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How to remove NaN from a Pandas Series?
In the pandas series constructor, the method called dropna() is used to remove missing values from a series object. And it does not update the original series object with removed NaN values instead of updating the original series object, it will return another series object with updated values.
The parameters of the dropna() method are axis, inplace, and how.
Example 1
# importing packages import pandas as pd import numpy as np # Creating Series objects sr = pd.Series([42, np.nan, 55, 42, np.nan, 73, np.nan, 55, 76, 87], index=list("ABCDEFGHIJ")) print('Series object:',sr) # Remove missing elements result = sr.dropna() # display output print(result)
Explanation
Initially, we have created a pandas Series with labeled index values and there are some Nan values present in the series object. After creating a pandas series object we have applied the dropna() method to remove missing values.
Output
Series object: A 42.0 B NaN C 55.0 D 42.0 E NaN F 73.0 G NaN H 55.0 I 76.0 J 87.0 dtype: float64 A 42.0 C 55.0 D 42.0 F 73.0 H 55.0 I 76.0 J 87.0 dtype: float64
In the above output block, we can see both initial and resultant series objects. The second series object is the output object with removed missing values.
Example 2
# importing packages import pandas as pd import numpy as np dates = pd.date_range('2021-06-01', periods=10, freq='D') #creating pandas Series with date index sr = pd.Series([np.nan, 61, 72, 11, np.nan, 24, 56, 30, np.nan, 55], index=dates) print('Series object:',sr) # Remove missing elements result = sr.dropna() # display output print(result)
Explanation
In the following example, we have created a pandas Series with date range index values and there are some Nan values present in the series object “sr”. After creating a pandas series object we applied the dropna() method to remove those Nan values.
Output
Series object: 2021-06-01 NaN 2021-06-02 61.0 2021-06-03 72.0 2021-06-04 11.0 2021-06-05 NaN 2021-06-06 24.0 2021-06-07 56.0 2021-06-08 30.0 2021-06-09 NaN 2021-06-10 55.0 Freq: D, dtype: float64 2021-06-02 61.0 2021-06-03 72.0 2021-06-04 11.0 2021-06-06 24.0 2021-06-07 56.0 2021-06-08 30.0 2021-06-10 55.0 dtype: float64
Here we got a new series object with removed Nan values. In the above output block, we can see both initial and resultant series objects. The first object is the initial series, and the second one is the output of the dropna() method.