Python Data Visualisation for Business Analyst – How to do Marginal Histogram plot

(Python Data Visualisation Tutorials)

How to do Marginal Histogram plot

In this data visualisation tutorial, you will learn How to do Marginal Histogram plot in Python.

Marginal histograms have a histogram along the X and Y axis variables. This is used to visualize the relationship between the X and Y along with the univariate distribution of the X and the Y individually. This plot if often used in exploratory data analysis (EDA).



Run this once before the plot’s code. The individual charts, however, may redefine its own aesthetics.

/* !pip install brewer2mpl */
import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import warnings; warnings.filterwarnings(action='once')

large = 22; med = 16; small = 12
params = {'axes.titlesize': large,
          'legend.fontsize': med,
          'figure.figsize': (16, 10),
          'axes.labelsize': med,
          'axes.titlesize': med,
          'xtick.labelsize': med,
          'ytick.labelsize': med,
          'figure.titlesize': large}
%matplotlib inline

/* Version */

How to do Marginal Histogram plot

Download Code:

/* Import Data */
df = pd.read_csv("mpg_ggplot2.csv")

/* Create Fig and gridspec */
fig = plt.figure(figsize=(16, 10), dpi= 80)
grid = plt.GridSpec(4, 4, hspace=0.5, wspace=0.2)

/* Define the axes */
ax_main = fig.add_subplot(grid[:-1, :-1])
ax_right = fig.add_subplot(grid[:-1, -1], xticklabels=[], yticklabels=[])
ax_bottom = fig.add_subplot(grid[-1, 0:-1], xticklabels=[], yticklabels=[])

/* Scatterplot on main ax */
ax_main.scatter('displ', 'hwy', s=df.cty*4, c=df.manufacturer.astype('category'), alpha=.9, data=df, cmap="tab10", edgecolors='gray', linewidths=.5)

/* histogram on the right */
ax_bottom.hist(df.displ, 40, histtype='stepfilled', orientation='vertical', color='deeppink')

/* histogram in the bottom */
ax_right.hist(df.hwy, 40, histtype='stepfilled', orientation='horizontal', color='deeppink')

/* Decorations */
ax_main.set(title='Scatterplot with Histograms \n displ vs hwy', xlabel='displ', ylabel='hwy')
for item in ([ax_main.xaxis.label, ax_main.yaxis.label] + ax_main.get_xticklabels() + ax_main.get_yticklabels()):

xlabels = ax_main.get_xticks().tolist()


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