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.count() function is used to return number of observations over requested axis.
Syntax: Panel.count(axis=’major’)
Parameters: axis : {‘items’, ‘major’, ‘minor’} or {0, 1, 2}
Returns: count of DataFrame
Code #1:
# 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]}) data = {'item1':df1, 'item2':df1} # creating Panel panel = pd.Panel.from_dict(data, orient ='minor') print(panel, "\n") print(panel['b']) print("\n", panel['b'].count()) |
Output:
Code #2:
# importing pandas module import pandas as pd import numpy as np df1 = pd.DataFrame({'a': ['Geeks', 'For', 'neveropen'], 'b': np.random.randn(3)}) data = {'item1':df1, 'item2':df1} # creating Panel panel = pd.Panel.from_dict(data, orient ='minor') print(panel, "\n") print(panel['b']) df2 = pd.DataFrame({'b': [11, 12, 13]}) print("\n", panel['b'].count()) |
Output:
