Python | Pandas Panel.add() Last Updated : 28 Jan, 2019 Summarize Comments Improve Suggest changes Share Like Article Like Report 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 over Returns: Panel Code #1: Python3 1== # 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') print("\nAdding panel['b'] with df1['b'] using add() method - \n") print("\n", panel['b'].add(df1['b'], axis = 0)) Output: Code #2: Python3 1== # 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("\nAdding panel['b'] with df2 using add() method - \n") print(panel['b'].add(df2, axis = 0)) Output: Code #3: Python3 1== # importing pandas module import pandas as pd import numpy as np df1 = pd.DataFrame({'a': ['Geeks', 'For', 'geeks', '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: Comment More infoAdvertise with us Next Article Python | Pandas Panel.add() S Shivam_k Follow Improve Article Tags : Python Python-pandas Python pandas-panel Python pandas-panel-methods Practice Tags : python Similar Reads Python | Pandas Panel.div() 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.div() function is used to get the divis 2 min read Python | Pandas Panel.mod() 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 modul 3 min read Python | Pandas Panel.abs() 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. Panel.abs() function is used to return a Series/DataFra 1 min read Python | Pandas Panel.mul() 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.mul() function is used to get the multi 2 min read Python | Pandas Panel.cummax() 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. Panel.cummax() function is used to returns a DataFrame 2 min read Like