I have one array with shape: (15,2). I also have another array with values: [0, 3, 5].
I want to create another column in the first array with values from the second array, where the first 5 rows has value 0, rows 6-10 has value 3, and the last 5 rows has value 5.
like so:
[0,
0,
0,
0,
0,
3,
3,
3,
3,
3,
5,
5,
5,
5,
5]
is there any numpy method that does that?
Thanks!
You can use numpy's built-in repeat and stacking:
a = np.zeros((15,2))
b = np.array([0,3,5])
np.hstack((a, np.repeat(b,5)[:,None]))
output:
[[0. 0. 0.]
[0. 0. 0.]
[0. 0. 0.]
[0. 0. 0.]
[0. 0. 0.]
[0. 0. 3.]
[0. 0. 3.]
[0. 0. 3.]
[0. 0. 3.]
[0. 0. 3.]
[0. 0. 5.]
[0. 0. 5.]
[0. 0. 5.]
[0. 0. 5.]
[0. 0. 5.]]
[:,None] slicing?
None adds an extra dimension to array (in the place it is added, here 2nd dimension in [:,None]). It is an alias for np.newaxis. Basically, we are adding another dimension so that when we stack, we stack correct dimensions together.rand = np.random.random((15,2)) # shape is (15,2)
vals = np.array([0,3,5]) # shape is (3,)
res = np.concatenate(([np.full((rand.shape[0]//vals.shape[0],), val) for val in vals]), axis=0)
res
output:
array([0, 0, 0, 0, 0, 3, 3, 3, 3, 3, 5, 5, 5, 5, 5])
Finally,
final = np.hstack((rand, res.reshape(15,1)))
final
output:
array([[0.29759807, 0.60548479, 0. ],
[0.61242249, 0.46456274, 0. ],
[0.86172011, 0.2963868 , 0. ],
[0.91728575, 0.36366023, 0. ],
[0.56488556, 0.82130321, 0. ],
[0.59482141, 0.46148353, 3. ],
[0.7762271 , 0.25415058, 3. ],
[0.09176551, 0.9687253 , 3. ],
[0.06473259, 0.34686598, 3. ],
[0.69542414, 0.15540001, 3. ],
[0.02880707, 0.23169327, 5. ],
[0.90004256, 0.22145591, 5. ],
[0.61596969, 0.46807342, 5. ],
[0.02263769, 0.68522023, 5. ],
[0.81777274, 0.58145853, 5. ]])
Use np.concatenate.
a = [0, 0, 0, 0, 0, 3, 3, 3, 3, 3, 5, 5, 5, 5, 5] # your list of [0, 3, 5]
a = np.array([a]).T # [ [0], [0], [0], ..., [5] ] the "vector" array
then simply
b = np.array([[i, i +1] for i in range(15)]) # some example 15x2 array
print(np.concatenate((b, a), axis=1))
The output is
array([[ 0, 1, 0],
[ 1, 2, 0],
[ 2, 3, 0],
[ 3, 4, 0],
[ 4, 5, 0],
[ 5, 6, 3],
[ 6, 7, 3],
[ 7, 8, 3],
[ 8, 9, 3],
[ 9, 10, 3],
[10, 11, 5],
[11, 12, 5],
[12, 13, 5],
[13, 14, 5],
[14, 15, 5]])
