How to Sort Dataframe in Python

We can use the sort_values() function in Pandas to sort a Pandas DataFrame.

In this article, we will learn to sort a dataframe in many ways.

We are performing the sorting in the below dummy data.

1. Sort Pandas DataFrame in an ascending order

# sort - ascending order
import pandas as pd 
import numpy as np 

di = {'Name': ['abi', 'hari', 'taylor', 'dev'],
		'Age': [21, 20, 21, 20],
		'Place': ['yale', 'london', 'delhi', 'mumbai'],
		}

df = pd.DataFrame(di, columns = ['Name', 'Age', 'Place'])

# sort Name in ascending order
df.sort_values(by = ['Name'], inplace = True)

print(df)

Output:

     Name  Age   Place
0     abi   21    yale
3     dev   20  mumbai
1    hari   20  london
2  taylor   21   delhi

2. Sort Pandas DataFrame in an descending order

# sort - descending order
import pandas as pd 
import numpy as np 

di = {'Name': ['abi', 'hari', 'taylor', 'dev'],
		'Age': [21, 20, 21, 20],
		'Place': ['yale', 'london', 'delhi', 'mumbai'],
		}

df = pd.DataFrame(di, columns = ['Name', 'Age', 'Place'])

# sort Name in descending order
df.sort_values(by = ['Name'], inplace = True, ascending = False)

print(df)

Output:

     Name  Age   Place
2  taylor   21   delhi
1    hari   20  london
3     dev   20  mumbai
0     abi   21    yale

3. Sort by multiple columns – Case 1

# sort - multiple columns
import pandas as pd 
import numpy as np 

di = {'Name': ['abi', 'hari', 'taylor', 'dev'],
		'Age': [21, 20, 21, 20],
		'Place': ['yale', 'london', 'delhi', 'mumbai'],
		}

df = pd.DataFrame(di, columns = ['Name', 'Age', 'Place'])

# sort by multiple columns: Place and Age
df.sort_values(by = ['Place', 'Age'], inplace = True)

print(df)

Output:

     Name  Age   Place
2  taylor   21   delhi
1    hari   20  london
3     dev   20  mumbai
0     abi   21    yale

Note that priority will be more for Place than Age.