Python | Pandas Panel.rtruediv()

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.rtruediv() function is used to get the floating division of series and dataframe/Panel.

Syntax: Panel.rtruediv(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', '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("\nFloating Dividing panel['b'] with df2['b'] using rtruediv() method - \n")
print("\n", panel['b'].rtruediv(df2['b'], axis = 0))

Output:

panel['b'] is - 

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

Floating Dividing panel['b'] with df2['b'] using rtruediv() method - 


       item1  item2
0  0.900901      1
1  0.813008      1
2  0.235294      1
3  0.075019      1

Code #2:

# 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("\nFloating Dividing panel['b'] with df2 using rtruediv() method - \n")
print(panel['b'].rtruediv(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  0.809990  0.358019
1  0.765535  0.101660
2  0.788052  0.742361
3  0.964031  0.618767
4  0.862207  0.131611

Floating Dividing panel['b'] with df2 using rtruediv() method - 

      item1     item2
0  0.073635  0.032547
1  0.746864  0.099180
2  0.002367  0.002229
3  0.008421  0.005405
4  0.000647  0.000099

Code #3:

# 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("\nFloating Dividing panel['b']['item1'] with df2['b'] or panel['b']['item2'] using rtruediv() method - \n")
print("\n", panel['b']['item1'].rtruediv(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 


Floating Dividing panel['b']['item1'] with df2['b'] or panel['b']['item2'] using rtruediv() method - 


 0    0.909091
1    9.756098
2    0.030030
3    0.960867
4    0.082521
dtype: float64