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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 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)
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 otherinplace, 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

Return Value

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


❮ DataFrame Reference