How to Set Axis for Rows and Columns in NumPy ?
Last Updated :
07 Nov, 2022
In this article, we are going to see how to set the axis for rows and columns in NumPy.
Functions Used
- np.array(object): to create a NumPy array, the object is the parameter that contains the array
- np.reshape(rows, columns): to reshape the array into the specified number of rows and columns. Here in the below examples, we have given -1 in place of rows to let numpy figure it out if there are 3 columns in each row.
- np.sum(axis): to calculate the sum or addition of the elements. Here we have mentioned the axis to do the operation array-wise, row-wise, or column-wise as per requirement.
Example 1: Set axis for array-wise calculation
In this example, we will reshape the NumPy array into rows having 3 columns each i.e nparray.reshape(-1, 3) to make it two-dimensional. Then we will perform the sum operation of the array elements array-wise that is in normal order starting from the first to last element of the NumPy array. We specifically set the axis= None to trigger the normal array-wise operation.
Code:
Python3
import numpy as np
nparray = np.array([[ 1 , 2 , 3 ], [ 11 , 22 , 33 ],
[ 4 , 5 , 6 ], [ 8 , 9 , 10 ],
[ 20 , 30 , 40 ]])
nparray = nparray.reshape( - 1 , 3 )
print (nparray)
output = nparray. sum (axis = None )
print ( "\n\nSum array-wise: " , output)
|
Output :
[[ 1 2 3]
[11 22 33]
[ 4 5 6]
[ 8 9 10]
[20 30 40]]
Sum array-wise: 204
Example 2: Set axis for column-wise calculation
In this example, we will reshape the numpy array into rows having 3 columns each. Then perform the sum operation of the array elements using the sum() function column-wise. We specifically set the axis= 0 to trigger the normal array-wise operation.
Code:
Python3
import numpy as np
nparray = np.array([[ 1 , 2 , 3 ], [ 11 , 22 , 33 ],
[ 4 , 5 , 6 ], [ 8 , 9 , 10 ],
[ 20 , 30 , 40 ]])
nparray = nparray.reshape( - 1 , 3 )
print (nparray)
output = nparray. sum (axis = 0 )
print ( "\n\nSum column-wise: " , output)
|
Output :
[[ 1 2 3]
[11 22 33]
[ 4 5 6]
[ 8 9 10]
[20 30 40]]
Sum column-wise: [44 68 92]
Example 3: Set axis for row-wise calculation
We will specifically set the axis = 1 to trigger the normal row-wise calculation.
Code:
Python3
import numpy as np
nparray = np.array([[ 1 , 2 , 3 ], [ 11 , 22 , 33 ],
[ 4 , 5 , 6 ], [ 8 , 9 , 10 ],
[ 20 , 30 , 40 ]])
nparray = nparray.reshape( - 1 , 3 )
print (nparray)
output = nparray. sum (axis = 1 )
print ( "\n\nSum row-wise: " , output)
|
Output :
[[ 1 2 3]
[11 22 33]
[ 4 5 6]
[ 8 9 10]
[20 30 40]]
Sum row-wise: [ 6 66 15 27 90]
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