>\n",
              "      <td>55605</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L5</td>\n",
              "      <td>50.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>32.80600</td>\n",
              "      <td>9.83300</td>\n",
              "      <td>(32.806000, 9.833000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31908</th>\n",
              "      <td>Stewart Valley 012</td>\n",
              "      <td>55528</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H6</td>\n",
              "      <td>130.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>36.23500</td>\n",
              "      <td>-116.18358</td>\n",
              "      <td>(36.235000, -116.183580)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31909</th>\n",
              "      <td>Rosamond</td>\n",
              "      <td>57434</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL3</td>\n",
              "      <td>11.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>34.82793</td>\n",
              "      <td>-118.14640</td>\n",
              "      <td>(34.827930, -118.146400)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31910</th>\n",
              "      <td>Northwest Africa 7496</td>\n",
              "      <td>56314</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Eucrite-pmict</td>\n",
              "      <td>788.4</td>\n",
              "      <td>Found</td>\n",
              "      <td>2012</td>\n",
              "      <td>22.94781</td>\n",
              "      <td>-13.38527</td>\n",
              "      <td>(22.947810, -13.385270)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        name     id  ...    reclong               GeoLocation\n",
              "31897  Jiddat al Harasis 799  57428  ...   56.38982    (19.772780, 56.389820)\n",
              "31898           Johannesburg  55765  ... -117.63728  (35.377880, -117.637280)\n",
              "31899        Los Vientos 028  57338  ...  -69.76667  (-24.683330, -69.766670)\n",
              "31900                 Tupelo  56551  ...  -88.77594   (34.242160, -88.775940)\n",
              "31901        Mandalay Spring  57454  ... -118.55319  (40.892010, -118.553190)\n",
              "31903               Antelope  57455  ... -118.54465  (40.901830, -118.544650)\n",
              "31904           Catalina 009  57173  ...  -69.71667  (-25.233330, -69.716670)\n",
              "31906       Ksar Ghilane 011  55606  ...    9.91300     (32.891000, 9.913000)\n",
              "31907       Ksar Ghilane 010  55605  ...    9.83300     (32.806000, 9.833000)\n",
              "31908     Stewart Valley 012  55528  ... -116.18358  (36.235000, -116.183580)\n",
              "31909               Rosamond  57434  ... -118.14640  (34.827930, -118.146400)\n",
              "31910  Northwest Africa 7496  56314  ...  -13.38527   (22.947810, -13.385270)\n",
              "\n",
              "[12 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E3GE00vNNOp5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 78
        },
        "outputId": "29b12c82-fdbd-4f7c-dd61-992cc735a194"
      },
      "source": [
        "#Oldest Meteorite Fell or Found\n",
        "data[data['year']==data['year'].min()]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Wietrzno-Bobrka</td>\n",
              "      <td>24259</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron</td>\n",
              "      <td>376.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>601</td>\n",
              "      <td>49.41667</td>\n",
              "      <td>21.7</td>\n",
              "      <td>(49.416670, 21.700000)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              name     id nametype  ...    reclat  reclong             GeoLocation\n",
              "0  Wietrzno-Bobrka  24259    Valid  ...  49.41667     21.7  (49.416670, 21.700000)\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-d805amJNN5F",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 78
        },
        "outputId": "9ba7b3e5-a8c6-4196-81ec-c8fc3044f9d6"
      },
      "source": [
        "#Oldest Meteorite Fell (Fall Observed)\n",
        "fell = data[data['fall']=='Fell']\n",
        "data[data['year'] == fell['year'].min()]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Nogata</td>\n",
              "      <td>16988</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L6</td>\n",
              "      <td>472.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>860</td>\n",
              "      <td>33.725</td>\n",
              "      <td>130.75</td>\n",
              "      <td>(33.725000, 130.750000)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     name     id nametype  ...  reclat  reclong              GeoLocation\n",
              "1  Nogata  16988    Valid  ...  33.725   130.75  (33.725000, 130.750000)\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J-7EEvtsNgww",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 78
        },
        "outputId": "22088842-6ba8-4d17-8115-b9f3716d8067"
      },
      "source": [
        "#Oldest Meteorite Found (Fall not Observed)\n",
        "data[(data['year']==data['year'].min()) & (data['fall']=='Found')]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Wietrzno-Bobrka</td>\n",
              "      <td>24259</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron</td>\n",
              "      <td>376.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>601</td>\n",
              "      <td>49.41667</td>\n",
              "      <td>21.7</td>\n",
              "      <td>(49.416670, 21.700000)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              name     id nametype  ...    reclat  reclong             GeoLocation\n",
              "0  Wietrzno-Bobrka  24259    Valid  ...  49.41667     21.7  (49.416670, 21.700000)\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g5mseYXhfrPi",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "61e9dd2e-9ddd-4649-dc02-9625dd796d4f"
      },
      "source": [
        "#Latest Meteorite Group by fell and found\n",
        "fell_found = data.groupby('fall')\n",
        "fell_found['year'].max()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "fall\n",
              "Fell     2013\n",
              "Found    2012\n",
              "Name: year, dtype: Int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MF6QXwrQf6Ty",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2ae6826a-a9fe-4770-c43b-4de08284ffb6"
      },
      "source": [
        "#Oldest Meteorite Group by fell and found\n",
        "fell_found['year'].min()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "fall\n",
              "Fell     860\n",
              "Found    601\n",
              "Name: year, dtype: Int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f5jRrdprOjQU"
      },
      "source": [
        "***Heaviest and Lightest Meteorite Fell or Found***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B8-h7CuAhLvV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "62c9d42b-0385-45d9-f565-478364f044fd"
      },
      "source": [
        "#Heaviest Meteorite group by Fell and Found\n",
        "fell_found['mass'].max()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "fall\n",
              "Fell     23000000.0\n",
              "Found    60000000.0\n",
              "Name: mass, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uWKwmFMhhc6C",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4a409f37-a966-4a8c-8f70-08b14d85493d"
      },
      "source": [
        "#Lightest Meteorite group by Fell and Found\n",
        "fell_found['mass'].min()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "fall\n",
