Mar_2_assignment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "266eb5dd-9967-437f-a0ec-c12f659c73f5",
   "metadata": {},
   "source": [
    "# Answer 1\n",
    "\n",
    "Matplotlib is a popular data visualization library in Python. It allows users to create a variety of static, animated, and interactive plots in Python. Matplotlib is widely used in data analysis, scientific research, and machine learning applications to visualize data and communicate insights to stakeholders.\n",
    "\n",
    "Matplotlib provides a range of modules, including Pyplot, which is a sub-library used to create simple plots, charts, and graphs. Pyplot provides a convenient interface for creating plots with minimal coding effort.\n",
    "\n",
    "Here are five plots that can be plotted using the Pyplot module of Matplotlib:\n",
    "\n",
    "1) Line Plot: This is a basic plot type that shows the relationship between two variables with a straight line connecting the data points.\n",
    "\n",
    "2) Scatter Plot: This is a plot type that displays the relationship between two variables with points on a 2D plane, where each point represents an observation in the data.\n",
    "\n",
    "3) Bar Plot: This is a plot type used to represent categorical data with rectangular bars. Each bar represents a category, and the height or length of the bar indicates the value associated with that category.\n",
    "\n",
    "4) Histogram: This is a plot type that shows the distribution of a numeric variable by dividing it into bins and counting the number of observations that fall within each bin.\n",
    "\n",
    "5) Pie Chart: This is a plot type that shows the relative proportions of categories in a dataset as a circular chart, where each slice represents a category, and the size of the slice represents the proportion of data associated with that category."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58f78d44-796c-4472-8018-8294c4dbe24b",
   "metadata": {},
   "source": [
    "# Answer 2\n",
    "\n",
    "A scatter plot is a type of plot that displays the relationship between two variables by plotting data points on a 2D plane, where each point represents an observation in the data. It is commonly used to visualize the correlation or association between two variables.\n",
    "\n",
    "Here's how to generate a scatter plot using the provided code:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ef4f5db8-2a8f-4511-9107-731a68b9b1c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Generate the data for x and y\n",
    "np.random.seed(3)\n",
    "x = 3 + np.random.normal(0, 2, 50)\n",
    "y = 3 + np.random.normal(0, 2, len(x))\n",
    "\n",
    "# Create the scatter plot\n",
    "plt.scatter(x, y)\n",
    "\n",
    "# Add title, xlabel, and ylabel\n",
    "plt.title(\"Scatter Plot of X and Y\")\n",
    "plt.xlabel(\"X\")\n",
    "plt.ylabel(\"Y\")\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14f5b873-cb79-457a-b407-7bb502243082",
   "metadata": {},
   "source": [
    "# Answer 3\n",
    "\n",
    "The subplot() function in Matplotlib is used to create multiple plots within a single figure. It allows users to display different visualizations side by side, making it easier to compare and contrast different aspects of the data.\n",
    "\n",
    "Here's an example of how to create four line plots using the subplot() function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "46730871-631e-4383-b026-4202df0694f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Define the data for each line\n",
    "x1 = np.array([0, 1, 2, 3, 4, 5])\n",
    "y1 = np.array([0, 100, 200, 300, 400, 500])\n",
    "\n",
    "x2 = np.array([0, 1, 2, 3, 4, 5])\n",
    "y2 = np.array([50, 20, 40, 20, 60, 70])\n",
    "\n",
    "x3 = np.array([0, 1, 2, 3, 4, 5])\n",
    "y3 = np.array([10, 20, 30, 40, 50, 60])\n",
    "\n",
    "x4 = np.array([0, 1, 2, 3, 4, 5])\n",
    "y4 = np.array([200, 350, 250, 550, 450, 150])\n",
    "\n",
    "# Create the subplots\n",
    "fig, axs = plt.subplots(2, 2, figsize=(10, 8))\n",
    "\n",
    "# Add a title for the figure\n",
