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Pandas DataFrame: mask() function

DataFrame - mask() function

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

Syntax:

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

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

Example:


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