I have an array :
e = np.array([[ 0, 1, 2, 3, 5, 6, 7, 8],
[ 4, 5, 6, 7, 5, 3, 2, 5],
[ 8, 9, 10, 11, 4, 5, 3, 5]])
I want to extract array by its columns in RANGE, if I want to take column in range 1 until 5, It will return
e = np.array([[ 1, 2, 3, 5, ],
[ 5, 6, 7, 5, ],
[ 9, 10, 11, 4, ]])
How to solve it? Thanks
You can just use e[:, 1:5] to retrive what you want.
In [1]: import numpy as np
In [2]: e = np.array([[ 0, 1, 2, 3, 5, 6, 7, 8],
...: [ 4, 5, 6, 7, 5, 3, 2, 5],
...: [ 8, 9, 10, 11, 4, 5, 3, 5]])
In [3]: e[:, 1:5]
Out[3]:
array([[ 1, 2, 3, 5],
[ 5, 6, 7, 5],
[ 9, 10, 11, 4]])
https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html
e[:, 1:5].
Numpy row and column indices start counting at 0.
The rows are specified first and then the column with a comma to separate the row from column.
The ":" (colon) is used to shortcut all rows or all columns when it is used alone.
When the row or column specifier has a range, then the ":" is paired with numbers that specify the inclusive start range and the exclusive end range.
For example
import numpy as np
np_array = np.array( [ [ 1, 2, 3, ],
[ 4, 5, 6, ],
[ 7, 8, 9 ] ] )
first_row = np_array[0,:]
first_row
output: array([1, 2, 3])
last_column = np_array[:,2]
last_column
output: array([3, 6, 9])
first_two_vals = np_array[0,0:2]
first_two_vals
output: array([1, 2])
You can use np.take with specifying axis=1
import numpy as np
e = np.array([[ 0, 1, 2, 3, 5, 6, 7, 8],
[ 4, 5, 6, 7, 5, 3, 2, 5],
[ 8, 9, 10, 11, 4, 5, 3, 5]])
e = np.take(e, [1,2,3,4], axis=1)
output:
array([[ 1, 2, 3, 5],
[ 5, 6, 7, 5],
[ 9, 10, 11, 4]])
https://numpy.org/doc/stable/reference/generated/numpy.take.html
