Untitled (1).ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "U0sPmlyTTAM-"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "vdgame = pd.read_csv(\"/content/videogames.csv\")\n",
        "print(vdgame.head())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zm5uQE6tTCEj",
        "outputId": "4baf1b8a-92dd-47b5-9142-d162445a407b"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                       Name Platform  Year_of_Release         Genre Publisher  \\\n",
            "0                Wii Sports      Wii           2006.0        Sports  Nintendo   \n",
            "1         Super Mario Bros.      NES           1985.0      Platform  Nintendo   \n",
            "2            Mario Kart Wii      Wii           2008.0        Racing  Nintendo   \n",
            "3         Wii Sports Resort      Wii           2009.0        Sports  Nintendo   \n",
            "4  Pokemon Red/Pokemon Blue       GB           1996.0  Role-Playing  Nintendo   \n",
            "\n",
            "   NA_Sales  EU_Sales  JP_Sales  Other_Sales  Global_Sales  Critic_Score  \\\n",
            "0     41.36     28.96      3.77         8.45         82.53          76.0   \n",
            "1     29.08      3.58      6.81         0.77         40.24           NaN   \n",
            "2     15.68     12.76      3.79         3.29         35.52          82.0   \n",
            "3     15.61     10.93      3.28         2.95         32.77          80.0   \n",
            "4     11.27      8.89     10.22         1.00         31.37           NaN   \n",
            "\n",
            "   Critic_Count  User_Score  User_Count Developer Rating  \n",
            "0          51.0         8.0       322.0  Nintendo      E  \n",
            "1           NaN         NaN         NaN       NaN    NaN  \n",
            "2          73.0         8.3       709.0  Nintendo      E  \n",
            "3          73.0         8.0       192.0  Nintendo      E  \n",
            "4           NaN         NaN         NaN       NaN    NaN  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Null values in VDgame**"
      ],
      "metadata": {
        "id": "3pOfpRfgUtMn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(vdgame.isnull().sum())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-fBc8cX7UHf1",
        "outputId": "f8125dce-7e49-4823-c279-da4dab5265e2"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Name                  2\n",
            "Platform              0\n",
            "Year_of_Release     269\n",
            "Genre                 2\n",
            "Publisher            54\n",
            "NA_Sales              0\n",
            "EU_Sales              0\n",
            "JP_Sales              0\n",
            "Other_Sales           0\n",
            "Global_Sales          0\n",
            "Critic_Score       8582\n",
            "Critic_Count       8582\n",
            "User_Score         9129\n",
            "User_Count         9129\n",
            "Developer          6623\n",
            "Rating             6769\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Lets removing the null values**"
      ],
      "metadata": {
        "id": "Cdd3RsP-VGaH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "vdgame= vdgame.dropna()"
      ],
      "metadata": {
        "id": "vCFLIIj9VAUQ"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Lets look top 10 best-selling game**"
      ],
      "metadata": {
        "id": "Nfz5oOTzVuPv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib as mpl\n",
        "game = vdgame.groupby(\"Genre\")[\"Global_Sales\"].count().head(10)\n",
        "custom_colors = mpl.colors.Normalize(vmin=min(game), vmax=max(game))\n",
        "colours = [mpl.cm.PuBu(custom_colors(i)) for i in game]\n",
        "plt.figure(figsize=(7,7))\n",
        "plt.pie(game, labels=game.index, colors=colours)\n",
        "central_circle = plt.Circle((0, 0), 0.5, color='white')\n",
        "fig = plt.gcf()\n",
        "fig.gca().add_artist(central_circle)\n",
        "plt.rc('font', size=12)\n",
        "plt.title(\"Top 10 Categories of Games Sold\", fontsize=20)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 432
        },
        "id": "COiVqxvlVbhu",
        "outputId": "6888ff03-0993-4a53-b5f0-12932f94240b"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 504x504 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(vdgame.corr())\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AZWc_bUEWgGD",
        "outputId": "f2068a3a-97e3-4643-fe5f-ba0448d8a028"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                 Year_of_Release  NA_Sales  EU_Sales  JP_Sales  Other_Sales  \\\n",
            "Year_of_Release         1.000000 -0.016239  0.041346 -0.038443     0.042315   \n",
