Electric_Vehicles_Market_Size_Analysis.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyPJ9Z7koWfnGD4oKpxu6yxP",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/RSN601KRI/Electric-Vehicles-Market-Size-Analysis/blob/master/Electric_Vehicles_Market_Size_Analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "r9qFKwFphtU_"
      },
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ev_data = pd.read_csv('Electric_Vehicle_Population_Data.csv')"
      ],
      "metadata": {
        "id": "acbQ6R3eiMGs"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(ev_data.head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vheLRkOaiSxm",
        "outputId": "22a343f6-bf95-4fc3-86b4-4d0d26071959"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   VIN (1-10)     County       City State  Postal Code  Model Year   Make  \\\n",
            "0  5YJYGDEE1L       King    Seattle    WA        98122        2020  TESLA   \n",
            "1  7SAYGDEE9P  Snohomish    Bothell    WA        98021        2023  TESLA   \n",
            "2  5YJSA1E4XK       King    Seattle    WA        98109        2019  TESLA   \n",
            "3  5YJSA1E27G       King   Issaquah    WA        98027        2016  TESLA   \n",
            "4  5YJYGDEE5M     Kitsap  Suquamish    WA        98392        2021  TESLA   \n",
            "\n",
            "     Model           Electric Vehicle Type  \\\n",
            "0  MODEL Y  Battery Electric Vehicle (BEV)   \n",
            "1  MODEL Y  Battery Electric Vehicle (BEV)   \n",
            "2  MODEL S  Battery Electric Vehicle (BEV)   \n",
            "3  MODEL S  Battery Electric Vehicle (BEV)   \n",
            "4  MODEL Y  Battery Electric Vehicle (BEV)   \n",
            "\n",
            "   Clean Alternative Fuel Vehicle (CAFV) Eligibility  Electric Range  \\\n",
            "0            Clean Alternative Fuel Vehicle Eligible           291.0   \n",
            "1  Eligibility unknown as battery range has not b...             0.0   \n",
            "2            Clean Alternative Fuel Vehicle Eligible           270.0   \n",
            "3            Clean Alternative Fuel Vehicle Eligible           210.0   \n",
            "4  Eligibility unknown as battery range has not b...             0.0   \n",
            "\n",
            "   Base MSRP  Legislative District  DOL Vehicle ID  \\\n",
            "0        0.0                  37.0     125701579.0   \n",
            "1        0.0                   1.0     244285107.0   \n",
            "2        0.0                  36.0     156773144.0   \n",
            "3        0.0                   5.0     165103011.0   \n",
            "4        0.0                  23.0     205138552.0   \n",
            "\n",
            "                Vehicle Location  \\\n",
            "0   POINT (-122.30839 47.610365)   \n",
            "1  POINT (-122.179458 47.802589)   \n",
            "2   POINT (-122.34848 47.632405)   \n",
            "3   POINT (-122.03646 47.534065)   \n",
            "4   POINT (-122.55717 47.733415)   \n",
            "\n",
            "                                Electric Utility  2020 Census Tract  \n",
            "0   CITY OF SEATTLE - (WA)|CITY OF TACOMA - (WA)       5.303301e+10  \n",
            "1                         PUGET SOUND ENERGY INC       5.306105e+10  \n",
            "2   CITY OF SEATTLE - (WA)|CITY OF TACOMA - (WA)       5.303301e+10  \n",
            "3  PUGET SOUND ENERGY INC||CITY OF TACOMA - (WA)       5.303303e+10  \n",
            "4                         PUGET SOUND ENERGY INC       5.303594e+10  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ev_data.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "j3hEDimCiTr4",
        "outputId": "5dc11098-d392-4661-8f04-a02976b500ec"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 17437 entries, 0 to 17436\n",