    "fig.suptitle('Four Line Plots using subplot() function')\n",
    "\n",
    "# Plot each line on its own subplot\n",
    "axs[0, 0].plot(x1, y1)\n",
    "axs[0, 0].set_title('Line 1')\n",
    "\n",
    "axs[0, 1].plot(x2, y2)\n",
    "axs[0, 1].set_title('Line 2')\n",
    "\n",
    "axs[1, 0].plot(x3, y3)\n",
    "axs[1, 0].set_title('Line 3')\n",
    "\n",
    "axs[1, 1].plot(x4, y4)\n",
    "axs[1, 1].set_title('Line 4')\n",
    "\n",
    "# Add x and y axis labels for each subplot\n",
    "for ax in axs.flat:\n",
    "    ax.set(xlabel='X-axis', ylabel='Y-axis')\n",
    "\n",
    "# Adjust the spacing between subplots\n",
    "fig.tight_layout()\n",
    "\n",
    "# Display the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35185b94-2b48-47a6-bb3c-ed2a889a96a6",
   "metadata": {},
   "source": [
    "This code creates a 2x2 grid of subplots using the subplot() function, with each subplot containing a line plot of the provided data. It also adds a title to the overall figure using the suptitle() function and x and y axis labels for each subplot. Finally, it adjusts the spacing between the subplots using the tight_layout() function and displays the plot using the show() function."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3462c49a-6b8d-4a03-a8e1-518a36c27d9a",
   "metadata": {},
   "source": [
    "# Answer 4\n",
    "\n",
    "A bar plot is a type of plot that displays data using rectangular bars of equal width. The length of each bar is proportional to the value of the data it represents. Bar plots are commonly used to compare data between different categories or groups.\n",
    "\n",
    "Bar plots are useful when we want to compare a numerical value across different categories. They are particularly useful when we want to compare many categories at once, as they provide a clear visual representation of the differences between categories.\n",
    "\n",
    "Here's an example of how to create a vertical bar plot and a horizontal bar plot using the provided data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b39fdd77-27b3-43e8-aba3-75fdf4cca445",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Define the data\n",
    "company = np.array([\"Apple\", \"Microsoft\", \"Google\", \"AMD\"])\n",
    "profit = np.array([3000, 8000, 1000, 10000])\n",
    "\n",
    "# Create a vertical bar plot\n",
    "plt.bar(company, profit)\n",
    "plt.title('Company profits')\n",
    "plt.xlabel('Company')\n",
    "plt.ylabel('Profit')\n",
    "plt.show()\n",
    "\n",
    "# Create a horizontal bar plot\n",
    "plt.barh(company, profit)\n",
    "plt.title('Company profits')\n",
    "plt.xlabel('Profit')\n",
    "plt.ylabel('Company')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8beef89d-9928-4ffe-8617-babfa8843203",
   "metadata": {},
   "source": [
    "# Answer 5\n",
    "\n",
    "A box plot is a type of plot that displays the distribution of a set of data. It shows the median, quartiles, and outliers of the data. Box plots are useful for visualizing the spread and skewness of a dataset.\n",
    "\n",
    "Box plots are used to identify and display key statistical features of a dataset, including the median, quartiles, and outliers. They are particularly useful for comparing multiple datasets, as they allow us to easily see differences in the spread and skewness of the data.\n",
    "\n",
    "Here's an example of how to create a box plot using the provided data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ac8cd728-8ff9-4118-83b8-32795ec98726",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Define the data\n",
    "box1 = np.random.normal(100, 10, 200)\n",
    "box2 = np.random.normal(90, 20, 200)\n",
    "\n",
    "# Combine the data into a list\n",
    "data = [box1, box2]\n",
    "\n",
    "# Create a box plot\n",
    "plt.boxplot(data)\n",
    "plt.title('Box Plot')\n",
    "plt.xlabel('Box')\n",
    "plt.ylabel('Value')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "58f11bea-aee0-4c9b-ac0e-329ccd630b30",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}