Plot different columns of different DataFrame in the same plot with Pandas

Question

I have two differents Data Frames:

DF1: with columns A B1 C1 D1 E1
DF2: with columns A B2 C2 D2 E2

With A being the same for the two of them.

then I want to plot two plots in the same figure, one at the right and the other at the left with this information:

Plot 1: x axis = column A
        y axis = B1, B2, C1, C2 curves

Plot 2: x axis = column A
        y axis = D1, D2, E1, E2 curves

How can I do it without merge the two DF using Pandas and Matplotlib?

Answer 1

The idea would be to create an axes ax and a twin axes ax2 = ax.twinx() and to then plot each dataframe to one of them, df.plot(ax=ax) and df2.plot(ax=ax2).

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

a = np.linspace(-5,5, 11)
data1 = np.sort(np.random.rand(len(a),5))
data1[:,0] =a 
data2 = np.sort(np.random.rand(len(a),5))*10
data2[:,0] =a 
df = pd.DataFrame(data1, columns=["A", "B1", "C1", "D1", "E1"])
df2 = pd.DataFrame(data2, columns=["A", "B2", "C2", "D2", "E2"])

fig, ax = plt.subplots()
ax2 = ax.twinx()

df.plot(x="A", y=["B1", "C1", "D1", "E1"], ax=ax)
df2.plot(x="A", y=["B2", "C2", "D2", "E2"], ax=ax2, ls="--")

plt.show()

If instead you want to have two separate plots (the question is not clear on this point), you can do it by

fig, (ax, ax2) = plt.subplots(ncols=2)

and removing the twinx call.