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Python | Pandas Panel.rsub()

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.rsub() function is used to get the subtraction of series and dataframe/Panel.

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

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

Returns: Panel

Code #1:




# importing pandas module 
import pandas as pd 
import numpy as np 
  
df1 = pd.DataFrame({'a': ['Geeks', 'For', 'neveropen', '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("\nSubtracting panel['b'] with df2['b'] using rsub() method - \n") 
print("\n", panel['b'].rsub(df2['b'], axis = 0)) 


Output:

panel['b'] is - 

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

Subtracting panel['b'] with df2['b'] using rsub() method - 

    item1  item2
0    -11      0
1    -23      0
2   -325      0
3  -1233      0

 

Code #2:




# importing pandas module 
import pandas as pd 
import numpy as np 
  
df1 = pd.DataFrame({'a': ['Geeks', 'For', 'neveropen', '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("\nSubtracting panel['b'] with df2 using rsub() method - \n") 
print(panel['b'].rsub(df2, axis = 0)) 


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  0.159943  0.383040
1  0.769608  0.776670
2  0.038762  0.889516
3  0.672955  0.094725
4  0.127130  0.729699

Subtracting panel['b'] with df2 using rsub() method - 

         item1        item2
0   -10.840057   -10.616960
1    -0.255392    -0.248330
2  -332.961238  -332.110484
3  -113.807045  -114.385275
4 -1332.872870 -1332.270301

 

Code #3:




# importing pandas module 
import pandas as pd 
import numpy as np 
  
df1 = pd.DataFrame({'a': ['Geeks', 'For', 'neveropen', '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("\nSubtracting panel['b']['item1'] with df2['b'] or panel['b']['item2'] using rsub() method - \n") 
print("\n", panel['b']['item1'].rsub(df2['b'], axis = 0)) 


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 


Subtracting panel['b']['item1'] with df2['b'] or panel['b']['item2'] using rsub() method - 


 0      -1.000
1       8.975
2    -323.000
3      -4.480
4   -1223.000
dtype: float64
Last Updated :
28 Jan, 2019
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