PYTHON

Insert numpy array to column

new_arr = np.insert(arr, index, arr_to_insert, axis=1)

how to add column to np array

x1= data[:,:-1]
x = np.insert(x1, index(0), values=1, axis=1)
#to add a column of 1's in the features matrix

add column array python

>>> a = np.array([[1,2,3],[2,3,4]])
>>> a
array([[1, 2, 3],
       [2, 3, 4]])

>>> z = np.zeros((2,1), dtype=int64)
>>> z
array([[0],
       [0]])

>>> np.append(a, z, axis=1)
array([[1, 2, 3, 0],
       [2, 3, 4, 0]])

numpy add new column

: import numpy as np
: N = 3
: A = np.eye(N)

: np.c_[ A, np.ones(N) ]              # add a column
array([[ 1.,  0.,  0.,  1.],
       [ 0.,  1.,  0.,  1.],
       [ 0.,  0.,  1.,  1.]])

add column to existing numpy array

b = np.insert(a, insert_index, values=a[:,2], axis=1)

add a new column to numpy array

import numpy as np
N = 10
a = np.random.rand(N,N)
b = np.zeros((N,N+1))
b[:,:-1] = a

add column array python

import numpy as np
N = 10
a = np.random.rand(N,N)
b = np.zeros((N,N+1))
b[:,:-1] = a

add a new column to numpy array

Returns
-------
append : ndarray
    A copy of `arr` with `values` appended to `axis`.  Note that `append`
    does not occur in-place: a new array is allocated and filled.  If
    `axis` is None, `out` is a flattened array.

add numpy to pandas column

df['new_column'] = array_name.tolist()