Last Updated : 10 Oct, 2018
Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages.
Pandasis one of those packages and makes importing and analyzing data much easier. Pandas
Series.prod()
method is used to get the product of the values for the requested axis.
Syntax: Series.prod(axis=None, skipna=None, level=None, numeric_only=None, min_count=0) Parameters: axis : {index (0)} skipna[boolean, default True] : Exclude NA/null values. If an entire row/column is NA, the result will be NA level[int or level name, default None] : If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar. numeric_only[boolean, default None] : Include only float, int, boolean data. If None, will attempt to use everything, then use only numeric data Returns: Return the product of the values for the requested axisCode #1:
By default, product of an empty or all-NA Series is 1.
Python3 1==
# importing pandas module
import pandas as pd
# min_count = 0 is the default
pd.Series([]).prod()
# When passed min_count = 1,
# product of an empty series will be NaN
pd.Series([]).prod(min_count = 1)
Output:
1.0 nanCode #2: Python3 1==
# importing pandas module
import pandas as pd
# applying prod() on a list of series
val = pd.Series([12, 5, 7]).prod()
val
Output:
420
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