⏱ Quick start

# library
import pandas as pd
import matplotlib.pyplot as plt

# Create data
values=[12, 11, 9, 13, 14, 16, 14, 15, 18, 17, 19, 20]
df=pd.DataFrame({'x': range(1,13), 'y': values })

# plot
df.plot('x', 'y') // This is the plot function of pandas

Pandas logoThree distinct syntaxes

There are 3 ways to build a chart with pandas: the plot method, the function name methods (like line, bar or hist) and the plot + function name method.

➡️ plot method

In this case, we have to specify the kind of chart we want to create. The plot method is a wrapper around the matplotlib.pyplot.plot function. The kind argument is used to specify the type of chart we want to create.

df.plot('x', 'y', kind='line')

➡️ function name method

The function name method is a bit more straightforward. We just have to call the right function name to create the chart we want. Matplotlib has various functions to create different types of charts. For example, theline function is used to create line charts.

df.line('x', 'y')

➡️ plot + function name method

This method is a combination of the previous two. We use the plot method and need the function nameright after it.

df.plot.line('x', 'y')

The function name method is the most straightforward and the one we recommend. Most posts on the gallery use this method.

Pandas logoChart examples with Pandas

Pandas offers a wide range of nice charts. Here is a selection of examples that you can find on the gallery. Click on the images to see the code!


👋 This document is a work by Yan Holtz. You can contribute on github, send me a feedback on twitter or subscribe to the newsletter to know when new examples are published! 🔥