Pandas DataFrame plot.area() Method

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Preparation

Before any data manipulation can occur, three (3) new libraries will require installation.

  • The Pandas library enables access to/from a DataFrame.
  • The Matplotlib library displays a visual graph of a plotted dataset.
  • The Scipy library allows users to manipulate and visualize the data.

To install these libraries, navigate to an IDE terminal. At the command prompt ($), execute the code below. For the terminal used in this example, the command prompt is a dollar sign ($). Your terminal prompt may be different.

$ pip install pandas

Hit the <Enter> key on the keyboard to start the installation process.

$ pip install matplotlib

Hit the <Enter> key on the keyboard to start the installation process.

$ pip install scipy

Hit the <Enter> key on the keyboard to start the installation process.

If the installations were successful, a message displays in the terminal indicating the same.

Feel free to view the PyCharm installation guide for the required libraries.

Add the following code to the top of each code snippet. This snippet will allow the code in this article to run error-free.

import pandas as pd
import matplotlib.pyplot as plt
import scipy

DataFrame Plot Area

The DataFrame.plot.area() method creates a stacked Area plot chart.

The syntax for this method is as follows:

DataFrame.plot.area(x=None, y=None, **kwargs)
xThis parameter determines the coordinates for the x-axis.
The default value is the index.
yThis parameter specifies the coordinates for the y axis.
The default value is the columns.
**kwargsAdditional keywords are outlined above in the plot method.

For this example, Rivers Clothing would like to plot an Area chart indicating Sales, New Customers, and Unique Visits to their online store over six (6) months.

df = pd.DataFrame({'Sales':    [3, 2, 3, 9, 10, 6],
                  'New-Custs': [7, 7, 6, 11, 17, 13],
                  'Visits':    [19, 41, 26, 61, 71, 60]},
index=pd.date_range(start='2022/01/01', end='2022/07/01', freq='M'))
ax = plt.gca()
df.plot.area(title='Sales Stats - 6 Months', fontsize=8, ax=ax)
plt.show()
  • Line [1] creates a DataFrame from a dictionary of lists. This output saves to df.
  • Line [2] creates an index based on a date range and frequency.
  • Line [3] Gets the current access (gca()) and saves it to ax.
  • Line [4] does the following:
    • creates the Area chart
    • sets the title and font size
    • sets the ax variable created above
  • Line [5] outputs the Area chart on-screen.

Output

The buttons on the bottom left can be used to further manipulate the chart.

💡 Note: Another way to create this chart is with the plot() method and the kind parameter set to the 'area' option.

More Pandas DataFrame Methods

Feel free to learn more about the previous and next pandas DataFrame methods (alphabetically) here:

👈 df.pivot()
df.plot.bar() 👉

Also, check out the full cheat sheet overview of all Pandas DataFrame methods.