Python | Pandas Panel.rmul()

In Pandas, Panel is a very important container for three-dimensional data. The names for the 3 axes are intended to give some semantic meaning to describing operations involving panel data and, in particular, econometric analysis of panel data.

In Pandas Panel.rmul() function is used to get the multiplication of series and dataframe/Panel.

Syntax: Panel.rmul(other, axis=0)



Parameters:
other : DataFrame or Panel
axis : Axis to broadcast over

Returns: Panel

Code #1:

filter_none

edit
close

play_arrow

link
brightness_4
code

# importing pandas module 
import pandas as pd 
import numpy as np 
  
df1 = pd.DataFrame({'a': ['Geeks', 'For', 'geeks', 'real'], 
                    'b': [111, 123, 425, 1333]}) 
  
df2 = pd.DataFrame({'a': ['I', 'am', 'dataframe', 'two'], 
                    'b': [100, 100, 100, 100]}) 
                      
data = {'item1':df1, 'item2':df2}
  
# creating Panel 
panel = pd.Panel.from_dict(data, orient ='minor'
print("panel['b'] is - \n\n", panel['b']) 
  
print("\nMultiplying panel['b'] with df2['b'] using rmul() method - \n"
print("\n", panel['b'].rmul(df2['b'], axis = 0)) 

chevron_right


Output:

panel['b'] is - 

    item1  item2
0    111    100
1    123    100
2    425    100
3   1333    100

Multiplying panel['b'] with df2['b'] using rmul() method - 


     item1  item2
0   11100  10000
1   12300  10000
2   42500  10000
3  133300  10000

 

Code #2:

filter_none

edit
close

play_arrow

link
brightness_4
code

# importing pandas module 
import pandas as pd 
import numpy as np 
  
df1 = pd.DataFrame({'a': ['Geeks', 'For', 'geeks', 'for', 'real'], 
                    'b': [11, 1.025, 333, 114.48, 1333]}) 
  
data = {'item1':df1, 'item2':df1} 
  
# creating Panel 
panel = pd.Panel.from_dict(data, orient ='minor'
print("panel['b'] is - \n\n", panel['b'], '\n'
  
# Create a 5 * 5 dataframe 
df2 = pd.DataFrame(np.random.rand(5, 2), columns =['item1', 'item2']) 
print("Newly create dataframe with random values is - \n\n", df2)
  
print("\nMultiplying panel['b'] with df2 using rmul() method - \n"
print(panel['b'].rmul(df2, axis = 0)) 

chevron_right


Output:

panel['b'] is - 

       item1     item2
0    11.000    11.000
1     1.025     1.025
2   333.000   333.000
3   114.480   114.480
4  1333.000  1333.000 

Newly create dataframe with random values is - 

       item1     item2
0  0.549490  0.658451
1  0.321557  0.139482
2  0.010817  0.775445
3  0.011675  0.333828
4  0.818014  0.462602

Multiplying panel['b'] with df2 using rmul() method - 

         item1       item2
0     6.044385    7.242957
1     0.329596    0.142969
2     3.602168  258.223060
3     1.336504   38.216583
4  1090.412087  616.648529

 

Code #3:

filter_none

edit
close

play_arrow

link
brightness_4
code

# importing pandas module 
import pandas as pd 
import numpy as np 
  
df1 = pd.DataFrame({'a': ['Geeks', 'For', 'geeks', 'for', 'real'], 
                    'b': [11, 1.025, 333, 114.48, 1333]}) 
                      
df2 = pd.DataFrame({'a': ['I', 'am', 'DataFrame', 'number', 'two'], 
                    'b': [10, 10, 10, 110, 110]})                     
                      
data = {'item1':df1, 'item2':df2} 
  
# creating Panel 
panel = pd.Panel.from_dict(data, orient ='minor'
  
print("panel['b'] is - \n\n", panel['b'], '\n'
  
print("\nMultiplying panel['b']['item1'] with df2['b'] or panel['b']['item2'] using rmul() method - \n"
print("\n", panel['b']['item1'].rmul(df2['b'], axis = 0)) 

chevron_right


Output:

panel['b'] is - 

       item1  item2
0    11.000     10
1     1.025     10
2   333.000     10
3   114.480    110
4  1333.000    110 


Multiplying panel['b']['item1'] with df2['b'] or panel['b']['item2'] using rmul() method - 


 0       110.00
1        10.25
2      3330.00
3     12592.80
4    146630.00
dtype: float64

 



My Personal Notes arrow_drop_up

Check out this Author's contributed articles.

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.