Python Data Visualisation for Business Analyst – How to Plot Multiple Time Series with different scales using secondary Y axis in Python

In this data visualisation tutorial, you will learn – How to Plot Multiple Time Series with different scales using secondary Y axis in Python.

If you want to show two time series that measures two different quantities at the same point in time, you can plot the second series againt the secondary Y axis on the right.

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__)``````
Data: economics

How to Plot Multiple Time Series with different scales using secondary Y axis in Python

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

x = df['date']
y1 = df['psavert']
y2 = df['unemploy']

/* Plot Line1 (Left Y Axis) */
fig, ax1 = plt.subplots(1,1,figsize=(16,9), dpi= 80)
ax1.plot(x, y1, color='tab:red')

/* Plot Line2 (Right Y Axis) */
ax2 = ax1.twinx()
ax2.plot(x, y2, color='tab:blue')

/* Decorations */
/* ax1 (left Y axis) */
ax1.set_xlabel('Year', fontsize=20)
ax1.tick_params(axis='x', rotation=0, labelsize=12)
ax1.set_ylabel('Personal Savings Rate', color='tab:red', fontsize=20)
ax1.tick_params(axis='y', rotation=0, labelcolor='tab:red' )
ax1.grid(alpha=.4)

/* ax2 (right Y axis) */
ax2.set_ylabel("Unemployed (1000's)", color='tab:blue', fontsize=20)
ax2.tick_params(axis='y', labelcolor='tab:blue')
ax2.set_xticks(np.arange(0, len(x), 60))
ax2.set_xticklabels(x[::60], rotation=90, fontdict={'fontsize':10})
ax2.set_title("Personal Savings Rate vs Unemployed: Plotting in Secondary Y Axis", fontsize=22)
fig.tight_layout()
plt.show()``````

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