              "Fell     0.10\n",
              "Found    0.01\n",
              "Name: mass, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8IvrHFCih6ml",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 78
        },
        "outputId": "9d64e51f-001f-429d-c11f-f32a38a8cc2d"
      },
      "source": [
        "#Heaviest Meteorite fell or found\n",
        "data[data['mass']==data['mass'].max()]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>995</th>\n",
              "      <td>Hoba</td>\n",
              "      <td>11890</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron, IVB</td>\n",
              "      <td>60000000.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>1920</td>\n",
              "      <td>-19.58333</td>\n",
              "      <td>17.91667</td>\n",
              "      <td>(-19.583330, 17.916670)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     name     id nametype  ...    reclat   reclong              GeoLocation\n",
              "995  Hoba  11890    Valid  ... -19.58333  17.91667  (-19.583330, 17.916670)\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
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          "height": 78
        },
        "outputId": "fbcd1b9a-d04a-4cca-8da3-e134e4f5fe1f"
      },
      "source": [
        "#Heaviest Meteorite Fell (Fall Observed)\n",
        "data[data['mass'] == fell['mass'].max()]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
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              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1581</th>\n",
              "      <td>Sikhote-Alin</td>\n",
              "      <td>23593</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron, IIAB</td>\n",
              "      <td>23000000.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1947</td>\n",
              "      <td>46.16</td>\n",
              "      <td>134.65333</td>\n",
              "      <td>(46.160000, 134.653330)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              name     id nametype  ... reclat    reclong              GeoLocation\n",
              "1581  Sikhote-Alin  23593    Valid  ...  46.16  134.65333  (46.160000, 134.653330)\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xwu8EcXOisrK",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 78
        },
        "outputId": "1f8cac89-b201-42bb-82ac-5f118c03db28"
      },
      "source": [
        "#Heaviest Meteorite Found (Fall not Observed)\n",
        "data[(data['mass']==data['mass'].max()) & (data['fall']=='Found')]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
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              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>995</th>\n",
              "      <td>Hoba</td>\n",
              "      <td>11890</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron, IVB</td>\n",
              "      <td>60000000.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>1920</td>\n",
              "      <td>-19.58333</td>\n",
              "      <td>17.91667</td>\n",
              "      <td>(-19.583330, 17.916670)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     name     id nametype  ...    reclat   reclong              GeoLocation\n",
              "995  Hoba  11890    Valid  ... -19.58333  17.91667  (-19.583330, 17.916670)\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JcFqQ0qZiNtZ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 78
        },
        "outputId": "1808c8c8-26e3-4c72-e136-8bae7047534b"
      },
      "source": [
        "#Lightest Meteorite fell or found\n",
        "data[data['mass']==data['mass'].min()]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
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              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>8363</th>\n",
              "      <td>Yamato 8333</td>\n",
              "      <td>29438</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H5</td>\n",
              "      <td>0.01</td>\n",
              "      <td>Found</td>\n",
              "      <td>1983</td>\n",
              "      <td>-71.5</td>\n",
              "      <td>35.66667</td>\n",
              "      <td>(-71.500000, 35.666670)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             name     id nametype  ... reclat   reclong              GeoLocation\n",
              "8363  Yamato 8333  29438    Valid  ...  -71.5  35.66667  (-71.500000, 35.666670)\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ML2sdt6Ii-P4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 378
        },
        "outputId": "92de6426-ab9e-44ce-c63e-9a201836d48a"
      },
      "source": [
        "#Lightest Meteorite Fell (Fall Observed)\n",
        "data[data['mass'] == fell['mass'].min()]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1122</th>\n",
              "      <td>Yoshiki</td>\n",
              "      <td>30372</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Stone-uncl</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1928</td>\n",
              "      <td>34.16667</td>\n",
              "      <td>131.45000</td>\n",
              "      <td>(34.166670, 131.450000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2064</th>\n",
              "      <td>Vilna</td>\n",
              "      <td>24183</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L5</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1967</td>\n",
              "      <td>54.22500</td>\n",
              "      <td>-111.69167</td>\n",
              "      <td>(54.225000, -111.691670)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8325</th>\n",
              "      <td>Allan Hills 83026</td>\n",
              "      <td>546</td>\n",
              "      <td>Valid</td>\n",
              "      <td>CO3</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>1983</td>\n",
              "      <td>-76.82234</td>\n",
              "      <td>158.21493</td>\n",
              "      <td>(-76.822340, 158.214930)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10889</th>\n",
              "      <td>Lewis Cliff 87056</td>\n",
              "      <td>13530</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Aubrite</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>1987</td>\n",
              "      <td>-84.34532</td>\n",
              "      <td>161.47809</td>\n",
              "      <td>(-84.345320, 161.478090)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16084</th>\n",
              "      <td>Pecora Escarpment 91357</td>\n",
              "      <td>18648</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L6</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>1991</td>\n",
              "      <td>-85.67623</td>\n",
              "      <td>-69.08566</td>\n",
              "      <td>(-85.676230, -69.085660)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19787</th>\n",
              "      <td>Queen Alexandra Range 971018</td>\n",
              "      <td>20526</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL5</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>1997</td>\n",
              "      <td>-84.00000</td>\n",
              "      <td>168.00000</td>\n",
              "      <td>(-84.000000, 168.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22655</th>\n",
              "      <td>Queen Alexandra Range 99064</td>\n",
              "      <td>21516</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L5</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>1999</td>\n",
              "      <td>-84.00000</td>\n",
