Extract Specific RANGE of columns in numpy array Python
You can just use e[:, 1:5] to retrive what you want.
In [1]: import numpy as npIn [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
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 npnp_array = np.array( [ [ 1, 2, 3, ], [ 4, 5, 6, ], [ 7, 8, 9 ] ] )first_row = np_array[0,:]first_rowoutput: array([1, 2, 3])last_column = np_array[:,2]last_columnoutput: array([3, 6, 9])first_two_vals = np_array[0,0:2]first_two_valsoutput: array([1, 2])