Python | Pandas Panel.add()

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.add() function is used for element-wise addition of series and series/dataframe.
Syntax: Panel.add(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', 'zambiatek', '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') print("\nAdding panel['b'] with df1['b'] using add() method - \n") print("\n", panel['b'].add(df1['b'], axis = 0)) |
Output:
Code #2:
# importing pandas module import pandas as pd import numpy as np df1 = pd.DataFrame({'a': ['Geeks', 'For', 'zambiatek', '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("\nAdding panel['b'] with df2 using add() method - \n") print(panel['b'].add(df2, axis = 0)) |
Output:
Code #3:
# importing pandas module import pandas as pd import numpy as np df1 = pd.DataFrame({'a': ['Geeks', 'For', 'zambiatek', 'real'], 'b': [-11, +1.025, -114.48, 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("\nAdding panel['b'] with df2['b'] using add() method - \n") print("\n", panel['b'].add(df2['b'], axis = 0)) |
Output:




