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 or Series of the same size containing the cumulative maximum.
Syntax: Panel.cummax(axis=None, skipna=True, *args, **kwargs)
Parameters:
axis : The index or the name of the axis. 0 is equivalent to None or ‘index’.
skipna : Exclude NA/null values. If an entire row/column is NA, the result will be NA.Returns: Cummax of DataFrame or Panel
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]})                       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'].cummax(axis = 0)) |
Output:
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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'].cummax(axis = 0)) |
Output:
