Python Data Visualisation for Business Analyst – How to plot Diverging Bars in Python

(Python Data Visualisation Tutorials)

Python Data Visualisation for Business Analyst – How to plot Diverging Bars in Python

In this data visualisation tutorial, you will learn How to plot Diverging Bars in Python.

If you want to see how the items are varying based on a single metric and visualize the order and amount of this variance, the diverging bars is a great tool. It helps to quickly differentiate the performance of groups in your data and is quite intuitive and instantly conveys the point.



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 */
Data: mtcars

How to plot Diverging Bars in Python

Download Code:


/* Prepare Data */
df = pd.read_csv("mtcars.csv")
x = df.loc[:, ['mpg']]
df['mpg_z'] = (x - x.mean())/x.std()
df['colors'] = ['red' if x < 0 else 'green' for x in df['mpg_z']]
df.sort_values('mpg_z', inplace=True)

/* Draw plot */
plt.figure(figsize=(14,10), dpi= 80)
plt.hlines(y=df.index, xmin=0, xmax=df.mpg_z, color=df.colors, alpha=0.4, linewidth=5)

/* Decorations */
plt.gca().set(ylabel='$Model$', xlabel='$Mileage$')
plt.yticks(df.index,, fontsize=12)
plt.title('Diverging Bars of Car Mileage', fontdict={'size':20})
plt.grid(linestyle='--', alpha=0.5)


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