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Quantiles choropleth

In this exercise we will create a quantile version of the tree density map. Remember that the quantile algorithm will rank and split the values into groups with the same number of elements to assign a color to each. This time, we will create seven groups that allocate the colors of the YlGn colormap across the entire set of values.

The district_trees GeoDataFrame is again already loaded. It includes the variable n_trees_per_area, measuring tree density by district (note the variable has been multiplied by 10,000).

This exercise is part of the course

Working with Geospatial Data in Python

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Exercise instructions

  • Generate a choropleth using the 'n_trees_per_area' variable, a quantile classification scheme with 7 classes and the YlGn color map. Assign the result to a variable named ax.
  • Remove the frames, ticks and tick labels from the plot for a cleaner map using the set_axis_off() method.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Generate the choropleth and store the axis
____ = districts_trees.plot(column='n_trees_per_area', scheme='____',
                          k=____, cmap='____', legend=True)

# Remove frames, ticks and tick labels from the axis
____.set_axis_off()
plt.show()
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