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How to replace NaN values by Zeroes in a column of a Pandas Series?
To replace NaN values by zeroes or other values in a column of Pandas Series, we can use s.fillna() method.
Create a one-dimensional ndarray with axis labels (including time series).
Print the input series.
Use s.fillna(0) to replace NaN in the series with value 0.
Similarly, use s.fillna(5) and s.fillna(7) to replace NaN in series with values 5 and 7, respectively.
Print the replaced NaN series.
import pandas as pd import numpy as np s = pd.Series([1, np.nan, 3, np.nan, 3, np.nan, 7, np.nan, 3]) print "Input series is:\n", s print "After replacing NaN with 0:\n", s.fillna(0) print "After replacing NaN with 5:\n", s.fillna(5) print "After replacing NaN with 7:\n", s.fillna(7)
Input series is: x y z 0 5.0 NaN NaN 1 NaN 1.0 1.0 2 1.0 NaN NaN 3 NaN 10.0 NaN After replacing NaN with 0: x y z 0 5.0 0.0 0.0 1 0.0 1.0 1.0 2 1.0 0.0 0.0 3 0.0 10.0 0.0 After replacing NaN with 5: x y z 0 5.0 5.0 5.0 1 5.0 1.0 1.0 2 1.0 5.0 5.0 3 5.0 10.0 5.0 After replacing NaN with 7: x y z 0 5.0 7.0 7.0 1 7.0 1.0 1.0 2 1.0 7.0 7.0 3 7.0 10.0 7.0
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