Replacing Masked Values (--) With A Null Or None Value Using Fiil_value From Ma Numpy In Python

Is there a way to replace a masked value in a numpy masked array as a null or None value? This is what I have tried but does not work. for stars in range(length_masterlist_final):

Solution 1:

Use Astropy:

>>> from pandas import DataFrame
>>> from astropy.table import Table
>>> import numpy as np
>>> 
>>> df = DataFrame()
>>> df['a'] = [1, np.nan, 2]
>>> df['b'] = [3, 4, np.nan]
>>> df
    a   b
0   1   3
1 NaN   4
2   2 NaN
>>> t = Table.from_pandas(df)
>>> t
<Table masked=True length=3>
   a       b   
float64 float64
------- -------
    1.0     3.0
     --     4.0
    2.0      --
>>> t.write('photometry.csv', format='ascii.csv')
>>> 
(astropy)neptune$ cat photometry.csv 
a,b
1.0,3.0
,4.0
2.0,

You can specify arbitrary transformations from table values to output values using the fill_values parameter (http://docs.astropy.org/en/stable/io/ascii/write.html#parameters-for-write).