            "NA_Sales               -0.016239  1.000000  0.841808  0.468607     0.726757   \n",
            "EU_Sales                0.041346  0.841808  1.000000  0.519929     0.716330   \n",
            "JP_Sales               -0.038443  0.468607  0.519929  1.000000     0.394823   \n",
            "Other_Sales             0.042315  0.726757  0.716330  0.394823     1.000000   \n",
            "Global_Sales            0.006661  0.955793  0.939313  0.613546     0.804028   \n",
            "Critic_Score           -0.007661  0.233580  0.213102  0.147314     0.191509   \n",
            "Critic_Count            0.203336  0.283917  0.265740  0.168299     0.239513   \n",
            "User_Score             -0.253914  0.085796  0.055915  0.127521     0.057083   \n",
            "User_Count              0.199348  0.246208  0.283504  0.072773     0.240085   \n",
            "\n",
            "                 Global_Sales  Critic_Score  Critic_Count  User_Score  \\\n",
            "Year_of_Release      0.006661     -0.007661      0.203336   -0.253914   \n",
            "NA_Sales             0.955793      0.233580      0.283917    0.085796   \n",
            "EU_Sales             0.939313      0.213102      0.265740    0.055915   \n",
            "JP_Sales             0.613546      0.147314      0.168299    0.127521   \n",
            "Other_Sales          0.804028      0.191509      0.239513    0.057083   \n",
            "Global_Sales         1.000000      0.237556      0.290397    0.088349   \n",
            "Critic_Score         0.237556      1.000000      0.396478    0.580318   \n",
            "Critic_Count         0.290397      0.396478      1.000000    0.195087   \n",
            "User_Score           0.088349      0.580318      0.195087    1.000000   \n",
            "User_Count           0.264151      0.265639      0.365603    0.017546   \n",
            "\n",
            "                 User_Count  \n",
            "Year_of_Release    0.199348  \n",
            "NA_Sales           0.246208  \n",
            "EU_Sales           0.283504  \n",
            "JP_Sales           0.072773  \n",
            "Other_Sales        0.240085  \n",
            "Global_Sales       0.264151  \n",
            "Critic_Score       0.265639  \n",
            "Critic_Count       0.365603  \n",
            "User_Score         0.017546  \n",
            "User_Count         1.000000  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.heatmap(vdgame.corr(), cmap=\"winter_r\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "id": "KYhjce7uZR14",
        "outputId": "9f029598-1d1c-4392-b902-57b54f9a566a"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Video Game Sales Prediction**"
      ],
      "metadata": {
        "id": "AVxCmYz-Z4CR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X = vdgame[[\"NA_Sales\", \"EU_Sales\", \"JP_Sales\", \"Other_Sales\"]]\n",
        "y = vdgame[\"Global_Sales\"]"
      ],
      "metadata": {
        "id": "Owfv9gkoZb1A"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "xtrain, xtest, ytrain, ytest = train_test_split(X, y, test_size=0.2, random_state=42)\n"
      ],
      "metadata": {
        "id": "aCGYHdBkaP4g"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "model = LinearRegression() \n",
        "model.fit(xtrain, ytrain)\n",
        "predictions = model.predict(xtest)"
      ],
      "metadata": {
        "id": "eM5AfoPhazFZ"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.metrics import accuracy_score"
      ],
      "metadata": {
        "id": "6oDj8Wl4h7px"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "predictions"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZqnaO3MGcRlp",
        "outputId": "5f78dcc7-dc79-4a90-df82-b0ea2f32b983"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([6.02947586, 0.44020146, 0.2302397 , ..., 0.22019897, 0.04024748,\n",
              "       0.96017088])"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "accuracy_score"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sETndAcGb_bO",
        "outputId": "4f9e745c-1a9d-43d4-edda-4d049a43892e"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function sklearn.metrics._classification.accuracy_score(y_true, y_pred, *, normalize=True, sample_weight=None)>"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_data_accuracy=accuracy_score(np.round(predictions),np.round(ytest))\n"
      ],
      "metadata": {
        "id": "6L69VYX2cEE2"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Accuracy:\",test_data_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "izflz_M9dTQ5",
        "outputId": "9f07fbc8-cca1-440a-c0e8-a68ecc650653"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy: 0.9926739926739927\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "3-N0DTADdh2n"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}