Mastering Matplotlib: A Guide to Bar Charts, Histograms, Scatter Plots, and Pie Charts

Let's dive into the different types of plots you can create using Matplotlib, along with examples:

1. Bar Chart:

   • A bar chart (or bar plot) displays categorical data with rectangular bars. Each bar represents a category, and the height of the bar corresponds to the value of that category.
   • Example:

    import matplotlib.pyplot as plt
   
    x = [1, 3, 5, 7, 9]
    y1 = [5, 2, 7, 8, 2]
    y2 = [8, 6, 2, 5, 6]
   
    plt.bar(x, y1, label="Example one")
    plt.bar(x, y2, label="Example two", color='g')
   
    plt.xlabel("X-axis")
    plt.ylabel("Y-axis")
    plt.title("Bar Chart Example")
    plt.legend()
    plt.show()
   

• This code creates a bar chart with two sets of bars, labeled "Example one" and "Example two" ⁴.

2.Histogram:

• A histogram represents the distribution of continuous data by dividing it into bins and showing the frequency of values falling into each bin.

• Example:
  

   import matplotlib.pyplot as plt
   import numpy as np
  
   data = np.random.randn(1000)  # Generate random data
   plt.hist(data, bins=20, edgecolor='black')
  
   plt.xlabel("Value")
   plt.ylabel("Frequency")
   plt.title("Histogram Example")
   plt.show()
  

• This code creates a histogram from random data.

3.Scatter Plot:

• A scatter plot displays individual data points as dots. It is useful for visualizing relationships between two continuous variables.

• Example:
  

   import matplotlib.pyplot as plt
  
   x = [10, 20, 30, 40]
   y = [20, 25, 35, 55]
  
   plt.scatter(x, y, marker='o', color='b', label="Data points")
   plt.xlabel("X-axis")
   plt.ylabel("Y-axis")
   plt.title("Scatter Plot Example")
   plt.legend()
   plt.show()
  

• This code creates a scatter plot with data points.

4.Pie Chart:

• A pie chart represents parts of a whole. It shows the proportion of each category relative to the total.

• Example:
  

   import matplotlib.pyplot as plt
  
   labels = ['Apples', 'Bananas', 'Cherries', 'Dates']
   sizes = [30, 25, 20, 15]
  
   plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90)
   plt.axis('equal')  # Equal aspect ratio ensures a circular pie chart
   plt.title("Pie Chart Example")
   plt.show()
  

• This code creates a simple pie chart with labeled slices ².

Remember to customize these plots further by adjusting labels, colors, and other parameters according to your specific requirements. Happy plotting! 😊📊🎨