            "Data columns (total 17 columns):\n",
            " #   Column                                             Non-Null Count  Dtype  \n",
            "---  ------                                             --------------  -----  \n",
            " 0   VIN (1-10)                                         17437 non-null  object \n",
            " 1   County                                             17437 non-null  object \n",
            " 2   City                                               17437 non-null  object \n",
            " 3   State                                              17437 non-null  object \n",
            " 4   Postal Code                                        17437 non-null  int64  \n",
            " 5   Model Year                                         17437 non-null  int64  \n",
            " 6   Make                                               17437 non-null  object \n",
            " 7   Model                                              17437 non-null  object \n",
            " 8   Electric Vehicle Type                              17437 non-null  object \n",
            " 9   Clean Alternative Fuel Vehicle (CAFV) Eligibility  17437 non-null  object \n",
            " 10  Electric Range                                     17436 non-null  float64\n",
            " 11  Base MSRP                                          17436 non-null  float64\n",
            " 12  Legislative District                               17436 non-null  float64\n",
            " 13  DOL Vehicle ID                                     17436 non-null  float64\n",
            " 14  Vehicle Location                                   17436 non-null  object \n",
            " 15  Electric Utility                                   17436 non-null  object \n",
            " 16  2020 Census Tract                                  17436 non-null  float64\n",
            "dtypes: float64(5), int64(2), object(10)\n",
            "memory usage: 2.3+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ev_data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SVlhlU1uiXtZ",
        "outputId": "11789e23-05e2-4791-cf29-496d4ce5c34a"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "VIN (1-10)                                           0\n",
              "County                                               0\n",
              "City                                                 0\n",
              "State                                                0\n",
              "Postal Code                                          0\n",
              "Model Year                                           0\n",
              "Make                                                 0\n",
              "Model                                                0\n",
              "Electric Vehicle Type                                0\n",
              "Clean Alternative Fuel Vehicle (CAFV) Eligibility    0\n",
              "Electric Range                                       1\n",
              "Base MSRP                                            1\n",
              "Legislative District                                 1\n",
              "DOL Vehicle ID                                       1\n",
              "Vehicle Location                                     1\n",
              "Electric Utility                                     1\n",
              "2020 Census Tract                                    1\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ev_data = ev_data.dropna()"
      ],
      "metadata": {
        "id": "Om0YNxRRibX2"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "ZOUcWv37ieyI"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "sns.set_style(\"whitegrid\")"
      ],
      "metadata": {