              "      <td>168.00000</td>\n",
              "      <td>(-84.000000, 168.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22656</th>\n",
              "      <td>Queen Alexandra Range 99063</td>\n",
              "      <td>21515</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL5</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>1999</td>\n",
              "      <td>-84.00000</td>\n",
              "      <td>168.00000</td>\n",
              "      <td>(-84.000000, 168.000000)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24889</th>\n",
              "      <td>Frontier Mountain 01156</td>\n",
              "      <td>10338</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H3/4</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>2001</td>\n",
              "      <td>-72.98944</td>\n",
              "      <td>160.40222</td>\n",
              "      <td>(-72.989440, 160.402220)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31084</th>\n",
              "      <td>Miller Butte 09001</td>\n",
              "      <td>55371</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H5</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>2009</td>\n",
              "      <td>-71.90355</td>\n",
              "      <td>160.48982</td>\n",
              "      <td>(-71.903550, 160.489820)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31515</th>\n",
              "      <td>Khatyrka</td>\n",
              "      <td>55600</td>\n",
              "      <td>Valid</td>\n",
              "      <td>CV3</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Found</td>\n",
              "      <td>2011</td>\n",
              "      <td>62.65316</td>\n",
              "      <td>174.50043</td>\n",
              "      <td>(62.653160, 174.500430)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                               name     id  ...    reclong               GeoLocation\n",
              "1122                        Yoshiki  30372  ...  131.45000   (34.166670, 131.450000)\n",
              "2064                          Vilna  24183  ... -111.69167  (54.225000, -111.691670)\n",
              "8325              Allan Hills 83026    546  ...  158.21493  (-76.822340, 158.214930)\n",
              "10889             Lewis Cliff 87056  13530  ...  161.47809  (-84.345320, 161.478090)\n",
              "16084       Pecora Escarpment 91357  18648  ...  -69.08566  (-85.676230, -69.085660)\n",
              "19787  Queen Alexandra Range 971018  20526  ...  168.00000  (-84.000000, 168.000000)\n",
              "22655   Queen Alexandra Range 99064  21516  ...  168.00000  (-84.000000, 168.000000)\n",
              "22656   Queen Alexandra Range 99063  21515  ...  168.00000  (-84.000000, 168.000000)\n",
              "24889       Frontier Mountain 01156  10338  ...  160.40222  (-72.989440, 160.402220)\n",
              "31084            Miller Butte 09001  55371  ...  160.48982  (-71.903550, 160.489820)\n",
              "31515                      Khatyrka  55600  ...  174.50043   (62.653160, 174.500430)\n",
              "\n",
              "[11 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YifJyqj5i9_-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 78
        },
        "outputId": "eda0cf76-29e3-47d2-941c-ae180d984d97"
      },
      "source": [
        "#Lightest Meteorite Found (Fall not Observed)\n",
        "data[(data['mass']==data['mass'].min()) & (data['fall']=='Found')]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>8363</th>\n",
              "      <td>Yamato 8333</td>\n",
              "      <td>29438</td>\n",
              "      <td>Valid</td>\n",
              "      <td>H5</td>\n",
              "      <td>0.01</td>\n",
              "      <td>Found</td>\n",
              "      <td>1983</td>\n",
              "      <td>-71.5</td>\n",
              "      <td>35.66667</td>\n",
              "      <td>(-71.500000, 35.666670)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             name     id nametype  ... reclat   reclong              GeoLocation\n",
              "8363  Yamato 8333  29438    Valid  ...  -71.5  35.66667  (-71.500000, 35.666670)\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PDP6wptRmf5T"
      },
      "source": [
        "***Heaviest and Lightest Meteorites Year-wise***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SqYWN6pqmfd8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f92f0e05-88d2-4354-e960-5f5841cc7b16"
      },
      "source": [
        "#Heaviest Meteorites for each year\n",
        "groupby_year = data.groupby('year')\n",
        "groupby_year['mass'].max()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "year\n",
              "601         376.0\n",
              "860         472.0\n",
              "1399     107000.0\n",
              "1490        103.3\n",
              "1491     127000.0\n",
              "          ...    \n",
              "2009    1600000.0\n",
              "2010     100000.0\n",
              "2011      50000.0\n",
              "2012      12110.0\n",
              "2013     100000.0\n",
              "Name: mass, Length: 253, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GXD_KT3omvu1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2a14acc6-1203-4160-f0f3-42151a66bb8b"
      },
      "source": [
        "#Lightest Meteorites for each year\n",
        "groupby_year['mass'].min()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "year\n",
              "601        376.00\n",
              "860        472.00\n",
              "1399    107000.00\n",
              "1490       103.30\n",
              "1491    127000.00\n",
              "          ...    \n",
              "2009         0.10\n",
              "2010         0.18\n",
              "2011         0.10\n",
              "2012         5.20\n",
              "2013    100000.00\n",
              "Name: mass, Length: 253, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_YBlkfMrkQKS"
      },
      "source": [
        "***Count of Meteorites Year-wise***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1Js68tpDki_Q",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8ebf34bd-7e1c-4776-fed8-12cffcd14cf8"
      },
      "source": [
        "#Count of Meteorites in each year\n",
        "data['year'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1979    3044\n",
              "1988    2295\n",
              "2003    1713\n",
              "1999    1578\n",
              "1990    1506\n",
              "        ... \n",
              "1723       1\n",
              "1787       1\n",
              "860        1\n",
              "1628       1\n",
              "1600       1\n",
              "Name: year, Length: 253, dtype: Int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b10Auq5eniAb"
      },
      "source": [
        "***Analysis based on Geo-Location***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HKWe-QW-nsD_",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "44d18fb4-97d2-4b4d-8ce5-32c637469789"
      },
      "source": [
        "#Meteorite Count for each GeoLocation \n",
        "data['GeoLocation'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(-71.500000, 35.666670)     4760\n",
              "(-84.000000, 168.000000)    3040\n",
              "(-72.000000, 26.000000)     1505\n",
              "(-79.683330, 159.750000)     657\n",
              "(-76.716670, 159.666670)     637\n",
              "                            ... \n",
              "(19.737680, 56.110870)         1\n",
              "(55.183330, -162.550000)       1\n",
              "(-25.916670, 119.300000)       1\n",
