Using a plot as a legend
One interesting thread of investigation in the farmer's market data is a state's "market friendliness" and specifically, the outliers. One way to look at this is by using the ratio of farmer's markets to people by state. You could directly look at the ratio; however, a ratio throws away the raw information about a state's population and the number of markets. A large state with a high ratio could be more interesting than a small one.
You can show both the ratio and raw numbers by drawing two plots, one of the ratio and the other of the market number to population scatter plot. To help simplify your now dense visualization, you can use the bar plot as a legend; calling out interesting states by matching the colors of their bars and scatter points.
Este exercício faz parte do curso
Improving Your Data Visualizations in Python
Instruções do exercício
- Set up two plots side-by-side using
plt.subplots()
. - Map the column
is_selected
to the color of both the bar and scatter plot. - Disable
dodge
on the bar plot, so the bars are full height. - Remove the legends in both plots.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# Set up two side-by-side plots
f, (ax1, ax2) = plt.subplots(____, ____, figsize = (15, 15))
# Map the column for selected states to the bar color
sns.barplot('people_per_market', 'state', hue = '____',
# Disable dodge so bars are full size
dodge = ____,
data = markets_by_state, ax = ax1)
# Map selected states to point color
sns.scatterplot('log_pop', 'log_markets', hue = '____',
data = markets_by_state, ax = ax2, s = 100)
# Remove the legend for both plots
ax1.____()
ax2.____()
plt.show()