Welcome Back

Google icon Sign in with Google
OR
I agree to abide by Pharmadaily Terms of Service and its Privacy Policy

Create Account

Google icon Sign up with Google
OR
By signing up, you agree to our Terms of Service and Privacy Policy
Instagram
youtube
Facebook

Pie Charts

Charts

  • In this tutorial, we are going to learn about how to create charts in matplotlib pyplot.
  • In pyplot, we can use pie() function to draw pie charts.
  • For instance:
    import matplotlib.pyplot as plt
    
    y = [35, 15, 25, 25, 75, 25]
    plt.title('First Pie Chart')
    plt.pie(y)
    plt.show() 

    Output:                                                                                                                                                                                    

  • Let's understand the mathematics behind the allotted region to each color here, well the size of each portion is calculated by comparing the value with sum of all other values:

    y[i]/sum(y)
    where i = index of y

Chart Labels

  • We can add labels to our allotted portions with the labels parameter in pie() funciton.
  • The label parameter should be an array with one label for each portion.
  • Let's check this code below:
    import matplotlib.pyplot as plt
    
    y = [35, 15, 25, 25, 75, 25]
    L = ['first','second','third','fourth','fifth','sixth']
    plt.title('First Pie Chart')
    plt.pie(y, labels = L)
    plt.show()

    Output :                                                                                                                                                                                   


Colors

  • We can also give different colors to our chart by color parameter:
    color = ['blue','red','black','hotpink','#4CAF50','grey']
    plt.pie(y, labels = L, colors = color)

    Output:                                                                                                                                                                                     


Legend

  • In the Pie chart, we can also add a list of explanations for each region (wedge). 
  • For this, we use legend() function.
    plt.legend()
    

  • We can also give our legend a header.

    plt.legend(title='six colors')