        "id": "5cP00kFXikE6"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# EV Adoption Over Time\n",
        "plt.figure(figsize=(12, 6))\n",
        "ev_adoption_by_year = ev_data['Model Year'].value_counts().sort_index()\n",
        "sns.barplot(x=ev_adoption_by_year.index, y=ev_adoption_by_year.values, palette=\"viridis\")\n",
        "plt.title('EV Adoption Over Time')\n",
        "plt.xlabel('Model Year')\n",
        "plt.ylabel('Number of Vehicles Registered')\n",
        "plt.xticks(rotation=45)\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "dXnF-en4imez",
        "outputId": "36a5904f-fc71-4793-9913-3d973f5e1445"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-9-80a460a6be95>:4: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  sns.barplot(x=ev_adoption_by_year.index, y=ev_adoption_by_year.values, palette=\"viridis\")\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
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79l++fLkOHjzokVndJSNz7ty5Vbp0aUnXzrFz+PBhTZkyRR06dFBMTIw6deqkfPnyecU7tV3/9W0YhgICAhQeHu54x6rFixfLx8dHRYoU0cSJEyXJKwqp69+5pnv37urRo4cCAwPVrVs33XffffL19VWVKlXUpEkTHT161Ot+lkVFRenxxx/XpEmTFBcXp6CgINntdqWnp6tly5aqUKGCduzY4cFp3SfjL8jXnwQ5Y5VjeHi4HnnkEa1du1aXL1/2mnOnXZ+jQ4cOatmypWJjYxUbG6uePXuqWbNmqlChgp544glVrVpVGzZs8OC07pOR29/fX7Vr19b+/fvVtWtXTZgwQc2bN1ejRo300EMPKSoqSidPnnT8nPMWNWrU0JUrVyzzuiNHjhxObyrUqlUrtWvXTrt27dLs2bMdK6Y+/PBD7d6920NTup8VX2+VKFHCsfIxNTVV27dv18SJE9W1a1f17NlTbdq0UUpKiuLj4z08qfulpaUpICBABQsW1MWLFxUUFKSNGzfq6tWrKlmypBYvXixJpp30PPs/A/RyR48e1c8//yybzabChQurbt26atq0qbZu3aqFCxcqR44catq0qeNwp4iICAUFBenixYueHfwOXJ/5nnvuUb169W7Yx2azOb04nzBhgpYuXapFixaZOarb3Cxz7dq1Vbt2bZ05c0bPP/+87rnnHknXflHY7XaFhIRk+9VC58+fV+7cuR1vQ5rxgu2RRx7RV199pZkzZ6pDhw6O7KVLl1ZwcHC2Ppno9Zn/vuopo5ypX7++bDab5syZo6lTpypHjhxau3atoqOjPTj5ncnI7evre8OKmOv/0nj9oWvvvfee5syZ4zhUNbu5PvP1f2nKKGmGDh3q9HVgs9lUsGBBp8MkspubfX1nPL5lypTRrl279NVXX2nTpk2aPn26zp49q759++rVV1/V+++/79nh78A/PdbdunXTww8/7CgjMz4nhQoVUv78+bP1aoqbPdY+Pj5q0KCBDh48qLi4OMXHxztK9/T0dAUHByt37twenvzOZOT29/e/6cpVm82mkJAQ1alTRxMmTNArr7yikiVLZutVFTf7XV2iRAkNGjRIV65cUdu2bRUaGirpWjGb8TMuu7+T6vW5M35vdejQQXny5NEvv/yiQ4cO6dVXX1WHDh0kXVtJld1XC508eVJ//vmn0tLSVKRIEUVERKhp06bavHmzFi1a5JWvO67PXLRoUce7IBv//0TXPj4+judfc+bM0ezZs5WcnKw1a9aocePGHp7+9t3ssZbk9DvM215v/dNjbbfbFRAQoKlTpzr9TsubN68KFCjgWEmVXV2fu1ixYqpUqZLjD8CVKlVSfHy8Fi1apC1btmjq1Knau3evpk+fLj8/P/Xr18+UGSml7mJ79uxR+/btVapUKZ0+fVqJiYlq3Lix3nrrLb399tt66623tGDBAh06dEht27ZVSEiIli1bJpvNlm0PB7hZ5mbNmqlnz54qVKiQ4wnd5cuXdfr0aV29elX//e9/9cknn2jevHkqWrSohxO47maZmzRpoldffVWFChVSvnz5FBYWpl9++UWVKlVS7ty5NWPGDJ08eVIPPfSQp8e/bXFxcerSpYtatGihXr16ydfXV2lpafL391eXLl10+fJlbdiwQQcOHNCrr76qoKAgLVmyRGlpabr33ns9Pf5t+XvmvxdTGU+CbDab6tWrJ7vdrjfffFOGYWj58uVOK6qyk7/n9vPzu+mLuStXrjiWiE+fPl2zZs3S/PnzVapUKfOHvkM3+/r+e0mT8f+Mz8PixYtlt9sdBUZ2c6uv7zx58mjcuHEqWbKkpk2bpkqVKik1NVVjx47Nlo9xhps91tc/qa9QoYJj34zPxTfffKM8efI4nT8vO7nZY53xor1JkyZKTU3VlClT1KZNG40ZM0Y5c+bUpk2bdPToUcchydnRrb7Gpf/740Lbtm315Zdf6sMPP9Q777zjtAI0O7nV13eOHDlUrlw5rVq1StWrV1fOnDk1d+5cHTx4UMOGDfPw9LfvZr+3UlNTFRAQoJYtW6ply5aO5ywZNmzYoIIFC2bbx3rPnj165ZVXlC9fPh05ckTFihXTCy+8oGbNmmnIkCHq37+/V77u+HvmF198UY0bN5bNZnOs1s8opux2u4YMGaLAwEAtXbrUscomu/m33NevjPG211u3yvz352X/+9//lCNHjmyZN8O/5ZaulekDBgxQsWLFHM/NwsPDZbPZVLduXdPmtBnecrZJL3Px4kV16tRJlStX1sCBA5WQkKBdu3bpjTfeUIUKFRzHrk+ePFkbN27U1q1bVbFiRZ06dUrTp09XxYoVPR3BZf+WOSIiQoMGDXKUERcvXnT8Qvz99981f/58Va5c2cMJXJfZzFOmTNHatWt17NgxlS1bVgcOHNC0adOy5eMsScePH1e3bt106dIlBQQEqFGjRurevbskOZ70SdLSpUu1evVqrV+/XmXLltXFixc1efLkbJn73zLf7EWNYRgaPXq0lixZooULF6pcuXKeGv2OuJI7PT1dbdu21fnz53X06FHNmTPH8Ze77MSVzNK1k6p+9tlnWrZsmWbPnp0ty8d/y3z9C9hx48apcePG2fLn9c1kNneGuLg4ffbZZ1q+fLlXPtbX//z+9ddftWTJEq1Zs0ZFixaVr6+vRo8enS1/fkuuf19L0ttvv609e/bok08+UXBwsNkj37HMZl6xYoUWL16sbdu2qVKlSjp16pQ+/PBDr3ysr1/pm1FA/vbbb/riiy/0v//9T/PmzcuW39fx8fFq166dmjdvrpdeekmHDx/W3Llz5ePjoyFDhji+r73pdce/ZR4+fLjTH5EMw1B6erpGjRqlFStWaN68eU5vRpSduJLbW15vuZJZko4dO