Pandas DataFrame Mask() Method - W3Schools

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Pandas DataFrame mask() Method

❮ DataFrame Reference

Example

Set to NaN, all values where the age IS over 30:

import pandas as pddata = { "age": [50, 40, 30, 40, 20, 10, 30], "qualified": [True, False, False, False, False, True, True]}df = pd.DataFrame(data)newdf = df.mask(df["age"] > 30) Try it Yourself »

Definition and Usage

The mask() method replaces the values of the rows where the condition evaluates to True.

The mask() method is the opposite of the The where() method.

Syntax

dataframe.mask(cond, other, inplace, axis, level, errors, try_cast)

Parameters

The other, inplace, axis, level, errors, try_cast parameters are keyword arguments.

Parameter Value Description
cond Required. An expression or function that evacuates to either True or False
other StringNumberSeriesDataFrame Optional. A set of values to replace the rows that evaluates to True with
inplace TrueFalse Optional, default False. Specifies whether to perform the operation on the original DataFrame or not, if not, which is default, this method returns a new DataFrame
axis NumberNone Optional, default None. Specifies the alignment axis
level NumberNone Optional, default None. Specifies the alignment level
errors 'raise''ignore' Optional, default 'raise'. Specifies what to do with exceptions
try_cast TrueFalse Optional, default False. Specifies whether to try to cast the result back to the input type or not

Return Value

A DataFrame with the result, or None if the inplace parameter is set to True.

❮ DataFrame Reference

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