How can l extract a section of the pandas dataframe like marked in the picture below?

Be sub_rows and sub_cols the dimension of the datafram to be extracted:

import pandas as pd

sub_rows = 10 # Amount of rows to be extracted
sub_cols = 3  # Amount of columns to be extracted


if sub_rows > len(df.index):
    print("Defined sub dataframe rows are more than in the original dataframe")
elif sub_cols > len(df.columns):
    print("Defined sub dataframe columns are more than in the original dataframe")
else:
    for i in range(0,len(df.index)-sub_rows):
        for j in range(0, len(df.columns)):
            d.iloc[i:i+sub_rows, j:j+sub_cols] # Extracted dataframe
            # Put here the code you need for your analysis

You can use the .iloc[] function to select the rows and columns you want.

dataframe.iloc[5:15,6:15]

This should select rows 5-14 and columns 6-14. Not sure if the numbers are correct but I think this method is what you were looking for.

edit: changed .loc[] to .iloc[] because we're using index values, and cleaned it up a bit

Here is the code to iterate over the whole dataframe

#df = big data frame
shape = (10,10) #shape of matrix to be analized, here is 10x10
step = 1 #step size, itterate over every number
        #or
step = 10 #step size, itterate block by block
        #keep in mind, iterating by block will leave some data out at the end of the rows and columns
#you can set step = shape if you are working  with a matrix that isn't square, just be sure to change step in the code below to step[0] and step[1] respectively 
for row in range( 0, len(df[0]) - shape[0]+1, step): #number of rows of big dataframe - number of rows of matrix to be analized 
   for col in range(0, len(df.iloc[0,:]) - shape[1]+1, step): #number of columns of big dataframe - number of columns of matrix to be analized 
        matrix = df.iloc[row:shape[0]+row, col:shape[1]+col] #slice out matrix and set it equal to 'matrix'
        #analize matrix here
    

This is basically the same as @dafmedinama said, i just added more commenting and simplified specifying the shape of the matrix as well as included a step variable if you don't want to iterate over every single number every time you move the matrix.