6a5c+dqyZIl2fZ3tfTvuYcNGyY/Pz9dvXpV77zzjqKjo1WlShXHzzXTz2Gb5e/vh9ty+fJlIzo62vjyyy+dth84cMCoVauW0bVrV8e2xMREY926dcavv/6ard+G91aZX375ZePq1auGYRjG2bNnjUceecR44IEHjF27dnliXLe4VeaXXnrJse2HH34wpk+fbixYsMCIj483e1S3SU9PN6ZPn268+OKLxoYNG4yJEycajRs3NiZNmuTY58qVK07X+f333419+/YZp06dMntct8hM5oyv7Qy7d+826tata+zYscPscd3G1dxpaWlG69atjZo1a2bb72tXM+/du9cYN26c0apVK6/O7I1vJ+3qY717925j5MiRRvPmzb36sf77z+9Dhw4ZCQkJxpkzZ0ye1n1u52e4YRjGhQsXsu3v68xkznjbeMMwjD179hiLFy821qxZY/z111+eGNktXH2s7Xa78e233xqtW7fOtt/XV65cMUaNGmX06tXL6ft38eLFxgMPPGCcPn3aaf/Tp09n+9cdrmY2jGvPRcPDw43t27ebOapbuZr7/Pnz2f71lquZt2/fbgwZMsRo0aJFts1sGLf3Ne5JHL53l7Lb7UpMTNSBAwcc29LS0nTffffpk08+0XPPPafJkyere/fuKlCgwE3Pu5TdZCbztGnT9PLLLytPnjyKiYnRY489prCwMA9OfWcyk3nSpEnq0aOH6tevr/r163twWvew2Wxq2bKlQkND9dBDDzn++vDll19KunZy4ICAAKdl8VWqVPHYvO6QmczXH94lXXsXwlWrVmXr81O4mtvPz0/PPPOMatSooZIlS3py9NvmauayZcuqRYsW6tixY7Y9/CEzmXPkyGHaO7iYxdXHOjw8XC1btlTnzp2z7fkAM/vz+/rVJPfee2+2PZdShtv5GX716lWFhIRk25/hmcns7+/v+F1drly5bLui93quPtY+Pj567LHHVKtWrWz7WBuGocKFCyssLEwBAQGOlRJVq1ZVzpw5HSduz8icL1++bP+6I7OZr1elShVt3rw5W58Xz9XcuXLl0jPPPKOGDRtm29dbrmaOiIjQlStX1K1bNxUqVMhDU9+52/ka9+g7fHuqDcOtffzxx0a9evWM7777zrEt469S//3vf41nnnnGOHPmjGG32z01ottlJnNSUpKnxssSmcl8+vRpx+Ocnp7ukTmz0smTJ2/618hvvvnmpn999gb/ljnj8bfSY71mzRoPTpW1yOz89e1Nv7P+jseax9qbc1vxd7VhWCP39Sv6Mp57nDp1ymjQoIFx7Ngxx2V//PGH6bNlldvJ7A3PyzKbOzuvCPu7zGbOzkcn3Ex2+r5mpdRd4tSpUzpx4oTOnTunOnXqyNfXVw0aNFBsbKw++ugj+fv7KyoqyrFyJF++fEpOTlaOHDmy7VvE327m7PxuRbebOTAw0Olk2NnNzXJL1xp5m82mQoUK6dlnn5V07a+RhmHowoULmj17ttatW+d4973sxB2ZeayzBzJbI7NkzdxWzCxZM7cVM0vWzJ2R+ezZs4qKilKJEiUkOZ8L78KFCzp37pzjOh988IHmzZunNWvWKG/evNnuOYoVM0vWzG3FzFL2zk0pdRfYvXu3Xn75Zfn7+yspKUmhoaHq0aOHGjZsqM6dO+vDDz/U+++/r3PnzqlZs2ZKS0vTkSNHVKBAAdntdk+Pf1vIbI3M0o25CxYsqFdeeUVRUVHKmzev0tPTJUn33HOPWrduLcMw9OGHHyp37txasmRJtnyyZ8XMkjVzk9kamSVr5rZiZsmaua2YWbJm7ltlNv7/YT42m00+Pj4KDg7Wf//7X3388ceaN2+e8uXL5+kILrNiZsmaua2YWfKC3KatycJNJSUlGY0bNzYmTJhgxMfHGydOnDBeffVVo2HDhsakSZOMK1euGLt27TIGDRpkVKxY0WjRooXx7LPPGjVr1jT+/PNPT49/W8hsjcyG8c+5mzRpYkycONFxKOb1y6HfeOMNo1q1asa+ffs8NfYdsWJmw7BmbjJbI7NhWDO3FTMbhjVzWzGzYVgzd2YzG8a1N1Jq2bKl8eqrrxqVKlXKtoc2WTGzYVgztxUzG4Z35KaU8rB9+/YZjzzyyA1fEO+++67RrFkzY+bMmUZ6erpx8eJFY9u2bcaHH35oLFiwwDh06JCHJr5zZP4/3pzZMP49d/PmzY0ZM2YYKSkpju2LFi0yatSocVcc23y7rJjZMKyZm8z/x5szG4Y1c1sxs2FYM7cVMxuGNXO7knn//v1GeHi4UaVKlWz9B1IrZjYMa+a2YmbD8I7cHL7nYVevXpXdbtfly5clSZcvX1ZgYKD69Omjy5cva+7cuapTp47Kly+vyMhIRUZGenZgNyCzNTJLt869YMECRUVFOd7d5pFHHtGDDz7oOAY6O7JiZsmauclsjcySNXNbMbNkzdxWzCxZM7crmXPnzq3nn39ebdq0ybbvvCZZM7NkzdxWzCx5R26bYRiGp4ewuqefflrBwcGaPXu2JCk1NVUBAQGSpFatWqlkyZKaMGGCJ0d0OzJbI7OU+dze9HbxVswsWTM3ma2RWbJmbitmlqyZ24qZJWvmduX56JUrV5QjRw6PzeouVswsWTO3FTNL2T939nzbtmwsJSVFycnJSk5OdmwbNmyY9u/fr969e0uSAgICdPXqVUlSzZo1lZKS4pFZ3YXM13h7ZunOcmfXJ3tWzCxZMzeZr/H2zJI1c1sxs2TN3FbMLFkz950+H73bXrhmhhUzS9bMbcXMknfmppQy0f79+9WjRw+1a9dOTZo00YoVKyRJYWFheuutt/TTTz+pZ8+eSktLk4/PtYcmKSlJwcHBunr1qrLjojYyWyOzZM3cVswsWTM3ma2RWbJmbitmlqyZ24qZJWvmJrM1MkvWzG3FzJL35ubwPZPs379fbdq0UcuWLVW5cmX98ccfmjt3rhYtWqSKFSvq0qVL2rhxo4YOHarg4GCVLl1a/v7+WrdunT777DOVK1fO0xFcRmZrZJasmduKmSVr5iazNTJL1sxtxcySNXNbMbNkzdxktkZmyZq5rZhZ8u7clFImOHv2rHr37q377rtPAwcOdGxv166dwsPDnbYlJydrypQpOnfunHLkyKHnnntOZcqU8cTYd4TM1sgsWTO3FTNL1sxNZmtklqyZ24qZJWvmtmJmyZq5yWyNzJI1c1sxs+T9uXn3PRNcvXpV58+fV+PGjSVJ6enp8vHxUfHixXX27FlJkmEYMgxDISEheuONN5z2y47IbI3MkjVzWzGzZM3cZLZGZsmaua2YWbJmbitmlqyZm8zWyCxZM7cVM0ven/vun9ALhIaG6t1331WNGjUkSXa7XZJ0zz33OL5IbDabfHx8nE5YZrPZzB/WTchsjcySNXNbMbNkzdxktkZmyZq5rZhZsmZuK2aWrJmbzNbILFkztxUzS96fm1LKJKVKlZJ0ra309/eXdK3NTEpKcuwzbdo0LV682HGm/OzyRfRPyGyNzJI1c1sxs2TN3GS2RmbJmrmtmFmyZm4rZpasmZvM1sgsWTO3FTNL3p2bUspkPj4+Tme9z2g2P/jgA7333nuqXbu2/Py866hKMlsjs2TN3FbMLFkzN5mtkVmyZm4rZpasmduKmSVr5iazNTJL1sxtxcySd+amlPKAjC8iPz8/FSlSRDNnztRHH32kzz//XOXLl/fwdFmDzNbILFkztxUzS9bMTWZrZJasmduKmSVr5rZiZsmauclsjcySNXNbMbPkfbmzV4XmJTLaTD8/Py1atEghISGaP3++KlWq5OHJsg6ZrZFZsmZuK2aWrJmbzNbILFkztxUzS