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null value replace from np,nan in python

df.replace('', np.nan, inplace=True)
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python numpy array replace nan with string

import numpy as np
l=['foo', 'bar', 'baz', np.nan]

l_new=['missing' if x is np.nan else x for x in l]

print l_new
# Result:
# ['foo', 'bar', 'baz', 'missing']
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replace nan numpy array

from numpy import *

a = array([[1, 2, 3], [0, 3, NaN]])
where_are_NaNs = isnan(a)
a[where_are_NaNs] = 0
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