Pandas DataFrame mask() Method

Example

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

import pandas as pd

data = {
"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)

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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	String Number Series DataFrame	Optional. A set of values to replace the rows that evaluates to True with
inplace	`True False`	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	Number `None`	Optional, default None. Specifies the alignment axis
level	Number `None`	Optional, default None. Specifies the alignment level
errors	`'raise' 'ignore'`	Optional, default 'raise'. Specifies what to do with exceptions
try_cast	`True False`	Optional, default False. Specifies whether to try to cast the result back to the input type or not