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.cumsum() function is used to returns a DataFrame or Series of the same size containing the cumulative sum.
Syntax: Panel.cumsum(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: Cumsum 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['b']) print("\n", panel['b'].cumsum(axis = 0)) |
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['b']) print("\n", panel['b'].cumsum(axis = 0)) |
Output:
