np.rehape ()
a = np.arange(6).reshape((3, 2))
>>> a
array([[0, 1],
[2, 3],
[4, 5]])
Careful Caterpillar
a = np.arange(6).reshape((3, 2))
>>> a
array([[0, 1],
[2, 3],
[4, 5]])np_scaled = scaler.fit_transform(data.values.reshape(-1,1))'''
This code is contributed by :
Tanishq Vyas (github : https://github.com/tanishqvyas )
'''
actual = actual.reshape((actual.shape[0], 1))# Python Program illustrating
# numpy.reshape() method
import numpy as geek
# array = geek.arrange(8)
# The 'numpy' module has no attribute 'arrange'
array1 = geek.arange(8)
print("Original array : \n", array1)
# shape array with 2 rows and 4 columns
array2 = geek.arange(8).reshape(-1, 1)
print("\narray reshaped with 2 rows and 4 columns : \n",
array2)
# shape array with 4 rows and 2 columns
array3 = geek.arange(8).reshape(4, 2)
print("\narray reshaped with 2 rows and 4 columns : \n",
array3)
# Constructs 3D array
array4 = geek.arange(8).reshape(2, 2, 2)
print("\nOriginal array reshaped to 3D : \n",
array4)z.reshape(-1,1)
array([[ 1],
[ 2],
[ 3],
[ 4],
[ 5],
[ 6],
[ 7],
[ 8],
[ 9],
[10],
[11],
[12]])