Preparing your figures to share with others

Introduction to Data Visualization with Matplotlib

Ariel Rokem

Data Scientist

Changing plot style

import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot(seattle_weather["MONTH"], seattle_weather["MLY-TAVG-NORMAL"])
ax.plot(austin_weather["MONTH"], austin_weather["MLY-TAVG-NORMAL"])
ax.set_xlabel("Time (months)")
ax.set_ylabel("Average temperature (Fahrenheit degrees)")
plt.show()

Choosing a style

plt.style.use("ggplot")

fig, ax = plt.subplots()
ax.plot(seattle_weather["MONTH"], seattle_weather["MLY-TAVG-NORMAL"])
ax.plot(austin_weather["MONTH"], austin_weather["MLY-TAVG-NORMAL"])
ax.set_xlabel("Time (months)")
ax.set_ylabel("Average temperature (Fahrenheit degrees)")
plt.show()

Back to the default

plt.style.use("default")

The available styles

https://matplotlib.org/stable/gallery/style_sheets/ style_sheets_reference.html

The "bmh" style

plt.style.use("bmh")

fig, ax = plt.subplots()
ax.plot(seattle_weather["MONTH"], seattle_weather["MLY-TAVG-NORMAL"])
ax.plot(austin_weather["MONTH"], austin_weather["MLY-TAVG-NORMAL"])
ax.set_xlabel("Time (months)")
ax.set_ylabel("Average temperature (Fahrenheit degrees)")
plt.show()

Seaborn styles

plt.style.use("seaborn-colorblind")

fig, ax = plt.subplots()
ax.plot(seattle_weather["MONTH"], seattle_weather["MLY-TAVG-NORMAL"])
ax.plot(austin_weather["MONTH"], austin_weather["MLY-TAVG-NORMAL"])
ax.set_xlabel("Time (months)")
ax.set_ylabel("Average temperature (Fahrenheit degrees)")
plt.show()

Guidelines for choosing plotting style

Dark backgrounds are usually less visible
If color is important, consider choosing colorblind-friendly options
- "seaborn-colorblind" or "tableau-colorblind10"
If you think that someone will want to print your figure, use less ink
If it will be printed in black-and-white, use the "grayscale" style

Practice choosing the right style for you!

Introduction to Data Visualization with Matplotlib