Delete rows and columns of NumPy ndarray
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.
# 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.
# 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.
# 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)
# 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)
# 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:
