How to Sort data by Column in a CSV File in Python ?

In this article, we will discuss how to sort CSV by column(s) using Python.

Method 1: Using sort_values()

We can take the header name as per our requirement, the axis can be either 0 or 1, where 0 means ‘rows’ and ‘1’ means ‘column’. Ascending can be either True/False and if True, it gets arranged in ascending order, if False, it gets arranged in descending order.

Syntax: DataFrame.sort_values(by, axis=0, ascending=True, inplace=False, kind=’quicksort’, na_position=’last’)

CSV File Used:

Below are various which depict various ways to sort a CSV dataset.

Example 1: Sorting the dataset in descending order on the basis of salary

Python3

# importing pandas package
import pandas as pandasForSortingCSV

# assign dataset
csvData = pandasForSortingCSV.read_csv("sample.csv")

# displaying unsorted data frame
print("\nBefore sorting:")
print(csvData)

# sort data frame
csvData.sort_values(["Salary"],
                    axis=0,
                    ascending=[False],
                    inplace=True)

# displaying sorted data frame
print("\nAfter sorting:")
print(csvData)

Output:

Example 2: Sorting the dataset in default (ascending) order on the basis of salary.

Python3

# importing pandas package
import pandas as pandasForSortingCSV

# assign dataset
csvData = pandasForSortingCSV.read_csv("sample.csv")

# displaying unsorted data frame
print("\nBefore sorting:")
print(csvData)

# sort data frame
csvData.sort_values(csvData.columns[4],
                    axis=0,
                    inplace=True)

# displaying sorted data frame
print("\nAfter sorting:")
print(csvData)

Output:

Example 3: Sorting the dataset on the basis of Name, Age and, Height in ascending order.

Python3

# importing pandas package
import pandas as pandasForSortingCSV

# assign dataset
csvData = pandasForSortingCSV.read_csv("sample.csv")

# displaying unsorted data frame
print("\nBefore sorting:")
print(csvData)

# sort data frame
csvData.sort_values(["Name", "Age", "Height"],
                    axis=0,
                    ascending=[True, True, True],
                    inplace=True)

# displaying sorted data frame
print("\nAfter sorting:")
print(csvData)

Output:

Example 4: Sorting the dataset on the basis of Salary in descending order and Age in ascending order.

Python3

# importing pandas package
import pandas as pandasForSortingCSV

# assign dataset
csvData = pandasForSortingCSV.read_csv("sample.csv")

# displaying unsorted data frame
print("\nBefore sorting:")
print(csvData)

# sort data frame
csvData.sort_values([csvData.columns[4], csvData.columns[2]],
                    axis=0,
                    ascending=[False, True],
                    inplace=True)

# displaying sorted data frame
print("\nAfter sorting:")
print(csvData)

Output:

Method 2: Using sorted()

Another way of sorting CSV files is by using the sorted() method on the CSV module object. However, it can only sort CSV files based on only one column.

Syntax: 

sorted(iterable, key, reverse)

Below are various which depict various ways to sort a CSV dataset.

Example 1: Sorting the dataset in ascending order on the basis of Age.

Python3

# import modules
import csv ,operator

# load csv file
data = csv.reader(open('sample.csv'),delimiter=',')

# sort data on the basis of age
data = sorted(data, key=operator.itemgetter(2))

# displaying sorted data
print('After sorting:')
display(data)

Output:

Example 2: Sorting the dataset in descending order on the basis of Age.

Python3

# import modules
import csv ,operator

# load csv file
data = csv.reader(open('sample.csv'),delimiter=',')

# sort data on the basis of age
data = sorted(data, key=operator.itemgetter(2), reverse=True)

# displaying sorted data
print('After sorting:')
display(data)

Output: