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Delete rows and columns of NumPy ndarray

  • Last Updated : 21 Apr, 2021
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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:

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