In this article, we will discuss how to delete the specified rows and columns in an n-dimensional array. We are going to delete the rows and columns using numpy.delete() method.
Syntax: numpy.delete(array_name, obj, axis=None)
Let’s discuss with the help of some examples:
Example 1:
Program to create a 2-dimensional array (3 rows and 4 columns) with NumPy and delete the specified row.
Python3
# importing numpy module import numpy as np # create an array with integers # with 3 rows and 4 columns a = np.array([[ 1 , 2 , 3 , 4 ], [ 5 , 6 , 7 , 8 ], [ 9 , 10 , 11 , 12 ]]) print (a) # delete 0 th row data = np.delete(a, 0 , 0 ) print ( "data after 0 th row deleted :" , data) # delete 1 st row data = np.delete(a, 1 , 0 ) print ( "data after 1 st row deleted :" , data) # delete 2 nd row data = np.delete(a, 2 , 0 ) print ( "data after 2 nd row deleted :" , data) |
Output:
Example 2:
Program to create a 2-dimensional array (6 rows and 2 columns) with NumPy and delete the specified columns.
Python3
# importing numpy module import numpy as np # create an array with integers with # 6 rows and 2 columns a = np.array([[ 1 , 2 ], [ 5 , 6 ], [ 9 , 10 , ], [ 78 , 90 ], [ 4 , 89 ], [ 56 , 43 ]]) print (a) # delete 0 th column data = np.delete(a, 0 , 1 ) print ( "data after 0 th column deleted :" , data) # delete 1 st column data = np.delete(a, 1 , 1 ) print ( "data after 1 st column deleted :" , data) |
Output:
Example 3:
Delete both 1 row and 1 column.
Python3
# importing numpy module import numpy as np # create an array with integers # with 3 rows and 3 columns a = np.array([[ 67 , 65 , 45 ], [ 45 , 67 , 43 ], [ 3 , 4 , 5 ]]) print ( "Original\n" , a) # delete 1 st row data = np.delete(a, 0 , 0 ) print ( "data after 1 st row deleted :\n" , data) # delete 1 st column data = np.delete(a, 0 , 1 ) print ( "data after 1 st column deleted :\n" , data) |
Output:
Example 4:
We can delete n number of rows at a time by passing row numbers as a list in the obj argument.
Syntax: numpy.delete(array_name, [row1,row2,.row n], axis=None)
Python3
# importing numpy module import numpy as np # create an array with integers # with 3 rows and 3 columns a = np.array([[ 67 , 65 , 45 ], [ 45 , 67 , 43 ], [ 3 , 4 , 5 ]]) print ( "Original\n" , a) # delete 1 st row and 2 nd # row at a time data = np.delete(a, [ 0 , 1 ], 0 ) print ( "data after 1 st and 2 ns row deleted :\n" , data) |
Output:
Example 5:
We can delete n number of columns at a time by passing column numbers as a list in the obj argument.
Syntax: numpy.delete(array_name, [column number1,column number2,.column number n], axis=None)
Python3
# importing numpy module import numpy as np # create an array with integers # with 3 rows and 3 columns a = np.array([[ 67 , 65 , 45 ], [ 45 , 67 , 43 ], [ 3 , 4 , 5 ]]) print ( "Original\n" , a) # delete 1 st column and 3 rd # column at a time data = np.delete(a, [ 0 , 2 ], 1 ) print ( "data after 1 st and 3 rd column deleted :\n" , data) |
Output: