Beeswarms
Build a beeswarm plot using sns.swarmplot()
that looks at the Ozone levels for all the cities in the pollution
data for the month of March. To make the beeswarm a bit more legible, decrease the point size to avoid the overcrowding caused by the many points drawn on the screen. Last, since you've done some manipulation of the data to make this plot, provide a title to help the reader orient with what they are viewing.
This exercise is part of the course
Improving Your Data Visualizations in Python
Exercise instructions
- Subset the
pollution
data to include just the observations in March. - Plot the
O3
levels as the continuous value in theswarmplot()
. - Decrease the point size to
3
to avoid crowding of the points. - Title the plot
'March Ozone levels by city'
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Filter data to just March
pollution_mar = pollution[pollution.month == ____]
# Plot beeswarm with x as O3
sns.swarmplot(y = "city",
x = '____',
data = pollution_mar,
# Decrease the size of the points to avoid crowding
size = ____)
# Give a descriptive title
plt.____('____')
plt.show()