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.size gives the number of rows if Series. Otherwise return the number of rows times number of columns if DataFrame.
Syntax: Panel.size
Parameters: None
Returns: Returns value in int representing the number of elements in this object.
Code #1:
# 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]}) print("df1 is - \n\n", df1) # Create a 5 * 5 dataframe df2 = pd.DataFrame(np.random.rand(10, 2), columns =['a', 'b']) print("df2 is - \n\n", df2) |
Now, let’s create the Panel using dict of df1 and df2, and get the size of that panel.
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("\nSize of panel['b'] is - ", panel['b'].size) |
Output:
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') print("\nSize of panel['b'] is - ", panel['b'].size) |
Output:
Code #3:
# importing pandas module import pandas as pd import numpy as np df1 = pd.DataFrame({'a': ['Geeks', 'For', 'neveropen', '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("\nSize of panel['b'] is - ", panel['b'].size) |
Output:
