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:
