{ "cells": [ { "cell_type": "markdown", "id": "df202df2", "metadata": {}, "source": [ "# Creating Dynamic Bar Charts with Python's Matplotlib\n", "\n", "## Introduction:\n", "Visualizing data is an essential aspect of data analysis and presentation. One effective way to represent data is through bar charts, which display data values as rectangular bars. In this tutorial, we'll explore how to create dynamic bar charts using Python's Matplotlib library. We'll create a bar chart to visualize the stock price changes of various companies in the year 2023.\n", "\n", "## Prerequisites:\n", "Before we begin, make sure you have Python and Matplotlib installed. You can install Matplotlib using the following command:\n", "\n", "```bash\n", "pip install matplotlib\n", "\n", "```\n", "\n", "## Step 1: Importing the Required Libraries\n", "To get started, we need to import the Matplotlib library that provides tools to create various types of plots, including bar charts. Open your favorite code editor or Jupyter Notebook and follow along." ] }, { "cell_type": "code", "execution_count": 1, "id": "59426733", "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "id": "9d2100ee", "metadata": {}, "source": [ "## Step 2: Data Preparation\n", "For this example, we'll use a sample dataset containing information about the stock price changes of different companies. You can replace this dataset with your own data." ] }, { "cell_type": "code", "execution_count": 4, "id": "741efe04", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | Company | \n", "Country | \n", "Change | \n", "
---|---|---|---|
0 | \n", "Carvana Co | \n", "USA | \n", "962 | \n", "
1 | \n", "Nvidia | \n", "USA | \n", "237 | \n", "
2 | \n", "Meta | \n", "USA | \n", "145 | \n", "
3 | \n", "Palantir | \n", "USA | \n", "133 | \n", "
4 | \n", "Coinbase | \n", "USA | \n", "124 | \n", "