Data_visualization_by_matplotlib_and_seaborn_of_shoolini_university.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "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/mahirmsb25/First-Sem-Project-/blob/main/Data_visualization_by_matplotlib_and_seaborn_of_shoolini_university.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###What is data visualization\n",
        "Data visualization refers to the graphical representation of data to communicate information clearly and efficiently. It involves using visual elements like charts, graphs, and maps to present complex datasets in a more understandable and insightful manner."
      ],
      "metadata": {
        "id": "k0MQ3Q2yNiwp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "7b2IF3ID9pOD",
        "outputId": "8c3e73fc-48a6-40de-8601-3b799e6dea66",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###What is Matplotlib?\n",
        "\n",
        "Matplotlib is a low level graph plotting library in python that serves as a visualization utility.\n",
        "\n",
        "Matplotlib was created by John D. Hunter.\n",
        "\n",
        "Matplotlib is open source and we can use it freely."
      ],
      "metadata": {
        "id": "Y3eHBH89NrPf"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "PCCHKhTz6Xcq"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np"
      ],
      "metadata": {
        "id": "r6bq8FP67byF"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "###line plot\n",
        "Line plots in Matplotlib are widely used for visualizing data where one variable changes over another."
      ],
      "metadata": {
        "id": "OXNUif8DN8Fn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#title, label, xlabel, ylabel"
      ],
      "metadata": {
        "id": "EVTetukNOBwQ"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Set Font Properties for Title and Labels\n",
        "\n",
        "You can use the fontdict parameter in xlabel(), ylabel(), and title() to set font properties for the title and labels."
      ],
      "metadata": {
        "id": "AhHLMA1AOafZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cgpa = np.array([6, 6.8, 7, 7.5, 8, 8.5, 10])\n",
        "pacakge = np.array([5, 6, 7, 7.5, 8, 10, 30])\n",
        "font1 = {'family':'serif','color':'blue','size':20}\n",
        "font2 = {'family':'serif','color':'darkred','size':15}\n",
        "\n",
        "plt.title(\"Shoolini university students of BTECH\", fontdict = font1)\n",
        "plt.xlabel(\"CGPA of students\", fontdict = font2)\n",
        "plt.ylabel(\"Package of students\", fontdict = font2)\n",
        "\n",
        "plt.plot(cgpa, pacakge,\"o--r\",  ms = 20, mec = \"r\", mfc = \"g\") # ms is marker size, mec marker edge color\n",
        "plt.grid(axis = \"y\",color = \"g\", linestyle = \":\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 484
        },
        "id": "LKmrjvmk7y6L",
        "outputId": "1002ab83-464b-47f8-a8b0-739282d24e61"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Creating Bars\n",
        "\n",
        "With Pyplot, you can use the bar() function to draw bar graphs:"
      ],
      "metadata": {
        "id": "vL8ycnVTPWhe"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Bar plots in Matplotlib are used to represent categorical data with rectangular bars."
      ],
      "metadata": {
        "id": "zwPgzBSnQIcO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "fruit = np.array([\"Apple\", \"Banana\", \"Orange\", \"watermelon\"])\n",
        "fruit_number = np.array([100, 80, 120, 50])\n",
        "color = [\"red\", \"green\", \"yellow\", \"hotpink\"]\n",
        "plt.bar(fruit, fruit_number, color = color)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "Hukjjqbl84v1",
        "outputId": "c83e4532-614f-440f-f076-cb24631f195f"
      },
      "execution_count": 8,
      "outputs": [
        {
          "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": [
        "fruit = np.array([\"Apple\", \"Banana\", \"Orange\", \"watermelon\"])\n",
        "fruit_number = np.array([100, 80, 120, 50])\n",
        "color = [\"red\", \"green\", \"yellow\", \"hotpink\"]\n",
        "plt.barh(fruit, fruit_number, color = color)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "AlMqYtBsBsDN",
        "outputId": "2f99523a-88a0-46db-d045-38ab36fdc178"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###pie plot\n",
        "Pie plots in Matplotlib are useful for representing data as a circular statistical graphic. Each wedge of the pie represents a proportion of the whole."
      ],
      "metadata": {
        "id": "2CTmkPsQQcsi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x = np.array([25, 35, 20, 20])\n",
        "my_labels = [\"Apple\", \"Banana\", \"Orange\", \"watermelon\"]\n",
        "my_explode = [0, 0.2, 0, 0]\n",
        "plt.pie(x, labels = my_labels, explode = my_explode)\n",
        "plt.legend(title = \"Myfruit\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 406
        },
        "id": "5JeTCkuBDsXY",
        "outputId": "745a2459-db17-4f52-f5f3-8c27b742b5c9"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###scatter plot\n",
        "Scatter plots in Matplotlib are used to visualize the relationship between two variables by displaying data points as individual markers."
      ],
      "metadata": {
        "id": "Dxy7CHC3TIyv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "age_cars = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6])\n",
        "speed_cars = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86])\n",
        "\n",
        "plt.scatter(age_cars, speed_cars)\n",
        "plt.title(\"Cars data\")\n",
        "plt.xlabel(\"age of cars\")\n",
        "plt.ylabel(\"Speed of cars\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "8WNZsbH_ELkN",
        "outputId": "1c87b78b-25cb-4604-d5cd-b47f7d03df10"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###Histogram\n",
        "Histogram plots in Matplotlib are used to visualize the distribution of a single continuous variable by dividing the data into bins and displaying the frequency or count of observations in each bin."
      ],
      "metadata": {
        "id": "tzsdiA54bJbO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Sample data\n",
        "data = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 6, 6, 6, 6, 6, 7, 7, 8]\n",
        "\n",
        "# Create a histogram plot\n",
        "plt.hist(data, bins=8, color='skyblue', edgecolor='black')\n",
        "\n",
        "# Add title and labels\n",
        "plt.title('Histogram Plot Example')\n",
        "plt.xlabel('Values')\n",
        "plt.ylabel('Frequency')\n",
        "\n",
        "# Display the plot\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "ERWY6VoCbIJv",
        "outputId": "0a3dbf01-cb79-47f6-d055-61f364c110b4"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}