Plot multiple time-series DataFrames into a single plot using Pandas (Matplotlib)

To plot multiple time-series data frames into a single plot using Pandas, we can take the following steps −

Set the figure size and adjust the padding between and around the subplots.
Create a Pandas data frame with time series.
Set the time series index for plot.
Plot rupees and dollor on the plot.
To display the figure, use show() method.

Example

import numpy as np
import pandas as pd
from matplotlib import pyplot as plt, dates

plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

df = pd.DataFrame(dict(date=list(pd.date_range("2021-01-01", periods=10)), rupees=np.linspace(1, 10, 10), dollar=np.linspace(10, 20, 10)))

df.set_index(pd.to_datetime(df.date), drop=True).plot()
df = df.set_index(pd.to_datetime(df.date), drop=True)
df.rupees.plot(grid=True, label="rupees", legend=True)
df.dollar.plot(secondary_y=True, label="dollar", legend=True)

plt.show()