In this article we will discuss how to sort a 2D Numpy array by single or multiple rows or columns.
Sorting 2D Numpy Array by a column
First of all import numpy module i.e.
import numpy as np
Now suppose we have a 2D Numpy array i.e.
# Create a 2D Numpy array list of list arr2D = np.array([[11, 12, 13, 22], [21, 7, 23, 14], [31, 10, 33, 7]]) print('2D Numpy Array') print(arr2D)
Output:
2D Numpy Array [[11 12 13 22] [21 7 23 14] [31 10 33 7]]
Now suppose we want to sort this 2D numpy array by 2nd column like this,
[[21 7 23 14] [31 10 33 7] [11 12 13 22]]
For this we need to change positioning of all rows in 2D numpy array based on sorted values of 2nd column i.e. column at index 1. Let’s see how to do that,
Sorting 2D Numpy Array by column at index 1
columnIndex = 1 # Sort 2D numpy array by 2nd Column sortedArr = arr2D[arr2D[:,columnIndex].argsort()] print('Sorted 2D Numpy Array') print(sortedArr)
Output:
Sorted 2D Numpy Array [[21 7 23 14] [31 10 33 7] [11 12 13 22]]
It sorted the 2D Numpy array by 2nd column i.e. column at index 1.
How did it worked ?
Let’s break down the above expression part by part and understand how ot worked.
Select the column at index 1 from 2D numpy array i.e.
arr2D[:,columnIndex]
It returns the values at 2nd column i.e. column at index position 1 i.e.
[12 7 10]
Now get the array of indices that sort this column i.e.
arr2D[:,columnIndex].argsort()
It returns the index positions that can sort the above column i.e.
[1 2 0]
It means for sorting column at index position 1 use following order of rows : [1 2 0]
So, to change the positioning of rows based on values returned by argsort(). Pass that to [] operator of 2D numpy array i.e.
arr2D[arr2D[:,columnIndex].argsort()]
It will change the row order and make the 2D numpy array sorted by 2nd column i.e. by column at index position 1.
Let’s see some other examples,
Sorting 2D Numpy Array by column at index 0
# Sort 2D numpy array by first column sortedArr = arr2D[arr2D[:,0].argsort()] print('Sorted 2D Numpy Array') print(sortedArr)
Output:
Sorted 2D Numpy Array [[11 12 13 22] [21 7 23 14] [31 10 33 7]]
Sorting 2D Numpy Array by last column
# Sort 2D numpy array by last column sortedArr = arr2D[arr2D[:, 1].argsort()] print('Sorted 2D Numpy Array') print(sortedArr)
Output:
[[31 10 33 7] [21 7 23 14] [11 12 13 22]]
Sort a 2D Numpy Array by row
On the similar logic we can sort a 2D Numpy array by a single row i.e. shuffle the columns of 2D numpy array to make the given row sorted.
Let’s understand by examples,
Suppose we have a 2D Numpy array i.e.
# Create a 2D Numpy array list of list arr2D = np.array([[11, 12, 13, 22], [21, 7, 23, 14], [31, 10, 33, 7]]) print('2D Numpy Array') print(arr2D)
Output:
2D Numpy Array [[11 12 13 22] [21 7 23 14] [31 10 33 7]]
Sorting 2D Numpy Array by row at index position 1
Let’s sort the above created 2D Numpy array by 2nd row i.e. row at index position 1 i.e.
# Sort 2D numpy array by 2nd row sortedArr = arr2D [ :, arr2D[1].argsort()] print('Sorted 2D Numpy Array') print(sortedArr)
Output:
Sorted 2D Numpy Array [[12 22 11 13] [ 7 14 21 23] [10 7 31 33]]
It changed the positions of all columns in 2D numpy array to make row at index position 1 sorted. So, basically we sorted the 2D Numpy array by row at index 1.
How it worked ?
Its logic was similar to above i.e. Select row at given index position using [] operator and then get sorted indices of this row using argsort().
<New positioning of columns> = arr[rowindex].argsort()
Then change the positioning of columns to make this 2d array sorted by row.
array[:, <New positioning of columns>]
Some other examples,
Sorting 2D Numpy Array by First Row
# Sort 2D numpy array by 2nd row sortedArr = arr2D [ :, arr2D[0].argsort()] print('Sorted 2D Numpy Array') print(sortedArr)
Output:
Sorted 2D Numpy Array [[11 12 13 22] [21 7 23 14] [31 10 33 7]]
