CODEWITHSUNDEEP
pythonnumpy
Richard Rublev
Richard Rublev

Reputation: 8164

Why my mask failed in Python?

My code:

#!/usr/bin/python

import numpy as np

names = np.array(['Bob', 'Joe', 'Will', 'Bob', 'Will', 'Joe', 'Joe'])
data = np.random.randn(7, 4) + 0.8

print (data)

mask2= ((names != 'Joe') == 7.0)
d2 = data[mask2]
print (d2)

d3 = data[names != 'Joe'] = 7.0
print (d3)

Actually,my intention was to get the same solution both with mask and with other expression. I have solved it with Patric,s help

mask2= (names != 'Joe')
data[mask2] = 7.0
print (data)

Then I have:

[[ 7.          7.          7.          7.        ]
 [-0.73168514  2.26996071 -0.24892468  1.31421193]
 [ 7.          7.          7.          7.        ]
 [ 7.          7.          7.          7.        ]
 [ 7.          7.          7.          7.        ]
 [ 0.74771766  2.44888399  0.62641731 -0.12963696]
 [ 0.08604169  2.25468039  2.1960925   0.88218726]]

Upvotes: 0

Views: 96

Answers (2)

manu190466
manu190466

Reputation: 1603

Not sure to understand, but if you expect 7.0 in all rows except Joe's, maybe what you want is :

data[names != 'Joe'] = 7.0
print data

Upvotes: 1

bakkal
bakkal

Reputation: 55448

mask2 = ((names != 'Joe') == 7.0)

Why my mask failed in Python?

This mask doesn't make sense, with that expression, you are compared the result of names != 'Joe' with 7.0

In [13]: names != 'Joe'
Out[13]: array([ True, False,  True,  True,  True, False, False], dtype=bool)

So it's natural that this will get you all False everywhere:

In [14]: ((names != 'Joe') == 7.0)
Out[14]: array([False, False, False, False, False, False, False], dtype=bool)

Your other mask makes sense, something in this form:

x[mask] = value

Upvotes: 2

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