April 2018
Beginner to intermediate
300 pages
7h 34m
English
Content preview from Matplotlib for Python Developers - Second Edition
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Showing the density of bivariate data with hexbin plots
Scatter plot is a common method to show the distribution of data in a more raw form. But when data density goes over a threshold, it may not be the best visualization method as points can overlap and we lose information about the actual distribution.
A hexbin map is a way to improve the interpretation of data density, by showing the data density in an area by color intensity.
Here is an example to compare the visualization of the same dataset that aggregates in the center:
import pandas as pdimport numpy as np# Prepare 2500 random data points densely clustered at centernp.random.seed(123)df = pd.DataFrame(np.random.randn(2500, 2), columns=['x', 'y'])df['y'] = df['y'] = df['y'] + np.arange(2500) ...
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