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Numpy MaskedArray.astype() function | Python

Last Updated : 16 Jun, 2021

In many circumstances, datasets can be incomplete or tainted by the presence of invalid data. For example, a sensor may have failed to record a data, or recorded an invalid value. The numpy.ma module provides a convenient way to address this issue, by introducing masked arrays.Masked arrays are arrays that may have missing or invalid entries.
numpy.MaskedArray.astype() function returns a copy of the MaskedArray cast to given newtype.
 

Syntax : numpy.MaskedArray.astype(newtype)
Parameters: 
newtype : Type in which we want to convert the masked array.
Return : [MaskedArray] A copy of self cast to input newtype. The returned record shape matches self.shape.


Code #1 : 
 


Output: 
Input array : [ 1 2 3 -1 5]
Masked array : [1 2 -- -1 5]
int32
Output typecasted array : [1.0 2.0 -- -1.0 5.0]
float64

 

 
Code #2 : 
 


Output: 
Input array : [10.1 20.2 30.3 40.4 50.5]
Masked array : [-- 20.2 -- 40.4 50.5]
float64
Output typecasted array : [-- 20 -- 40 50]
int32

 
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