How to read a multiple column from a .dat file in matplotlib and then plot then into multiple subplots

In matplotlib subplots() is the first address for generating multiple plots into one figure.
(See link for description and examples.)

So you could do

fig, axs = pl.subplots(2)
axs[0].plot(x, y1)
axs[1].plot(x, y2)

instead of your plot command above.

However, please note that while reading a file like this is possible and correct, there are several tools which help you here so you do not have to program this very common task manually again and again.

The most important tools are imo numpy and pandas, perhaps you heard already about them and like to try yourself.

With numpy you could do

import numpy as np
import matplotlib.pyplot as plt

data = np.genfromtxt("sigma.dat")

fig, axs = plt.subplots(2)
for i, ax in enumerate(axs):
    ax.plot(data[:, 0], data[:, i+1])

With pandas you could do

import pandas as pd

df = pd.read_csv("sigma.dat", delim_whitespace=True, index_col=0)
df.plot(subplots=True)

Short Explanation:

With numpy, you import an additional library along with matplotlib, which helps you not only with reading data from files, but which is in fact the basic needed library to do scientific math and calculations in python.

pandas on the other hand can replace matplotlib and/or numpy, as it is built on top of both. It is a complete data analysis tool with a wide range of functions included for a variaty of standard approaches in this topic.

Edit:

After reading your next question, I think I understand a little more of your task, so this is an approach in Python to create four subplots with no space in between:

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv('sigma.dat', delim_whitespace=True, index_col=0, header=None)

fig, axs = plt.subplots(2, 2, sharex=True, sharey='row', gridspec_kw={'hspace': 0, 'wspace': 0})

axs[0, 0].plot(df[df.columns[:2]])
axs[0, 1].plot(df[df.columns[:2]]*1.2)
axs[1, 0].plot(df[df.columns[2:]])
axs[1, 1].plot(df[df.columns[2:]]*.75)

EDIT2:

Further attempt to copy this handmade original

import matplotlib as mpl
mpl.rcParams['font.family'] = 'Times New Roman'

fig, axs = plt.subplots(2, 2, sharex=True, gridspec_kw={'hspace': 0, 'wspace': 0})

axs[0, 0].plot(df[df.columns[:2]])
axs[0, 1].plot(df[df.columns[:2]]*1.2)
axs[1, 0].plot(df[df.columns[2:]])
axs[1, 1].plot(df[df.columns[2:]]*.75)
for i in range(2):
    axs[i, 1].spines['left'].set_position(('axes', 1))
    axs[i, 1].yaxis.set_ticks_position('right')
    axs[i, 1].yaxis.set_label_position('right')

axs[0, 0].set_ylabel('A11')
axs[0, 1].set_ylabel('A12')
axs[1, 0].set_ylabel('A21')
axs[1, 1].set_ylabel('A22')

for ax, lbl in zip(axs.flatten(), list('abcd')):
    ax.text(.05, .9, f'({lbl})', transform=ax.transAxes)
axs[1, 0].set_xlabel('X-12-Scale', x=1)