Sorting 2D Numpy Array by Last row
# Sort 2D numpy array by last row sortedArr = arr2D[:, arr2D[1].argsort()] print('Sorted 2D Numpy Array') print(sortedArr)
Output:
Sorted 2D Numpy Array [[22 12 11 13] [14 7 21 23] [ 7 10 31 33]]
Complete example is as follows:
import numpy as np def main(): # Create a 2D Numpy array list of list arr2D = np.array([[11, 12, 13, 22], [21, 7, 23, 14], [31, 10, 33, 7]]) print('2D Numpy Array') print(arr2D) print('****** Sort 2D Numpy array by column ******') print('*** Sort 2D Numpy array by 2nd column i.e. column at index 1 ***') columnIndex = 1 # Sort 2D numpy array by 2nd Column sortedArr = arr2D[arr2D[:,columnIndex].argsort()] print('Sorted 2D Numpy Array') print(sortedArr) print('*** Sort 2D Numpy array by 1st column i.e. column at index 0 ***') # Sort 2D numpy array by first column sortedArr = arr2D[arr2D[:,0].argsort()] print('Sorted 2D Numpy Array') print(sortedArr) print('*** Sort 2D Numpy array by last column ***') # Sort 2D numpy array by last column sortedArr = arr2D[arr2D[:, 1].argsort()] print('Sorted 2D Numpy Array') print(sortedArr) print('****** Sort 2D Numpy array by row ******') # Create a 2D Numpy array list of list arr2D = np.array([[11, 12, 13, 22], [21, 7, 23, 14], [31, 10, 33, 7]]) print('2D Numpy Array') print(arr2D) print('*** Sort 2D Numpy array by 2nd Row i.e. row at index position 1 ***') # Sort 2D numpy array by 2nd row sortedArr = arr2D [ :, arr2D[1].argsort()] print('Sorted 2D Numpy Array') print(sortedArr) print('*** Sort 2D Numpy array by First Row***') # Sort 2D numpy array by first row sortedArr = arr2D [ :, arr2D[0].argsort()] print('Sorted 2D Numpy Array') print(sortedArr) print('*** Sort 2D Numpy array by Last Row***') # Sort 2D numpy array by last row sortedArr = arr2D[:, arr2D[1].argsort()] print('Sorted 2D Numpy Array') print(sortedArr) if __name__ == '__main__': main()
Output:
2D Numpy Array [[11 12 13 22] [21 7 23 14] [31 10 33 7]] ****** Sort 2D Numpy array by column ****** *** Sort 2D Numpy array by 2nd column i.e. column at index 1 *** Sorted 2D Numpy Array [[21 7 23 14] [31 10 33 7] [11 12 13 22]] *** Sort 2D Numpy array by 1st column i.e. column at index 0 *** Sorted 2D Numpy Array [[11 12 13 22] [21 7 23 14] [31 10 33 7]] *** Sort 2D Numpy array by last column *** Sorted 2D Numpy Array [[31 10 33 7] [21 7 23 14] [11 12 13 22]] ****** Sort 2D Numpy array by row ****** 2D Numpy Array [[11 12 13 22] [21 7 23 14] [31 10 33 7]] *** Sort 2D Numpy array by 2nd Row i.e. row at index position 1 *** Sorted 2D Numpy Array [[12 22 11 13] [ 7 14 21 23] [10 7 31 33]] *** Sort 2D Numpy array by First Row*** Sorted 2D Numpy Array [[11 12 13 22] [21 7 23 14] [31 10 33 7]] *** Sort 2D Numpy array by Last Row*** Sorted 2D Numpy Array [[22 12 11 13] [14 7 21 23] [ 7 10 31 33]]
Pandas Tutorials Learn Data Analysis with Python

Pandas Tutorial Part #1  Introduction to Data Analysis with Python

Pandas Tutorial Part #2  Basics of Pandas Series

Pandas Tutorial Part #3  Get & Set Series values

Pandas Tutorial Part #4  Attributes & methods of Pandas Series

Pandas Tutorial Part #5  Add or Remove Pandas Series elements

Pandas Tutorial Part #6  Introduction to DataFrame

Pandas Tutorial Part #7  DataFrame.loc[]  Select Rows / Columns by Indexing

Pandas Tutorial Part #8  DataFrame.iloc[]  Select Rows / Columns by Label Names

Pandas Tutorial Part #9  Filter DataFrame Rows

Pandas Tutorial Part #10  Add/Remove DataFrame Rows & Columns

Pandas Tutorial Part #11  DataFrame attributes & methods

Pandas Tutorial Part #12  Handling Missing Data or NaN values

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Pandas Tutorial Part #15  Merging or Concatenating DataFrames

Pandas Tutorial Part #16  DataFrame GroupBy explained with examples
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