Matplotlib

TL;DR

• A Python library for creating static, animated, and interactive visualizations.
• Commonly used to draw line plots, scatter plots, bar charts, histograms, and more.
• Often used together with Pandas to plot data loaded from CSV or other data sources.

Definition

Matplotlib is a powerful Python library used for data visualization. It allows users to create a wide range of static, animated, and interactive visualizations in a variety of formats, including plots, histograms, scatter plots, bar charts, and more.

Explanation

Matplotlib provides plotting functions (commonly via matplotlib.pyplot aliased as plt) to build visualizations. Typical workflows shown in the examples include:

• Importing matplotlib.pyplot and setting a plotting style: plt.style.use('seaborn').
• Loading data into a Pandas DataFrame and extracting relevant columns.
• Using plotting functions such as plot() for line plots and scatter() for scatter plots.
• Adding axis labels and titles with xlabel(), ylabel(), and title().
• Rendering the visualization with show().

Examples

Line plot — Average monthly temperature

To create a line plot of average monthly temperature:

import matplotlib.pyplot as plt

plt.style.use('seaborn')

import pandas as pd

df = pd.read_csv('temperature_data.csv')

month = df['month']

temperature = df['temperature']

plt.plot(month, temperature)

plt.xlabel('Month')

plt.ylabel('Temperature (°F)')

plt.title('Average Monthly Temperature in City')

plt.show()

The resulting line plot will show the trend of the average monthly temperature in the city over the course of a year.

Scatter plot — Height vs Weight

To create a scatter plot showing the relationship between height and weight:

import matplotlib.pyplot as plt

plt.style.use('seaborn')

import pandas as pd

df = pd.read_csv('height_weight_data.csv')

height = df['height']

weight = df['weight']

plt.scatter(height, weight)

plt.xlabel('Height (in)')

plt.ylabel('Weight (lb)')

plt.title('Height vs Weight')

plt.show()

The resulting scatter plot will show the relationship between height and weight in the group of individuals.

Use cases

• Data analysts and scientists use Matplotlib to create visualizations that help them understand and analyze their data and communicate their findings to others.

Related terms

• Pandas
• matplotlib.pyplot (plt)