              "(34.318330, -103.471670)       1\n",
              "(27.033330, 16.183330)         1\n",
              "Name: GeoLocation, Length: 16905, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ybOmJRz2pChw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5fbf1975-09bc-49b1-8827-5b82e9454837"
      },
      "source": [
        "#Heaviest Meteorite for each GeoLocation\n",
        "groupby_loc = data.groupby('GeoLocation')\n",
        "groupby_loc['mass'].max()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "GeoLocation\n",
              "(-1.002780, 37.150280)     14200.0\n",
              "(-1.216670, 30.000000)      4975.0\n",
              "(-1.450000, 29.833330)       465.5\n",
              "(-1.870890, -79.957560)     6580.0\n",
              "(-10.059440, 33.395000)     3920.0\n",
              "                            ...   \n",
              "(9.500000, 35.333330)       2450.0\n",
              "(9.533330, 39.716670)       6500.0\n",
              "(9.600000, 9.916670)         480.0\n",
              "(9.666670, 105.666670)     13100.0\n",
              "(9.916670, 13.983330)        968.0\n",
              "Name: mass, Length: 16905, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YteGEK6fqD_z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a208c8d7-e0f8-42b7-8893-e33474afdc73"
      },
      "source": [
        "#Lightest Meteorite for each GeoLocation\n",
        "groupby_loc['mass'].min()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "GeoLocation\n",
              "(-1.002780, 37.150280)     14200.0\n",
              "(-1.216670, 30.000000)      4975.0\n",
              "(-1.450000, 29.833330)       465.5\n",
              "(-1.870890, -79.957560)     6580.0\n",
              "(-10.059440, 33.395000)     3920.0\n",
              "                            ...   \n",
              "(9.500000, 35.333330)       2450.0\n",
              "(9.533330, 39.716670)       6500.0\n",
              "(9.600000, 9.916670)         480.0\n",
              "(9.666670, 105.666670)     13100.0\n",
              "(9.916670, 13.983330)        968.0\n",
              "Name: mass, Length: 16905, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dLh4hvzcwtHv",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e188bb1e-3d5b-4c5a-bd1a-ea43d5ae1a23"
      },
      "source": [
        "#Geolocation of Heaviest Meteorite\n",
        "data['GeoLocation'][data['mass']==data['mass'].max()]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "995    (-19.583330, 17.916670)\n",
              "Name: GeoLocation, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hSsc_voN27JS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "87dc4d2a-a1bf-4b85-e9f9-04bc565e8fad"
      },
      "source": [
        "#Geolocation of Lightest Meteorite\n",
        "data['GeoLocation'][data['mass']==data['mass'].min()]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "8363    (-71.500000, 35.666670)\n",
              "Name: GeoLocation, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "O7zGFbK132qH"
      },
      "source": [
        "***Pivot Tables***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ejCy92Qc4RE2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 378
        },
        "outputId": "484a5175-e552-42ed-dee6-56c3f79caca7"
      },
      "source": [
        "table = pd.pivot_table(data[:10], values='mass', index=['year'],columns=['fall'], aggfunc=np.sum)\n",
        "table"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>fall</th>\n",
              "      <th>Fell</th>\n",
              "      <th>Found</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>year</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>601</th>\n",
              "      <td>NaN</td>\n",
              "      <td>376.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>860</th>\n",
              "      <td>472.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1399</th>\n",
              "      <td>107000.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1490</th>\n",
              "      <td>103.3</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1491</th>\n",
              "      <td>127000.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1575</th>\n",
              "      <td>NaN</td>\n",
              "      <td>50000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1583</th>\n",
              "      <td>15000.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1600</th>\n",
              "      <td>NaN</td>\n",
              "      <td>10100000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1621</th>\n",
              "      <td>1967.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1623</th>\n",
              "      <td>10400.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "fall      Fell       Found\n",
              "year                      \n",
              "601        NaN       376.0\n",
              "860      472.0         NaN\n",
              "1399  107000.0         NaN\n",
              "1490     103.3         NaN\n",
              "1491  127000.0         NaN\n",
              "1575       NaN  50000000.0\n",
              "1583   15000.0         NaN\n",
              "1600       NaN  10100000.0\n",
              "1621    1967.0         NaN\n",
              "1623   10400.0         NaN"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 74
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W72rJJYt4_7t",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 378
        },
        "outputId": "c6453b7a-4ace-4671-89c5-b5db48e093d8"
      },
      "source": [
        "table2 = pd.pivot_table(data[:10],values='mass',index=['year'],columns=['nametype'], aggfunc=np.sum)\n",
        "table2"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>nametype</th>\n",
              "      <th>Valid</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>year</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>601</th>\n",
              "      <td>376.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>860</th>\n",
              "      <td>472.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1399</th>\n",
              "      <td>107000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1490</th>\n",
              "      <td>103.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1491</th>\n",
              "      <td>127000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1575</th>\n",
              "      <td>50000000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1583</th>\n",
              "      <td>15000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1600</th>\n",
              "      <td>10100000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1621</th>\n",
              "      <td>1967.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1623</th>\n",
              "      <td>10400.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "nametype       Valid\n",
              "year                \n",
              "601            376.0\n",
              "860            472.0\n",
              "1399        107000.0\n",
              "1490           103.3\n",
              "1491        127000.0\n",
              "1575      50000000.0\n",
              "1583         15000.0\n",
              "1600      10100000.0\n",
              "1621          1967.0\n",
              "1623         10400.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 75
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kpK2UN8a7LyL"
      },
      "source": [
        "***Crosstab and Heatmap***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZasaOa677PNd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 138
