How to Sort Pandas DataFrame with Examples
Sort Pandas DataFrame with Example’s
It’s very much easier to Sort Pandas DataFrame using the sort_values
function from DataFrame
class. In this tutorial, you are going to learn how to sort Pandas DataFrame with examples.
Let’s start with the sample DataFrame. Now assume you have the following data for sorting:
Model  Battery  Price 
Google Pixel 3  2915  37300 
Oneplus 7  4085  53999 
Asus ROG  6000  45000 
Oppo Reno  4065  39990 
Redmi K20  4000  27244 
Create a DataFrame using Python Program:
from pandas import DataFrame Phones = {'Model': ['Google Pixel 3','Oneplus 7','Asus ROG','Oppo Reno','Redmi K20'], 'Battery': [2915,4085,6000,4065,4000], 'Price': [37300,53999,45000,39990,27244]} df = DataFrame(Phones, columns= ['Model', 'Battery','Price']) print (df)
The output for the above program will be:
Sorting Pandas DataFrame in Ascending Order
The sort_values()
function sorts data in ascending order by default. In this example, we going to sort the Pandas DataFrame in ascending order by using Model
.
df.sort_values(by=['Model'], inplace=True)
The complete code to sort DataFrame in ascending order will look like:
from pandas import DataFrame Phones = {'Model': ['Google Pixel 3','Oneplus 7','Asus ROG','Oppo Reno','Redmi K20'], 'Battery': [2915,4085,6000,4065,4000], 'Price': [37300,53999,45000,39990,27244]} df = DataFrame(Phones, columns= ['Model', 'Battery','Price']) # sort DataFrame by Model df.sort_values(by=['Model'], inplace=True) print (df)
The output of the above code will be:
As you can see how the data is sorted in ascending order. The above output Asus ROG
is in the first place while in Google Pixel 3
second place.
Sort Pandas DataFrame in Descending Order
In this example, we going to sort the Pandas DataFrame in descending order by using Model
name. To sort in descending order you should add ascending parameter with value false as given below:
df.sort_values(by=['Model'], inplace=True, ascending=False)
The complete code to sort DataFrame in ascending order will look like:
from pandas import DataFrame Phones = {'Model': ['Google Pixel 3','Oneplus 7','Asus ROG','Oppo Reno','Redmi K20'], 'Battery': [2915,4085,6000,4065,4000], 'Price': [37300,53999,45000,39990,27244]} df = DataFrame(Phones, columns= ['Model', 'Battery','Price']) # sort DataFrame by Model df.sort_values(by=['Model'], inplace=True, ascending=False) print (df)
The output of the above code will be:
As you can see how the data is sorted in descending order. The above output Redmi K20
is in the first place while Oppo Reno
in second place.
Sorting Pandas DataFrame Based on Multiple Columns
In this example, we going to sort the Pandas DataFrame based on multiple columns by using Battery
and Price
. To sort DataFrame based on multiple columns you should set values as given below:
df.sort_values(by=['Battery','Price'], inplace=True)
The complete code to sort DataFrame in ascending order will look like:
from pandas import DataFrame Phones = {'Model': ['Google Pixel 3','Oneplus 7','Asus ROG','Oppo Reno','Redmi K20'], 'Battery': [2915,4085,6000,4065,4000], 'Price': [37300,53999,45000,39990,27244]} df = DataFrame(Phones, columns= ['Model', 'Battery','Price']) # sort DataFrame by Model df.sort_values(by=['Battery','Price'], inplace=True) print (df)
The output of the above code will be:
As you can see how the data is sorted based on Battery and Price columns.
Conclusion
You have successfully learned How to Sort Pandas DataFrame with Examples. If you have any queries regarding this tutorial please don’t forget to comment below.
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