Menu
Is there a way to remove a NaN values from a panda series? I have a series that may or may not have some NaN values in it, and I'd like to return a copy of the series with all the NaNs removed.
867
Use dropna() function to drop rows with NaN / None values in pandas DataFrame. Python doesn't support Null hence any missing data is represented as None or NaN. NaN stands for Not A Number and is one of the common ways to represent the missing value in the data.
From a pandas Series a set of elements can be removed using the index, index labels through the methods drop() and truncate(). The drop() method removes a set of elements at specific index locations. The locations are specified by index or index labels.
Analyze and drop Rows/Columns with Null values in a Pandas series. The dropna() function is used to return a new Series with missing values removed. There is only one axis to drop values from. If True, do operation inplace and return None.
Pandas dropna() - Drop Null/NA Values from DataFrame.
>>> s = pd.Series([1,2,3,4,np.NaN,5,np.NaN]) >>> s[~s.isnull()] 0 1 1 2 2 3 3 4 5 5 update or even better approach as @DSM suggested in comments, using pandas.Series.dropna():
>>> s.dropna() 0 1 1 2 2 3 3 4 5 5 If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
