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.mod() function is used to get the module of series and dataframe/Panel.
Syntax: Panel.mod(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("\nModulo of panel['b'] with df2['b'] using mod() method - \n") print("\n", panel['b'].mod(df2['b'], axis = 0)) |
Output:
panel['b'] is -
item1 item2
0 111 100
1 123 100
2 425 100
3 1333 100
Modulo of panel['b'] with df2['b'] using mod() method -
item1 item2
0 11 0
1 23 0
2 25 0
3 33 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("\nModulo of panel['b'] with df2 using mod() method - \n") print(panel['b'].mod(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 0.003619 0.293626
1 0.624030 0.360525
2 0.335041 0.450568
3 0.414065 0.120144
4 0.842085 0.222036
Modulo of panel['b'] with df2 using mod() method -
item1 item2
0 0.001529 0.135848
1 0.400970 0.303949
2 0.303965 0.030172
3 0.197954 0.103345
4 0.820835 0.118100
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("\nModulo of panel['b']['item1'] with df2['b'] or panel['b']['item2'] using mod() method - \n") print("\n", panel['b']['item1'].mod(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
Modulo of panel['b']['item1'] with df2['b'] or panel['b']['item2'] using mod() method -
0 1.000
1 1.025
2 3.000
3 4.480
4 13.000
dtype: float64