        },
        "outputId": "990205a5-1b78-4db4-bbc6-25a76e328ecf"
      },
      "source": [
        "#Crosstabulation between 'mass' and 'fall'\n",
        "fall_mass = pd.crosstab(data['fall'].head(10),data['mass'].head(10))\n",
        "fall_mass"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>mass</th>\n",
              "      <th>103.3</th>\n",
              "      <th>376.0</th>\n",
              "      <th>472.0</th>\n",
              "      <th>1967.0</th>\n",
              "      <th>10400.0</th>\n",
              "      <th>15000.0</th>\n",
              "      <th>107000.0</th>\n",
              "      <th>127000.0</th>\n",
              "      <th>10100000.0</th>\n",
              "      <th>50000000.0</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>fall</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Fell</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Found</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "mass   103.3       376.0       472.0       ...  127000.0    10100000.0  50000000.0\n",
              "fall                                       ...                                    \n",
              "Fell            1           0           1  ...           1           0           0\n",
              "Found           0           1           0  ...           0           1           1\n",
              "\n",
              "[2 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oLDvb7QFEWf0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 351
        },
        "outputId": "95db54e3-f60f-42fd-f9ce-4f892e6f18cd"
      },
      "source": [
        "#Heatmap of Crosstabulation between 'mass' and 'fall'\n",
        "sns.heatmap(fall_mass)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f4e26026080>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 77
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CltVPC1m8Ufk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        },
        "outputId": "3e1bd146-887e-4447-fe46-5cc2cdf201cc"
      },
      "source": [
        "#Crosstabulation between 'mass' and 'nametype'\n",
        "pd.crosstab(data['nametype'].head(10),data['mass'].head(10))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>mass</th>\n",
              "      <th>103.3</th>\n",
              "      <th>376.0</th>\n",
              "      <th>472.0</th>\n",
              "      <th>1967.0</th>\n",
              "      <th>10400.0</th>\n",
              "      <th>15000.0</th>\n",
              "      <th>107000.0</th>\n",
              "      <th>127000.0</th>\n",
              "      <th>10100000.0</th>\n",
              "      <th>50000000.0</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>nametype</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Valid</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "mass      103.3       376.0       ...  10100000.0  50000000.0\n",
              "nametype                          ...                        \n",
              "Valid              1           1  ...           1           1\n",
              "\n",
              "[1 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UcBpbb0T9UrT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 138
        },
        "outputId": "f7846969-14ad-401d-e03b-ad3f7c9588c7"
      },
      "source": [
        "#Crosstabulation between 'fall' and 'year'\n",
        "fall_year = pd.crosstab(data['fall'].head(10),data['year'].head(10))\n",
        "fall_year"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>year</th>\n",
              "      <th>601</th>\n",
              "      <th>860</th>\n",
              "      <th>1399</th>\n",
              "      <th>1490</th>\n",
              "      <th>1491</th>\n",
              "      <th>1575</th>\n",
              "      <th>1583</th>\n",
              "      <th>1600</th>\n",
              "      <th>1621</th>\n",
              "      <th>1623</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>fall</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Fell</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Found</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "year   601   860   1399  1490  1491  1575  1583  1600  1621  1623\n",
              "fall                                                             \n",
              "Fell      0     1     1     1     1     0     1     0     1     1\n",
              "Found     1     0     0     0     0     1     0     1     0     0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 79
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PGlG2PxIEFj0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 301
        },
        "outputId": "fcbbd774-1d7f-461d-b722-f47acb1dea20"
      },
      "source": [
        "#Heatmap of Crosstabulation between 'fall' and 'year'\n",
        "sns.heatmap(fall_year)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f4e25f785f8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 80
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cMx46XW79hjq",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        },
        "outputId": "d8b9c10f-9387-493b-ac3b-76347b5acc15"
      },
      "source": [
        "#Crosstabulation between 'nametype' and 'year'\n",
        "pd.crosstab(data['nametype'].head(10),data['year'].head(10))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>year</th>\n",
              "      <th>601</th>\n",
              "      <th>860</th>\n",
              "      <th>1399</th>\n",
              "      <th>1490</th>\n",
              "      <th>1491</th>\n",
              "      <th>1575</th>\n",
              "      <th>1583</th>\n",
              "      <th>1600</th>\n",
              "      <th>1621</th>\n",
              "      <th>1623</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>nametype</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Valid</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "year      601   860   1399  1490  1491  1575  1583  1600  1621  1623\n",
              "nametype                                                            \n",
              "Valid        1     1     1     1     1     1     1     1     1     1"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7XbcNCicBLdj"
      },
      "source": [
        "***Plotting***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uFLVBn_PO3Ue"
      },
      "source": [
        "#Preprocessing of Mass\n",
        "mass = data['mass']\n",
        "mass = np.array(mass)\n",
        "minmax_scale = preprocessing.MinMaxScaler(feature_range=(0,1))\n",
        "data['scaled_mass'] = minmax_scale.fit_transform(mass.reshape(len(mass),1))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4h19vQdTPQVL",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bcec0416-49d6-4f53-d3bd-9b822e68a32b"
      },
      "source": [
        "data['scaled_mass']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0        6.266500e-06\n",
              "1        7.866500e-06\n",
              "2        1.783333e-03\n",
              "3        1.721500e-06\n",
              "4        2.116667e-03\n",
              "             ...     \n",
              "31907    8.348333e-07\n",
              "31908    2.166500e-06\n",
              "31909    1.848333e-07\n",
              "31910    1.313983e-05\n",
              "31911    1.666667e-03\n",
              "Name: scaled_mass, Length: 31912, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_Gg6uurYZ3KT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 331
        },
        "outputId": "c6efca5a-475a-4775-9438-3bff7044edf2"
