Series.product() function in pandas computes the product of the elements in the series.
Series.product(axis=None, skipna=True, level=None, numeric_only=None, min_count=0)
axis: This indicates the axis in which the operation is to be performed. The value
1indicates rows and columns, respectively. The default is
skipna: This is used to eliminate NAN or null values when calculating the result. The default is
level(optional): The default value is
None. It represents the level to be broadcasted(in the case of multilevel).
numeric_only: Only float, int, and boolean columns are allowed. If there is None, it will try to use everything. Otherwise, it will just use numerical data. Not used during the Series.
min_count: This represents the minimum number of valid values needed to complete the operation. The default is
The following code will demonstrate how to use the
Series.product() function in pandas:
import pandas as pd import numpy as np # create Series my_series = pd.Series([17, np.nan, 28, 15, 23, 7, np.nan]) # compute the product of the series # using product() print(my_series.product(skipna=True))
In the code above:
Line 5: We create the Series,
Line 9: We use the
product() function to return the product of the Series elements.
Note: The NaN values are dropped by setting the
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