Annotations

Improving Your Data Visualizations in Python

Nick Strayer

Instructor

What annotations add

Compact and efficient communication
Opportunity to supply deeper insight to data

Outlier with attention drawn with annotation

Flow chart of when to use annotations

sns.scatterplot(x='NO2', y='SO2', data = houston_pollution)

# X and Y location of outlier and text
plt.text(13,33,'Look at this outlier', 
         # Text properties for alignment and size. 
         fontdict = {'ha': 'left', 'size': 'x-large'})

Text point out outlier

sns.scatterplot(x='NO2', y='SO2', data = houston_pollution)

# Arrow start and annotation location
plt.annotate('A buried point to look at', xy=(45.5,11.8), xytext=(60,22), 
  # Arrow configuration and background box
  arrowprops={'facecolor':'grey', 'width': 3}, backgroundcolor = 'white' )

Arrow pointing out outlier

Let's annotate

Improving Your Data Visualizations in Python