9bMbcXMkjVzk9kamSVr5rZiZsn7crNSyoOioqIkSQsXLlRERISHpzEHma2RWbJmbitmlqyZm8zWyCxZM7cVM0vWzG3FzJI1c5PZGpkla+a2YmbJe3LbjOsPSITpUlJSFBwc7OkxTEVm67BibitmlqyZm8zWYcXcVswsWTO3FTNL1sxNZuuwYm4rZpa8IzelFAAAAAAAAEzH4XsAAAAAAAAwHaUUAAAAAAAATEcpBQAAAAAAANNRSgEAAAAAAMB0lFIAAAAAAAAwHaUUAAAAAAAATEcpBQAAcBfZtGmTwsPDdf78+Uxf59FHH9Unn3ySdUMBAABkAUopAACATOrXr5/Cw8M1aNCgGy4bOnSowsPD1a9fPw9M9s8GDBigJ554QqmpqU7b161bp8qVK+uPP/7w0GQAAMDqKKUAAABcUKRIEa1atUqXL192bLty5Yq++OILFS1a1IOT3dyAAQN08eJFTZo0ybHt/PnzGjhwoLp166ZKlSq5/T7T0tLcfpsAAMD7UEoBAAC4oGLFiipSpIi+/vprx7avv/5aRYoUUYUKFZz2TU1N1YgRI1S7dm1FREToueee0/bt2532WbdunRo1aqQqVaqoXbt2+uuvv264z19//VXPP/+8qlSpovr162vEiBFKSUnJ1LwhISEaOXKkZs2apd9//12SNHLkSN1zzz3q2rWrjh8/rl69eqlGjRp64IEH1K1bNx09etRx/e3bt+s///mPatWqperVq6tt27Y3rK4KDw/X/Pnz9dJLLykyMlJTp07N1GwAAMDaKKUAAABc1KpVKy1dutTx8eeff66nnnrqhv3Gjh2rNWvWaPTo0Vq2bJlKliypzp076+zZs5Kk48ePq3v37nrkkUe0fPlyPfPMMxo/frzTbcTHx+vFF19Uw4YNtWLFCr333nvaunWrhg8fnul5H3zwQT333HN68803tXr1aq1evVpjxoyRYRjq1KmTcubMqXnz5mnBggUKDg5W586dHYf7Xbx4US1bttT8+fO1aNEilSxZUl26dFFycrLTfUyePFkNGjTQypUr1apVq0zPBgAArItSCgAAwEUtWrTQ1q1b9ddff+mvv/7Sb7/9phYtWjjtk5KSooULF6pv376qX7++ypQpo+HDhytHjhxasmSJJGnBggW699571a9fP5UuXVotWrRQdHS00+1MmzZNTzzxhDp27KhSpUqpWrVqeuutt7R8+XJduXIl0zP37t1bkvT666/rtddeU1hYmFatWqX09HS98847Cg8PV1hYmEaNGqXjx49r8+bNkqTatWvrySefVFhYmMLCwjR8+HBdunRJW7Zscbr95s2bq1WrVipRosRdeRgjAAC4+/h5egAAAIDsJn/+/Hr44Ye1bNkyGYahhx9+WPnz53faJz4+XmlpaapWrZpjm7+/v6pUqaK4uDhJUlxcnKpUqeJ0vcjISKePd+/erT179mjlypWObYZhKD09XUePHlVYWFimZg4MDFSnTp00cuRIdejQwXHb8fHxTjNK186RFR8fL0lKTEzU+++/r82bNyspKUnp6em6dOmSjh075nSdypUrZ2oOAACADJRSAAAAt6FVq1YaNmyYJGnw4MFZdj8pKSmKiYlRu3btbrisSJEiLt2Wr6+vfH19ZbPZHLddqVIljRs37oZ9M0q2N998U2fPntVbb72lokWLKiAgQK1bt77hZObBwcEuzQIAAEApBQAAcBvq1q2rtLQ02Ww2RUVF3XD5vffeK39/f/32228qVqyYpGvvSrdjxw7HSqWwsDB99913TtfLOBl5hooVK2r//v0qWbKk2zNUqlRJq1evVoECBRQSEnLTfX777TcNHjxY9evXl3TtPFhnzpxx+ywAAMB6OKcUAADAbfD19dXq1au1atUq+fr63nB5cHCwnnvuOY0dO1Y//vij9u/fr7fffluXL1/W008/LUmKiYnRoUOHNGbMGB04cEArV67UsmXLnG7nxRdf1LZt2zRs2DDt2rVLhw4d0rfffutYpXUnnnjiCeXLl0/dunXTr7/+qiNHjmjTpk0aMWKETpw4IUkqVaqUVqxYobi4OP3+++/q06ePAgMD7/i+AQAAKKUAAABuU0hIyD+uMJKkPn36qFGjRurbt6+io6N1+PBhffTRR8qTJ48kqWjRopo0aZLWrl2rJ598UgsXLtRrr73mdBvly5fXnDlzdOjQIT3//POKjo7WxIkTVahQoTuePygoSHPnzlXRokXVvXt3NW3aVG+99ZauXLniyPXOO+/o3Llzio6OVt++fdWuXTsVKFDgju8bAADAZhiG4ekhAAAAAAAAYC2slAIAAAAAAIDpKKUAAAAAAABgOkopAAAAAAAAmI5SCgAAAAAAAKajlAIAAAAAAIDpKKUAAAAAAABgOkopAAAAAAAAmI5SCgAAAAAAAKajlAIAAAAAAIDpKKUAAAAAAABgOkopAAAAAAAAmI5SCgAAAAAAAKb7f05GwHr5l1hTAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# geographical distribution at county level\n",
        "ev_county_distribution = ev_data['County'].value_counts()\n",
        "top_counties = ev_county_distribution.head(3).index"
      ],
      "metadata": {
        "id": "pXuiFWYOitfC"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# filtering the dataset for these top counties\n",
        "top_counties_data = ev_data[ev_data['County'].isin(top_counties)]"
      ],
      "metadata": {
        "id": "jaoDfuPTiyEd"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# analyzing the distribution of EVs within the cities of these top counties\n",
        "ev_city_distribution_top_counties = top_counties_data.groupby(['County', 'City']).size().sort_values(ascending=False).reset_index(name='Number of Vehicles')"
      ],
      "metadata": {
        "id": "CAaTqVB1i03-"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# visualize the top 10 cities across these counties\n",
        "top_cities = ev_city_distribution_top_counties.head(10)"
      ],
      "metadata": {
        "id": "sZjDEzxri4uS"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12, 8))\n",
        "sns.barplot(x='Number of Vehicles', y='City', hue='County', data=top_cities, palette=\"magma\")\n",
        "plt.title('Top Cities in Top Counties by EV Registrations')\n",
