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Pandas Series: mask() function

Replace values in Pandas Series

The mask() function is used to replace values where the condition is True.

Syntax:

Series.mask(self, cond, other=nan, inplace=False, axis=None, level=None, errors='raise', try_cast=False)
Pandas Series mask image

Parameters:

Name Description Type/Default Value Required / Optional
cond Where cond is False, keep the original value. Where True, replace with corresponding value from other. If cond is callable, it is computed on the Series/DataFrame and should return boolean Series/DataFrame or array. The callable must not change input Series/DataFrame (though pandas doesn’t check it). boolean Series/DataFrame, array-like, or callable Required
other Entries where cond is True are replaced with corresponding value from other. If other is callable, it is computed on the Series/DataFrame and should return scalar or Series/DataFrame. The callable must not change input Series/DataFrame (though pandas doesn’t check it). scalar, Series/DataFrame, or callable Required
inplace Whether to perform the operation in place on the data. bool
Default Value: False
Required
axis Alignment axis if needed. int
Default Value: None
Required
level Alignment level if needed. int
Default Value: None
Required
errors Note that currently this parameter won’t affect the results and will always coerce to a suitable dtype.
  • ‘raise’ : allow exceptions to be raised.
  • ‘ignore’ : suppress exceptions. On error return original object.
str, {‘raise’, ‘ignore’}
Default Value: ‘raise’
Required
try_cast Try to cast the result back to the input type (if possible). bool
Default Value: False
Required

Returns: Same type as caller

Notes: The mask method is an application of the if-then idiom. For each element in the calling DataFrame, if cond is False the element is used; otherwise the corresponding element from the DataFrame other is used.
The signature for DataFrame.where() differs from numpy.where(). Roughly df1.where(m, df2) is equivalent to np.where(m, df1, df2).

For further details and examples see the mask documentation in indexing.

Example:


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