# How to do Marginal Boxplot

In this data visualisation tutorial, you will learn How to do Marginal Boxplot 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). Marginal boxplot serves a similar purpose as marginal histogram. However, the boxplot helps to pinpoint the median, 25th and 75th percentiles of the X and the Y.

## Setup

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}
plt.rcParams.update(params)
plt.style.use('seaborn-whitegrid')
sns.set_style("white")
%matplotlib inline

/* Version */
print(mpl.__version__)
print(sns.__version__)``````

## How to do Marginal Boxplot

``````/* Import Data */

/* 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_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*5, c=df.manufacturer.astype('category').cat.codes, alpha=.9, data=df, cmap="Set1", edgecolors='black', linewidths=.5)

/* Add a graph in each part */
sns.boxplot(df.hwy, ax=ax_right, orient="v")
sns.boxplot(df.displ, ax=ax_bottom, orient="h")

/* Decorations ------------------ */
/*  Remove x axis name for the boxplot */
ax_bottom.set(xlabel='')
ax_right.set(ylabel='')

/* Main Title, Xlabel and YLabel */
ax_main.set(title='Scatterplot with Histograms \n displ vs hwy', xlabel='displ', ylabel='hwy')

/* Set font size of different components */
ax_main.title.set_fontsize(20)
for item in ([ax_main.xaxis.label, ax_main.yaxis.label] + ax_main.get_xticklabels() + ax_main.get_yticklabels()):
item.set_fontsize(14)

plt.show()``````

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

Applied Data Science Coding in Python: How to visualise data with Boxplot

Python Boxplot