[FIXED] Placing Subplots in Matplotlib with Occupying Different column and row sizes

Issue

I am trying to create 6 graphs of subplots. 2 of the line plots are on the same row and the row below it will have the Cumulative Plot which will occupy the space of 2 columns. It will do this for col1 and col2 creating 6 plots in total (3 for each range). However the plots overlap how would I be able to fix it and make it so that it fits the format mentioned at Format of the Plots.

Format of the Plots:

-line plot `col1`(column=1, row=1), line plot `col1` (column=2, row=1)
-cumulative plot `col1`(column= 1 and 2, row=2)
-line plot `col2`(column=1, row=3), line plot `col2` (column=2, row=3)
-cumulative plot `col2`(column= 1 and 2, row=4)

code:

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


df = pd.DataFrame({
    'x': [1,2,3,4,5,6],
    'col1': [5,3,4,8,9,11],
    'col2': [2,6,3,11,3,6]
})


def Graphing():
    # Size of the figure 
    fig = plt.figure(figsize=(16, 9))
    
    for count, (y,plots,iterator,title) in enumerate(zip(                             
        [df['col1'],df['col2']],   # Range Columns 
        [[(4, 2, 1), (4, 2, 2), (4, 1, 2)], [(4, 2, 1), (4, 2, 2), (4, 1, 4)]], #Columns 
        [0,3], #iterator used to give different names to subplot_
        ['Column 1', 'Column 2'])): #Column used 
    
        for subplot_,add_plot,y,title2 in zip(
                             [f'sub{iterator+0}',f'sub{iterator+1}',f'sub{iterator+2}'],  #Name of the subplot sub0, sub1..
                             [plots[0],plots[1],plots[2]], # cordinates of the subplot 4, 2, 1), (4, 2, 2) ...
                             [y,y,np.cumsum(y)],
                             ['Line Plot','Line Plot', 'Cumulative Plot']):  # Range values for the plot 
            
            #Adds Subplot
            subplot_ = fig.add_subplot(*add_plot)
            
            #Title
            subplot_.set(title=f'{title} {title2}')
            
            # Sets up the x,y, color of the plot 
            getattr(subplot_, 'plot')(df['x'],y,color='r', marker='o')
                
    # Show Graph 
    plt.show()  
        
Graphing()

Output:

Solution

move this inside the first for loop

        fig = plt.figure(figsize=(16, 9))

second, show the plot once your inner loop completes

        plt.show()

third, modify the sub-plot indexes

[[(4, 2, 1), (4, 2, 2), (4, 1, 3)], [(4, 2, 1), (4, 2, 2), (4, 1, 3)]], #Columns 

here is a revised Graphing function

def Graphing():
    # Size of the figure 
    
    for count, (y,plots,iterator,title) in enumerate(zip(                             
        [df['col1'],df['col2']],   # Range Columns 
        [[(4, 2, 1), (4, 2, 2), (4, 1, 3)], [(4, 2, 1), (4, 2, 2), (4, 1, 3)]], #Columns 
        [0,3], #iterator used to give different names to subplot_
        ['Column 1', 'Column 2'])): #Column used 

        fig = plt.figure(figsize=(16, 9))
    
        for subplot_,add_plot,y,title2 in zip(
                             [f'sub{iterator+0}',f'sub{iterator+1}',f'sub{iterator+2}'],  #Name of the subplot sub0, sub1..
                             [plots[0],plots[1],plots[2]], # cordinates of the subplot 4, 2, 1), (4, 2, 2) ...
                             [y,y,np.cumsum(y)],
                             ['Line Plot','Line Plot', 'Cumulative Plot']):  # Range values for the plot 
            
            #Adds Subplot
            subplot_ = fig.add_subplot(*add_plot)
            
            #Title
            subplot_.set(title=f'{title} {title2}')
            
            # Sets up the x,y, color of the plot 
            getattr(subplot_, 'plot')(df['x'],y,color='r', marker='o')
            
        plt.show()
    # Show Graph 
#     plt.show()  

Answered By - Naveed