        "plt.xlabel('Number of Vehicles Registered')\n",
        "plt.ylabel('City')\n",
        "plt.legend(title='County')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 757
        },
        "id": "gF5qA5y9i7sA",
        "outputId": "8699e3d5-0ad4-4104-bf82-21414c595442"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# analyzing the distribution of electric vehicle Types\n",
        "ev_type_distribution = ev_data['Electric Vehicle Type'].value_counts()"
      ],
      "metadata": {
        "id": "evXU7Bpli-hd"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10, 6))\n",
        "sns.barplot(x=ev_type_distribution.values, y=ev_type_distribution.index, palette=\"rocket\")\n",
        "plt.title('Distribution of Electric Vehicle Types')\n",
        "plt.xlabel('Number of Vehicles Registered')\n",
        "plt.ylabel('Electric Vehicle Type')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 714
        },
        "id": "p9l9JXrCjChW",
        "outputId": "e090add0-2da0-4cdb-99be-8423e8aaafe7"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-16-b5f1f7d74943>:2: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  sns.barplot(x=ev_type_distribution.values, y=ev_type_distribution.index, palette=\"rocket\")\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# analyzing the popularity of EV manufacturers\n",
        "ev_make_distribution = ev_data['Make'].value_counts().head(10)  # Limiting to top 10 for clarity"
      ],
      "metadata": {
        "id": "kpenXrjwjEyK"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12, 6))\n",
        "sns.barplot(x=ev_make_distribution.values, y=ev_make_distribution.index, palette=\"cubehelix\")\n",
        "plt.title('Top 10 Popular EV Makes')\n",
        "plt.xlabel('Number of Vehicles Registered')\n",
        "plt.ylabel('Make')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "9qwBnPByjJty",
        "outputId": "a8138c93-0869-49ba-da8e-6ddca93cce24"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-18-80ec777523b9>:2: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `y` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  sns.barplot(x=ev_make_distribution.values, y=ev_make_distribution.index, palette=\"cubehelix\")\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# selecting the top 3 manufacturers based on the number of vehicles registered\n",
        "top_3_makes = ev_make_distribution.head(3).index"
      ],
      "metadata": {
        "id": "UPgh15lyjMHL"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# filtering the dataset for these top manufacturers\n",
        "top_makes_data = ev_data[ev_data['Make'].isin(top_3_makes)]"
      ],
      "metadata": {
        "id": "IWmBINmbjPxS"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# analyzing the popularity of EV models within these top manufacturers\n",
        "ev_model_distribution_top_makes = top_makes_data.groupby(['Make', 'Model']).size().sort_values(ascending=False).reset_index(name='Number of Vehicles')"
      ],
      "metadata": {
        "id": "3u2Xdby9jT8s"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# visualizing the top 10 models across these manufacturers for clarity\n",
        "top_models = ev_model_distribution_top_makes.head(10)"
      ],
      "metadata": {
        "id": "tVIg7H3HjXaX"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12, 8))\n",
        "sns.barplot(x='Number of Vehicles', y='Model', hue='Make', data=top_models, palette=\"viridis\")\n",
        "plt.title('Top Models in Top 3 Makes by EV Registrations')\n",
        "plt.xlabel('Number of Vehicles Registered')\n",
        "plt.ylabel('Model')\n",
        "plt.legend(title='Make', loc='center right')\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 756
        },
        "id": "mZcAyRxGjaPT",