      },
      "source": [
        "#Plotting Graph of Mass Vs Year and Scaled Mass Vs Year to make sure preproccessing is not wrong\n",
        "%matplotlib inline\n",
        "fig, ax = plt.subplots(2,1, sharex=True,figsize=(10,5))\n",
        "ax[0].plot(data.loc[:100,'mass'],'b')\n",
        "ax[1].plot(data.loc[:100,'scaled_mass'],'g')\n",
        "labels = ax[0].set_xticklabels(data.loc[:100,'year'],rotation=0)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HfudrXNSgU0v",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 456
        },
        "outputId": "75fd6cea-2642-463d-8214-2bf117554d4b"
      },
      "source": [
        "#Plotting Histogram for frequency of Meteorite Landings (in centuries)\n",
        "%matplotlib inline\n",
        "fig = plt.figure(figsize=(10,5))\n",
        "ax = fig.add_axes([0,0,1,1])\n",
        "ax.hist(data['year'])\n",
        "ax.set_xlabel('Year')\n",
        "ax.set_ylabel('Count')\n",
        "ax.set_title('Plot showing most of the Meteorite landings (fell or found) has been in recent centuries')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Plot showing most of the Meteorite landings (fell or found) has been in recent centuries')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 85
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ZvDc/APxNkt9v9b5v60vnAremu+nClu01f3CSh85y1dcxzWce3Wl0z2j7oE1aWz5gLfcld1rv2vTb5j/ojuw/rX1+bJbkoelu4LF5uv85sW1V/YYuqMzmc1sLxCChddnxdKemfJ3uVp6/ojv/f+LQ63HAN9MdGj1gxPxLgQuT/Bz4Z7prIEadQjXZG+k+oC8Avk93IXP/nzadRfch+/Upng/1frqd/AXAd4HT6D7A71jD5f1OVV1Cd8Hkv9D9+vd4ulvv3kZ34eObWvm1dIe5X9lmnfgncjck+c6I5d7WlvXYNv+76c7D/uEsqzbt8kesbwXdL+yvovtiswJ4GbPYh1XVj6pq2RSjX0F3QfTZ6U4B+jLdtTi0bTkJuKz1sZ3p+tGpwJeS3Ep34fXD2vTTtfVsjGqTI+guyryI7ojCJ5n5dC7oTuO6ku7D/qJWz1lpR9WeRNc3bgD2pDvPfk1M17c3ofuS/hPgRrqLcJ87RZ2uo7ve4rBR45spX8uBXkj3i+tlwDforjs4fg2WA0BVfZnueoBP0R1FuA9weG+SZ9H15RuABzH74AndkaeH0bXfsdz59L2n0oXfNXE63WlG/0XXl37F6qerDNm/XkvXf39Cd0H3c3r7iuneg8vo2uedbf7ldKcprgumfG9W1SfoPp8+RncB/L8Dd29B9XF0p8VeTref+ADdEcPZ+Hu6H7luzog7GVXVuXQXML+d7qLrs1h1NGxN9yXQvb5PTHdHp4n/2bLG/baqbgUOpnsf/ISuf7yZ7jMJuqPiV7T+8By6fqx11MQV+ZLWEeluu/feqtp9xoml9cja9O0kewEnAPuXH1wzar/wnwXsU+22uZI01wwS0gJLd374H9L9crsj3S+XZ1fVixe0YtJasm9L0obNICEtsCR3pfvl8AF01yl8nu7WgbdMO6O0jrNvS9KGzSAhSZIkaTAvtpYkSZI0mEFCkiRJ0mAb3T+k22GHHWrJkiULXQ1JkiRpvfDtb3/7p1W1eHL5RhcklixZwrJlU91SXpIkSVJfkpH/2NJTmyRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjSYQUKSJEnSYAYJSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgixa6ApIkSdIoS475/EJXYcFd8aY/XugqTMkjEpIkSZIGM0hIkiRJGswgIUmSJGkwg4QkSZKkwQwSkiRJkgYzSEiSJEkazCAhSZIkaTCDhCRJkqTBDBKSJEmSBjNISJIkSRrMICFJkiRpMIOEJEmSpMHGFiSS3CXJuUm+l+TCJK9r5XskOSfJ8iQfT7J5K9+iPV/exi/pLeuVrfySJIf0ype2suVJjhnXtkiSJEla3TiPSPwaOKiqHgLsDSxNcgDwZuDtVXVf4CbgqDb9UcBNrfztbTqS7AUcDjwIWAq8O8mmSTYF3gU8FtgLeEqbVpIkSdKYjS1IVOfn7elm7VHAQcAnW/kJwBPa8GHtOW38o5OklZ9cVb+uqsuB5cD+7bG8qi6rqtuAk9u0kiRJksZsrNdItCMH5wPXA2cAPwJurqrb2yRXAbu04V2AFQBt/M+Ae/TLJ80zVbkkSZKkMRtrkKiqO6pqb2BXuiMIDxjn+qaS5Ogky5IsW7ly5UJUQZIkSdqgzMtdm6rqZuBM4OHAdkkWtVG7Ale34auB3QDa+G2BG/rlk+aZqnzU+t9XVftV1X6LFy+ek22SJEmSNmbjvGvT4iTbteEtgccAF9MFiie2yY4EPtuGT23PaeO/WlXVyg9vd3XaA9gTOBc4D9iz3QVqc7oLsk8d1/ZIkiRJWmXRzJOssZ2AE9rdlTYBTqmq/0hyEXBykjcC3wU+2Kb/IPDhJMuBG+mCAVV1YZJTgIuA24HnV9UdAEleAJwObAocX1UXjnF7JEmSJDVjCxJVdQGwz4jyy+iul5hc/ivgSVMs6zjguBHlpwGnrXVlJUmSJA3if7aWJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjSYQUKSJEnSYAYJSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjSYQUKSJEnSYAYJSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjSYQUKSJEnSYAYJSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjTY2IJEkt2SnJnkoiQXJnlRK39tkquTnN8eh/bmeWWS5UkuSXJIr3xpK1ue5Jhe+R5JzmnlH0+y+bi2R5IkSdIq4zwicTvw0qraCzgAeH6Svdq4t1fV3u1xGkAbdzjwIGAp8O4kmybZFHgX8FhgL+ApveW8uS3rvsBNwFFj3B5JkiRJzdiCRFVdU1XfacO3AhcDu0wzy2HAyVX166q6HFgO7N8ey6vqsqq6DTgZOCxJgIOAT7b5TwCeMJ6tkSRJktQ3L9dIJFkC7AOc04pekOSCJMcn2b6V7QKs6M12VSubqvwewM1VdfukckmSJEljNvYgkWRr4FPAi6vqFuA9wH2AvYFrgH+chzocnWRZkmUrV64c9+okSZKkDd5Yg0SSzehCxEer6tMAVXVdVd1RVb8F3k936hLA1cBuvdl3bWVTld8AbJdk0aTyO6mq91XVflW13+LFi+dm4yRJkqSN2Djv2hTgg8DFVfW2XvlOvcn+FPhBGz4VODzJFkn2APYEzgXOA/Zsd2janO6C7FOrqoAzgSe2+Y8EPjuu7ZEkSZK0yqKZJ1ljjwCeBnw/yfmt7FV0d13aGyjgCuDZAFV1YZJTgIvo7vj0/Kq6AyDJC4DTgU2B46vqwra8VwAnJ3kj8F264CJJkiRpzMYWJKrqG0BGjDptmnmOA44bUX7aqPmq6jJWnRolSZIkaZ74n60lSZIkDWaQkCRJkjSYQUKSJEnSYAYJSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjSYQUKSJEnSYAYJSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjSYQUKSJEnSYAYJSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjSYQUKSJEnSYAYJSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI02NiCRJLdkpyZ5KIkFyZ5USu/e5Izklza/m7fypPkHUmWJ7kgyb69ZR3Zpr80yZG98t9P8v02zzuSZFzbI0mSJGmVcR6RuB14aVXtBRwAPD/JXsAxwFeqak/gK+05wGOBPdvjaOA90AUP4FjgYcD+wLET4aNN86zefEvHuD2SJEmSmrEFiaq6pqq+04ZvBS4GdgEOA05ok50APKENHwacWJ2zge2S7AQcApxRVTdW1U3AGcDSNu5uVXV2VRVwYm9ZkiRJksZoXq6RSLIE2Ac4B9ixqq5po64FdmzDuwArerNd1cqmK79qRPmo9R+dZFmSZStXrlyrbZEkSZI0D0EiydbAp4AXV9Ut/XHtSEKNuw5V9b6q2q+q9lu8ePG4VydJkiRt8MYaJJJsRhciPlpVn27F17XTkmh/r2/lVwO79WbftZVNV77riHJJkiRJYzbOuzYF+CBwcVW9rTfqVGDizktHAp/tlR/R7t50APCzdgrU6cDBSbZvF1kfDJzext2S5IC2riN6y5IkSZI0RovGuOxHAE8Dvp/k/Fb2KuBNwClJjgKuBJ7cxp0GHAosB34JPAOgqm5M8gbgvDbd66vqxjb8POBDwJbAF9pDkiRJ0piNLUhU1TeAqf6vw6NHTF/A86dY1vHA8SPKlwEPXotqSpIkSVoD/mdrSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjSYQUKSJEnSYAYJSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI02KyCRJJHzKZMkiRJ0sZhtkck/mWWZZIkSZI2AoumG5nk4cD/BBYn+eveqLsBm46zYpIkSZLWXdMGCWBzYOs23Ta98luAJ46rUpIkSZLWbdMGiao6CzgryYeq6sp5qpMkSZKkddxMRyQmbJHkfcCS/jxVddA4KiVJkiRp3TbbIPEJ4L3AB4A7xlcdSZIkSeuD2QaJ26vqPWOtiSRJkqT1xmxv//q5JM9LslOSu088xlozSZIkSeus2R6ROLL9fVmvrIB7z211JEmSJK0PZhUkqmqPcVdEkiRJ0vpjVkEiyRGjyqvqxLmtjiRJkqT1wWxPbXpob/guwKOB7wAGCUmSJGkjNNtTm17Yf55kO+DksdRIkiRJ0jpvtndtmuwXgNdNSJIkSRup2V4j8Tm6uzQBbAo8EDhlXJWSJEmStG6b7TUSb+0N3w5cWVVXjaE+kiRJktYDszq1qarOAn4IbANsD9w2zkpJkiRJWrfNKkgkeTJwLvAk4MnAOUmeOM6KSZIkSVp3zfbUplcDD62q6wGSLAa+DHxyXBWTJEmStO6a7V2bNpkIEc0NA+aVJEmStIGZ7RGJLyY5HTipPf8L4LTxVEmSJEnSum7aIJHkvsCOVfWyJH8GPLKN+k/go+OunCRJkqR100xHJP4JeCVAVX0a+DRAkt9r4x4/1tpJkiRJWifNdJ3DjlX1/cmFrWzJWGokSZIkaZ03U5DYbppxW85lRSRJkiStP2YKEsuSPGtyYZJnAt+ebsYkxye5PskPemWvTXJ1kvPb49DeuFcmWZ7kkiSH9MqXtrLlSY7ple+R5JxW/vEkm89mgyVJkiStvZmukXgx8JkkT2VVcNgP2Bz40xnm/RDwTuDESeVvr6q39guS7AUcDjwI2Bn4cpL7tdHvAh4DXAWcl+TUqroIeHNb1slJ3gscBbxnhjpJkiRJmgPTHpGoquuq6n8CrwOuaI/XVdXDq+raGeb9OnDjLOtxGHByVf26qi4HlgP7t8fyqrqsqm4DTgYOSxLgIFb9Q7wTgCfMcl2SJEmS1tKs/o9EVZ0JnDlH63xBkiOAZcBLq+omYBfg7N40V7UygBWTyh8G3AO4uapuHzG9JEmSpDGb7/9O/R7gPsDewDXAP87HSpMcnWRZkmUrV66cj1VKkiRJG7R5DRLtVKk7quq3wPvpTl0CuBrYrTfprq1sqvIbgO2SLJpUPtV631dV+1XVfosXL56bjZEkSZI2YvMaJJLs1Hv6p8DEHZ1OBQ5PskWSPYA9gXOB84A92x2aNqe7IPvUqiq6U62e2OY/EvjsfGyDJEmSpFleI7EmkpwEHAjskOQq4FjgwCR7A0V34fazAarqwiSnABcBtwPPr6o72nJeAJwObAocX1UXtlW8Ajg5yRuB7wIfHNe2SJIkSVrd2IJEVT1lRPGUX/ar6jjguBHlpwGnjSi/jFWnRkmSJEmaR/N9sbUkSZKkDYBBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjSYQUKSJEnSYAYJSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjSYQUKSJEnSYAYJSTfYE+MAAA8pSURBVJIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjSYQUKSJEnSYAYJSZIkSYMZJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmDGSQkSZIkDWaQkCRJkjTY2IJEkuOTXJ/kB72yuyc5I8ml7e/2rTxJ3pFkeZILkuzbm+fINv2lSY7slf9+ku+3ed6RJOPaFkmSJEmrG+cRiQ8BSyeVHQN8par2BL7SngM8FtizPY4G3gNd8ACOBR4G7A8cOxE+2jTP6s03eV2SJEmSxmRsQaKqvg7cOKn4MOCENnwC8IRe+YnVORvYLslOwCHAGVV1Y1XdBJwBLG3j7lZVZ1dVASf2liVJkiRpzOb7Gokdq+qaNnwtsGMb3gVY0ZvuqlY2XflVI8olSZIkzYMFu9i6HUmo+VhXkqOTLEuybOXKlfOxSkmSJGmDNt9B4rp2WhLt7/Wt/Gpgt950u7ay6cp3HVE+UlW9r6r2q6r9Fi9evNYbIUmSJG3s5jtInApM3HnpSOCzvfIj2t2bDgB+1k6BOh04OMn27SLrg4HT27hbkhzQ7tZ0RG9ZkiRJksZs0bgWnOQk4EBghyRX0d196U3AKUmOAq4EntwmPw04FFgO/BJ4BkBV3ZjkDcB5bbrXV9XEBdzPo7