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 overReturns: 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("\nMultiplying panel['b'] with df2['b'] using rmul() method - \n") print("\n", panel['b'].rmul(df2['b'], axis = 0)) |
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
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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("\nMultiplying panel['b'] with df2 using rmul() method - \n") print(panel['b'].rmul(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 0.549490 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
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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("\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)) |
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
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