How can I transform my array to 0 or 1 elements?

Question

[[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [0 1 1 1 0 0 0 0 0 1 1 0 0 3 3 0 0 0 4 4 0 0 0 5 5 5 5 0 0 2 2 2 2 2 0 2 2 2 2 2 0 0 0 6 6 6 6 6 6 0 6 6 6 6] [0 1 1 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 4 4 0 0 5 5 5 5 5 5 0 2 2 2 2 2 2 2 2 2 2 2 2 0 0 6 6 6 6 6 6 6 6 6 6 6] [1 1 1 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 4 4 0 5 5 5 0 0 5 5 5 0 2 2 0 0 2 2 0 0 0 2 2 0 0 6 6 0 0 6 6 6 0 0 6 6] [1 1 1 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 4 4 0 5 5 5 5 0 0 0 0 0 2 2 0 2 2 2 0 0 0 2 2 2 0 6 6 0 0 0 6 6 0 0 6 6] [1 1 1 0 0 0 0 0 0 0 0 0 0 3 3 0 0 0 4 4 0 0 5 5 5 5 5 5 0 0 2 2 0 2 2 2 0 0 0 2 2 2 0 6 6 0 0 0 6 6 0 0 6 6] [0 1 1 0 0 0 0 0 0 7 0 0 0 3 3 0 0 0 4 4 0 0 0 0 5 5 5 5 5 0 2 2 0 2 2 2 0 0 0 2 2 2 0 6 6 0 0 0 6 6 0 0 6 6]]

what i want is to change the value of every none 0 number to 1.

what i can do:

for element in list: for sub_element in element: if sub_element != 0: sub_element = 1

How can i do that in numpy?

a[a!=0] = 1 ?

MaxU - stand with Ukraine
– MaxU - stand with Ukraine

2018-06-19 10:55:40 +00:00
Commented Jun 19, 2018 at 10:55 — MaxU - stand with Ukraine
– MaxU - stand with Ukraine, Commented Jun 19, 2018 at 10:55

Jan Spurny · Accepted Answer · 2018-06-19 10:59:43Z

If your numpy array is named a, you can use something like this:

a[a!=0.0] = 1

proof:

>>> a = numpy.array([0.0, 1.0, 2.0, 3.0, 0.0, 10.0]) >>> a array([ 0., 1., 2., 3., 0., 10.]) >>> a[a!=0.0] = 1 >>> a array([ 0., 1., 1., 1., 0., 1.])

This works because a != 0.0 will return array with True/False values where the condition is met and then the assignment is performed only on those elements where there is True:

>>> a != 0 array([False, True, True, True, False, True], dtype=bool)

Also, this works with any other condition.

jpp · Accepted Answer · 2018-06-19 11:01:01Z

2

Given a NumPy array A:

res = A.astype(bool).astype(int)

For efficiency, and most use cases, you can keep your array as Boolean, omitting the integer conversion.

This works because 0 is the only integer considered False; all others are True. Converting a Boolean array to int is then a trivial mapping of False to 0 and True to 1.

edited Jun 19, 2018 at 11:01

answered Jun 19, 2018 at 10:55

jpp

166k37 gold badges301 silver badges362 bronze badges

3 Comments

Nelly Over a year ago

I checked with np.unique(A) and seems to be correct as 0 and 1 are the only values, may you edit the answer to explain how that line works as i didn't understand it, thanks.

jpp Over a year ago

@Nelly, Sure, I added an explanation.

jpp Over a year ago

@RoadRunner, I wouldn't go that far. In many cases, I think Boolean arrays are hugely underrated, you don't need the astype(int) part most times; it's true NumPy may take a byte to store a Boolean, but when you start storing large arrays in other formats (e.g. HDF5) it plays a part.

Collectives™ on Stack Overflow

How can I transform my array to 0 or 1 elements?

2 Answers 2

Comments

3 Comments

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

Comments

3 Comments

Related