sz1JbAF9pDkiRJ0jwYW5CoqqdMMerRI6Yt4PlTLOd44PgR5cuAB69NHSVJkiStGf+ztSRJkqTBDBKSJEmSBjNISJIkSRrMICFJkiRpMIOEJEmSpMEMEpIkSZIGM0hIkiRJGswgIUmSJGkwg4QkSZKkwQwSkiRJkgYzSEiSJEkazCAhSZIkaTCDhCRJkqTBDBKSJEmSBjNISJIkSRrMICFJkiRpMIOEJEmSpMEMEpIkSZIGM0hIkiRJGswgIUmSJGkwg4QkSZKkwQwSkiRJkgYzSEiSJEkazCAhSZIkaTCDhCRJkqTBDBKSJEmSBjNISJIkSRrMICFJkiRpMIOEJEmSpMEMEpIkSZIGM0hIkiRJGswgIUmSJGkwg4QkSZKkwQwSkiRJkgYzSEiSJEkazCAhSZIkaTCDhCRJkqTBDBKSJEmSBjNISJIkSRrMICFJkiRpMIOEJEmSpMEMEpIkSZIGM0hIkiRJGswgIUmSJGkwg4QkSZKkwQwSkiRJkgZbkCCR5Iok309yfpJlrezuSc5Icmn7u30rT5J3JFme5IIk+/aWc2Sb/tIkRy7EtkiSJEkbo4U8IvGHVbV3Ve3Xnh8DfKWq9gS+0p4DPBbYsz2OBt4DXfAAjgUeBuwPHDsRPiRJkiSN17p0atNhwAlt+ATgCb3yE6tzNrBdkp2AQ4AzqurGqroJOANYOt+VliRJkjZGCxUkCvhSkm8nObqV7VhV17Tha4Ed2/AuwIrevFe1sqnK7yTJ0UmWJVm2cuXKudoGSZIkaaO1aIHW+8iqujrJPYEzkvywP7KqKknN1cqq6n3A+wD222+/OVuuJEmStLFakCMSVXV1+3s98Bm6axyua6cs0f5e3ya/GtitN/uurWyqckmSJEljNu9BIslWSbaZGAYOBn4AnApM3HnpSOCzbfhU4Ih296YDgJ+1U6BOBw5Osn27yPrgViZJkiRpzBbi1KYdgc8kmVj/x6rqi0nOA05JchRwJfDkNv1pwKHAcuCXwDMAqurGJG8AzmvTvb6qbpy/zZAkSZI2XvMeJKrqMuAhI8pvAB49oryA50+xrOOB4+e6jpIkSZKmty7d/lWSJEnSesIgIUmSJGkwg4QkSZKkwQwSkiRJkgYzSEiSJEkazCAhSZIkaTCDhCRJkqTBDBKSJEmSBjNISJIkSRrMICFJkiRpMIOEJEmSpMEMEpIkSZIGM0hIkiRJGswgIUmSJGkwg4QkSZKkwQwSkiRJkgYzSEiSJEkazCAhSZIkaTCDhCRJkqTBDBKSJEmSBjNISJIkSRrMICFJkiRpMIOEJEmSpMEMEpIkSZIGM0hIkiRJGswgIUmSJGkwg4QkSZKkwQwSkiRJkgYzSEiSJEkazCAhSZIkaTCDhCRJkqTBDBKSJEmSBjNISJIkSRrMICFJkiRpMIOEJEmSpMEMEpIkSZIGM0hIkiRJGswgIUmSJGkwg4QkSZKkwQwSkiRJkgYzSEiSJEkazCAhSZIkaTCDhCRJkqTBDBKSJEmSBjNISJIkSRps0UJXYG0lWQr8M7Ap8IGqetMCV0mSJGmtLDnm8wtdBWlG6/URiSSbAu8CHgvsBTwlyV4LWytJkiRpw7deBwlgf2B5VV1WVbcBJwOHLXCdJEmSpA3e+h4kdgFW9J5f1cokSZIkjdF6f43EbCQ5Gji6Pf15kksWsDo7AD9dwPVvjGzz+WV7zz/bfP7Z5vPPNp9ftvf8G9nmefMC1OTOdh9VuL4HiauB3XrPd21lq6mq9wHvm69KTSfJsqrab6HrsTGxzeeX7T3/bPP5Z5vPP9t8ftne8299bPP1/dSm84A9k+yRZHPgcODUBa6TJEmStMFbr49IVNXtSV4AnE53+9fjq+rCBa6WJEmStMFbr4MEQFWdBpy20PUYYJ04xWojY5vPL9t7/tnm8882n3+2+fyyveffetfmqaqFroMkSZKk9cz6fo2EJEmSpAVgkJhjSbZL8skkP0xycZKHJ7l7kjOSXNr+bt+mTZJ3JFme5IIk+y50/ddHSV6S5MIkP0hyUpK7tAvwz2lt+/F2MT5JtmjPl7fxSxa29uuHJMcnuT7JD3plg/t1kiPb9JcmOXIhtmV9MUWb/0Pbt1yQ5DNJtuuNe2Vr80uSHNIrX9rKlic5Zr63Y30xqr17416apJLs0J7bx+fAVG2e5IWtn1+Y5C29cvv4Wppiv7J3krOTnJ9kWZL9W7n9fC0l2S3JmUkuav35Ra18w/n8rCofc/gATgCe2YY3B7YD3gIc08qOAd7chg8FvgAEOAA4Z6Hrv7496P4B4eXAlu35KcDT29/DW9l7gee24ecB723DhwMfX+htWB8ewP8C9gV+0Csb1K+BuwOXtb/bt+HtF3rb1tXHFG1+MLCoDb+51+Z7Ad8DtgD2AH5EdwOKTdvwvdv+6HvAXgu9beviY1R7t/Ld6G7ocSWwQyuzj4+pzYE/BL4MbNGe37P9tY+Pr82/BDy2DR8KfK03bD9fu/beCdi3DW8D/FfryxvM56dHJOZQkm3p3qQfBKiq26rqZuAwuoBB+/uENnwYcGJ1zga2S7LTPFd7Q7AI2DLJIuCuwDXAQcAn2/jJbT7xWnwSeHSSzGNd10tV9XXgxknFQ/v1IcAZVXVjVd0EnAEsHX/t10+j2ryqvlRVt7enZ9P97xzo2vzkqvp1VV0OLAf2b4/lVXVZVd0GnNym1SRT9HGAtwMvB/oXFNrH58AUbf5c4E1V9es2zfWt3D4+B6Zo8wLu1oa3BX7Shu3na6mqrqmq77ThW4GL6X4A3WA+Pw0Sc2sPYCXwb0m+m+QDSbYCdqyqa9o01wI7tuFdgBW9+a9qZZqlqroaeCvwY7oA8TPg28DNvS9c/Xb9XZu38T8D7jGfdd6ADO3X9ve59Vd0v1yBbT4WSQ4Drq6q700aZXuPz/2AR7VTT89K8tBWbpuPz4uBf0iygu7z9JWt3DafQ+lOpd4HOIcN6PPTIDG3FtEdMnxPVe0D/ILukNXvVHeMyltlzZF2XuFhdCFuZ2Ar1pGUvjGxX8+vJK8Gbgc+utB12VAluSvwKuBvF7ouG5lFdKdvHAC8DDjFo8Zj91zgJVW1G/AS2lkVmjtJtgY+Bby4qm7pj1vfPz8NEnPrKuCqqjqnPf8kXbC4buKUpfZ34lDt1XTn307YtZVp9v4IuLyqVlbVb4BPA4+gOxw48X9S+u36uzZv47cFbpjfKm8whvZr+/scSPJ04HHAU9sHENjm43Afuh8ovpfkCrq2+06S/4HtPU5XAZ9up3acC/wW2AHbfJyOpPvsBPgE3eliYJvPiSSb0YWIj1bVRDtvMJ+fBok5VFXXAiuS3L8VPRq4CDiV7o1K+/vZNnwqcES7Sv8A4Ge9Q12anR8DByS5a/vVaqLNzwSe2KaZ3OYTr8UTga/2voxpmKH9+nTg4CTbtyNJB7cyzVKSpXTn6/9JVf2yN+pU4PB0dyXbA9gTOBc4D9gz3V3MNqe7wcCp813v9VFVfb+q7llVS6pqCd0X3H3bft4+Pj7/TnfBNUnuR3cB9U+xj4/TT4A/aMMHAZe2Yfv5WmrfSz4IXFxVb+uN2nA+PxfqKu8N9QHsDSwDLqDbIW5Pdw7+V+jenF8G7t6mDfAuujtOfB/Yb6Hrvz4+gNcBPwR+AHyY7q4e96b7kFlO9wvLxB1A7tKeL2/j773Q9V8fHsBJdNeg/IbuC9VRa9Kv6c7rX94ez1jo7VqXH1O0+XK682TPb4/39qZ/dWvzS2h3YGnlh9LdKeRHwKsXervW1ceo9p40/gpW3bXJPj6mNqcLDh9p+/PvAAf1prePj6fNH0l3beH36M7f//02rf187dv7kXSnLV3Q228fuiF9fvqfrSVJkiQN5qlNkiRJkgYzSEiSJEkazCAhSZIkaTCDhCRJkqTBDBKSJEmSBjNISJLGpt0P/RtJHtsre1KSLy5kvSRJa8/bv0qSxirJg+n+f8s+wCLgu8DSqvrRGixrUVXdPsdVlCStAYOEJGnskrwF+AWwVfu7O/BgYDPgtVX12SRL6P6p5FZtthdU1beSHAi8AbgJeEBV3W9+ay9JGsUgIUkauyRb0f2n4tuA/wAurKqPJNmO7r/M70P3H2B/W1W/SrIncFJV7deCxOeBB1fV5QuzBZKkyRYtdAUkSRu+qvpFko8DPweeDDw+yd+00XcB7gX8BHhnkr2BO4D+kYdzDRGStG4xSEiS5stv2yPAn1fVJf2RSV4LXAc8hO5mIL/qjf7FPNVRkjRL3rVJkjTfTgdemCQASfZp5dsC11TVb4GnAZsuUP0kSbNgkJAkzbc30F1kfUGSC9tzgHcDRyb5HvAAPAohSes0L7aWJEmSNJhHJCRJkiQNZpCQJEmSNJhBQpIkSdJgBglJkiRJgxkkJEmSJA1mkJAkSZI0mEFCkiRJ0mAGCUmSJEmD/f/ST57qC5uFZgAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Jn-62bs22r4f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "7615ef00-76cc-4e1d-c274-943aaf2cd369"
      },
      "source": [
        "#Plotting Histogram for frequency of Meteorite Landings\n",
        "fig = plt.figure(figsize=(15,5))\n",
        "yr_plot = sns.countplot(data=data[:100],x='year')\n",
        "yr_plot.set_title('Plot showing most of the Meteorite landings (fell or found) has been in recent centuries')\n",
        "yr_plot.set_xticklabels(labels=data.loc[:100,'year'],rotation=90)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Text(0, 0, '601'),\n",
              " Text(0, 0, '860'),\n",
              " Text(0, 0, '1399'),\n",
              " Text(0, 0, '1490'),\n",
              " Text(0, 0, '1491'),\n",
              " Text(0, 0, '1575'),\n",
              " Text(0, 0, '1583'),\n",
              " Text(0, 0, '1600'),\n",
              " Text(0, 0, '1621'),\n",
              " Text(0, 0, '1623'),\n",
              " Text(0, 0, '1628'),\n",
              " Text(0, 0, '1632'),\n",
              " Text(0, 0, '1637'),\n",
              " Text(0, 0, '1668'),\n",
              " Text(0, 0, '1671'),\n",
              " Text(0, 0, '1688'),\n",
              " Text(0, 0, '1715'),\n",
              " Text(0, 0, '1716'),\n",
              " Text(0, 0, '1723'),\n",
              " Text(0, 0, '1724'),\n",
              " Text(0, 0, '1740'),\n",
              " Text(0, 0, '1741'),\n",
              " Text(0, 0, '1749'),\n",
              " Text(0, 0, '1751'),\n",
              " Text(0, 0, '1753'),\n",
              " Text(0, 0, '1753'),\n",
              " Text(0, 0, '1766'),\n",
              " Text(0, 0, '1768'),\n",
              " Text(0, 0, '1768'),\n",
              " Text(0, 0, '1773'),\n",
              " Text(0, 0, '1775'),\n",
              " Text(0, 0, '1776'),\n",
              " Text(0, 0, '1781'),\n",
              " Text(0, 0, '1784'),\n",
              " Text(0, 0, '1784'),\n",
              " Text(0, 0, '1785'),\n",
              " Text(0, 0, '1787'),\n",
              " Text(0, 0, '1790'),\n",
              " Text(0, 0, '1792'),\n",
              " Text(0, 0, '1793'),\n",
              " Text(0, 0, '1794'),\n",
              " Text(0, 0, '1795'),\n",
              " Text(0, 0, '1795'),\n",
              " Text(0, 0, '1796'),\n",
              " Text(0, 0, '1796'),\n",
              " Text(0, 0, '1797'),\n",
              " Text(0, 0, '1798'),\n",
              " Text(0, 0, '1798'),\n",
              " Text(0, 0, '1801'),\n",
              " Text(0, 0, '1803'),\n",
              " Text(0, 0, '1803'),\n",
              " Text(0, 0, '1803'),\n",
              " Text(0, 0, '1804'),\n",
              " Text(0, 0, '1804'),\n",
              " Text(0, 0, '1804'),\n",
              " Text(0, 0, '1804'),\n",
              " Text(0, 0, '1804'),\n",
              " Text(0, 0, '1805'),\n",
              " Text(0, 0, '1805'),\n",
              " Text(0, 0, '1805')]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 86
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bbSCMNe6Dw7X",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 476
        },
        "outputId": "c65650d6-2289-4ffb-92b9-c756fa0bc89b"