        "outputId": "385501ac-332f-48a4-ecf6-df0027e9908d"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# analyzing the distribution of electric range\n",
        "plt.figure(figsize=(12, 6))\n",
        "sns.histplot(ev_data['Electric Range'], bins=30, kde=True, color='royalblue')\n",
        "plt.title('Distribution of Electric Vehicle Ranges')\n",
        "plt.xlabel('Electric Range (miles)')\n",
        "plt.ylabel('Number of Vehicles')\n",
        "plt.axvline(ev_data['Electric Range'].mean(), color='red', linestyle='--', label=f'Mean Range: {ev_data[\"Electric Range\"].mean():.2f} miles')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "AFQ_7XNPjcYQ",
        "outputId": "0d96248a-2e88-4df3-d7f1-7053141100b9"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# calculating the average electric range by model year\n",
        "average_range_by_year = ev_data.groupby('Model Year')['Electric Range'].mean().reset_index()\n",
        "\n",
        "plt.figure(figsize=(12, 6))\n",
        "sns.lineplot(x='Model Year', y='Electric Range', data=average_range_by_year, marker='o', color='green')\n",
        "plt.title('Average Electric Range by Model Year')\n",
        "plt.xlabel('Model Year')\n",
        "plt.ylabel('Average Electric Range (miles)')\n",
        "plt.grid(True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "DwxJSNV-jfuL",
        "outputId": "de19a217-f13e-4c0b-936f-427c5e38a39f"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "average_range_by_model = top_makes_data.groupby(['Make', 'Model'])['Electric Range'].mean().sort_values(ascending=False).reset_index()"
      ],
      "metadata": {
        "id": "PjFi6mngjji6"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# the top 10 models with the highest average electric range\n",
        "top_range_models = average_range_by_model.head(10)"
      ],
      "metadata": {
        "id": "fvqyybIRjnZG"
      },
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12, 8))\n",
        "barplot = sns.barplot(x='Electric Range', y='Model', hue='Make', data=top_range_models, palette=\"cool\")\n",
        "plt.title('Top 10 Models by Average Electric Range in Top Makes')\n",
        "plt.xlabel('Average Electric Range (miles)')\n",
        "plt.ylabel('Model')\n",
        "plt.legend(title='Make', loc='center right')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 718
        },
        "id": "rp1FyO9LjpkO",
        "outputId": "0a3a7451-42b7-4c08-f8d1-d09fb1c01d9e"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# calculate the number of EVs registered each year\n",
        "ev_registration_counts = ev_data['Model Year'].value_counts().sort_index()\n",
        "ev_registration_counts"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "glXmEj0bjrap",
        "outputId": "14e59c08-a297-40c2-dc1f-507340949325"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Model Year\n",
              "2000       1\n",
              "2002       1\n",
              "2008       1\n",
              "2010       4\n",
              "2011      68\n",
              "2012     142\n",
              "2013     424\n",
              "2014     321\n",
              "2015     479\n",
              "2016     576\n",
              "2017     832\n",
              "2018    1448\n",
              "2019    1136\n",
              "2020    1178\n",
              "2021    1872\n",
              "2022    2710\n",
              "2023    5576\n",
              "2024     667\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from scipy.optimize import curve_fit\n",
        "import numpy as np"
      ],
      "metadata": {
        "id": "vqB20W_Ejuw7"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# filter the dataset to include years with complete data, assuming 2023 is the last complete year\n",