      },
      "source": [
        "#Plotting Meteorite Landings fell and found\n",
        "%matplotlib inline\n",
        "fig, ax = plt.subplots(2,1, sharex=True,sharey=True,figsize=(10,7))\n",
        "ax[0].hist(data['year'][data['fall']=='Fell'])\n",
        "ax[1].hist(data['year'][data['fall']=='Found'])\n",
        "for i in range(2):\n",
        "  ax[i].set_xlabel('Year')\n",
        "  ax[i].set_ylabel('Count')\n",
        "ax[0].set_title('Plot showing most of the Meteorite landings (fell) has been in recent centuries')\n",
        "ax[1].set_title('Plot showing most of the Meteorite landings (found) has been in recent centuries')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Plot showing most of the Meteorite landings (found) has been in recent centuries')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kef4tW65HYSP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "outputId": "1039ff72-0955-4e77-80c1-1068b8082cd8"
      },
      "source": [
        "#Relation between Year and Mass in 21st century\n",
        "twenty = data[data['year']>2000]\n",
        "fig = plt.figure(figsize=(20,5))\n",
        "sns.barplot(x= twenty['year'].head(20000),y=twenty['mass'].head(20000))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f4e233dd5f8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 88
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Rr17GwXLJQok",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        },
        "outputId": "923d1e05-ed41-46db-80f7-c98e1f194f18"
      },
      "source": [
        "#Plotting Histogram for frequency of Meteorite Landings in 21st Century\n",
        "%matplotlib inline\n",
        "fig = plt.figure(figsize=(20,5))\n",
        "ax = fig.add_axes([0,0,1,1])\n",
        "ax.hist(twenty['year'])\n",
        "ax.set_xlabel('Year')\n",
        "ax.set_ylabel('Count')\n",
        "ax.set_title('Plot showing most of the Meteorite landings (fell or found) has been in 21st century')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Plot showing most of the Meteorite landings (fell or found) has been in 21st century')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 89
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1XZyWAkSK3p4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 408
        },
        "outputId": "f8f52192-3aee-4d26-d507-8c1a26b48824"
      },
      "source": [
        "fig = plt.figure(figsize=(10,5))\n",
        "sns.distplot(twenty['year'])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f4e23489668>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 90
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 689
        },
        "id": "zm-tdBsBJChW",
        "outputId": "74d732c5-868b-4486-8c5d-9724e5ed222f"
      },
      "source": [
        "import folium\n",
        "folium.Map()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" data-html=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 onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
            ],
            "text/plain": [
              "<folium.folium.Map at 0x7f4e229bf5f8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 92
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 198
        },
        "id": "RyWXtEl_JGzO",
        "outputId": "042305d0-c5e2-4534-f0ac-7d8fe10460e0"
      },
      "source": [
        "data.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>id</th>\n",
              "      <th>nametype</th>\n",
              "      <th>recclass</th>\n",
              "      <th>mass</th>\n",
              "      <th>fall</th>\n",
              "      <th>year</th>\n",
              "      <th>reclat</th>\n",
              "      <th>reclong</th>\n",
              "      <th>GeoLocation</th>\n",
              "      <th>scaled_mass</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Wietrzno-Bobrka</td>\n",
              "      <td>24259</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron</td>\n",
              "      <td>376.0</td>\n",
              "      <td>Found</td>\n",
              "      <td>601</td>\n",
              "      <td>49.41667</td>\n",
              "      <td>21.70000</td>\n",
              "      <td>(49.416670, 21.700000)</td>\n",
              "      <td>0.000006</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Nogata</td>\n",
              "      <td>16988</td>\n",
              "      <td>Valid</td>\n",
              "      <td>L6</td>\n",
              "      <td>472.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>860</td>\n",
              "      <td>33.72500</td>\n",
              "      <td>130.75000</td>\n",
              "      <td>(33.725000, 130.750000)</td>\n",
              "      <td>0.000008</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Elbogen</td>\n",
              "      <td>7823</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Iron, IID</td>\n",
              "      <td>107000.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1399</td>\n",
              "      <td>50.18333</td>\n",
              "      <td>12.73333</td>\n",
              "      <td>(50.183330, 12.733330)</td>\n",
              "      <td>0.001783</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Rivolta de Bassi</td>\n",
              "      <td>22614</td>\n",
              "      <td>Valid</td>\n",
              "      <td>Stone-uncl</td>\n",
              "      <td>103.3</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1490</td>\n",
              "      <td>45.48333</td>\n",
              "      <td>9.51667</td>\n",
              "      <td>(45.483330, 9.516670)</td>\n",
              "      <td>0.000002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Ensisheim</td>\n",
              "      <td>10039</td>\n",
              "      <td>Valid</td>\n",
              "      <td>LL6</td>\n",
              "      <td>127000.0</td>\n",
              "      <td>Fell</td>\n",
              "      <td>1491</td>\n",
              "      <td>47.86667</td>\n",
              "      <td>7.35000</td>\n",
              "      <td>(47.866670, 7.350000)</td>\n",
              "      <td>0.002117</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               name     id  ...              GeoLocation scaled_mass\n",
              "0   Wietrzno-Bobrka  24259  ...   (49.416670, 21.700000)    0.000006\n",
              "1            Nogata  16988  ...  (33.725000, 130.750000)    0.000008\n",
              "2           Elbogen   7823  ...   (50.183330, 12.733330)    0.001783\n",
              "3  Rivolta de Bassi  22614  ...    (45.483330, 9.516670)    0.000002\n",
              "4         Ensisheim  10039  ...    (47.866670, 7.350000)    0.002117\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oHIPyLXeKBFW"
      },
      "source": [
        "gel = data.iloc[:100,:]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vt6ESN4UJilj"
      },
      "source": [
        "met = folium.Map()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zFCj-X8DJtjW"
      },
      "source": [
        "metf = folium.map.FeatureGroup()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sq2-dDAdJ6Td"
      },
      "source": [
        "for lat,lng in zip(gel.reclat,gel.reclong):\n",
        "  metf.add_child(folium.features.Marker([lat,lng]))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "PldyMm57LPzC",
        "outputId": "71a2bfa6-1f5d-49ad-ca23-77647e3f761c"
      },
      "source": [
        "met.add_child(metf)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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        "id": "ippBR5goL24X"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}