        "filtered_years = ev_registration_counts[ev_registration_counts.index <= 2023]"
      ],
      "metadata": {
        "id": "b8bzGoqAjxcs"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# define a function for exponential growth to fit the data\n",
        "def exp_growth(x, a, b):\n",
        "    return a * np.exp(b * x)"
      ],
      "metadata": {
        "id": "REL1qipPj0SB"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# prepare the data for curve fitting\n",
        "x_data = filtered_years.index - filtered_years.index.min()\n",
        "y_data = filtered_years.values"
      ],
      "metadata": {
        "id": "CaPkA5ZAj2Y7"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# fit the data to the exponential growth function\n",
        "params, covariance = curve_fit(exp_growth, x_data, y_data)"
      ],
      "metadata": {
        "id": "xFi8xe4-j4da"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# use the fitted function to forecast the number of EVs for 2024 and the next five years\n",
        "forecast_years = np.arange(2024, 2024 + 6) - filtered_years.index.min()\n",
        "forecasted_values = exp_growth(forecast_years, *params)"
      ],
      "metadata": {
        "id": "6xIaUHQqj6tl"
      },
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# create a dictionary to display the forecasted values for easier interpretation\n",
        "forecasted_evs = dict(zip(forecast_years + filtered_years.index.min(), forecasted_values))"
      ],
      "metadata": {
        "id": "KAo3cUXRj9Qn"
      },
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(forecasted_evs)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i7qZ9SSHkAO0",
        "outputId": "9bbf8420-b67e-4c43-9939-4a5fed57df25"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{2024: 7493.129253541961, 2025: 11150.495823821178, 2026: 16593.00846282369, 2027: 24691.989862831648, 2028: 36744.051854863326, 2029: 54678.67734488265}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# prepare data for plotting\n",
        "years = np.arange(filtered_years.index.min(), 2029 + 1)\n",
        "actual_years = filtered_years.index\n",
        "forecast_years_full = np.arange(2024, 2029 + 1)"
      ],
      "metadata": {
        "id": "YyKJFStpkDPB"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# actual and forecasted values\n",
        "actual_values = filtered_years.values\n",
        "forecasted_values_full = [forecasted_evs[year] for year in forecast_years_full]"
      ],
      "metadata": {
        "id": "zY1BDarMkGwr"
      },
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12, 8))\n",
        "plt.plot(actual_years, actual_values, 'bo-', label='Actual Registrations')\n",
        "plt.plot(forecast_years_full, forecasted_values_full, 'ro--', label='Forecasted Registrations')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 693
        },
        "id": "5Sn4ZayckJRz",
        "outputId": "4ec28f0b-89b4-4a6d-fbc6-94365051dab2"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7c8609493940>]"
            ]
          },
          "metadata": {},
          "execution_count": 40
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.title('Current & Estimated EV Market')\n",
        "plt.xlabel('Year')\n",
        "plt.ylabel('Number of EV Registrations')\n",
        "plt.legend()\n",
        "plt.grid(True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 509
        },
        "id": "r6DtxdGqkMDw",
        "outputId": "0e924aa1-d93a-4954-a204-78a7ef919026"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:matplotlib.legend:No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.show()"
      ],
      "metadata": {
        "id": "TQJSLwb5kP2h"
      },
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "ZQD0uBYykSKG"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}