In this short guide, you’ll see how to change the order of columns in Pandas DataFrame.
An example is included for illustration purposes.
Steps to Change the Order of Columns in Pandas DataFrame
Step 1: Prepare the Data for the DataFrame
To begin, prepare the data for your DataFrame.
For example, the following dataset was prepared:
Name | Age | Profession | Country |
Jack | 22 | Accountant | Italy |
Maria | 31 | Engineer | Spain |
Emma | 43 | Doctor | Brazil |
Rick | 25 | Lawyer | Mexico |
Sophia | 52 | Banker | France |
Step 2: Create the DataFrame
Now create the actual DataFrame based on the above dataset:
import pandas as pd data = {'Name': ['Jack','Maria','Emma','Rick','Sophia'], 'Age': [22,31,43,25,52], 'Profession': ['Accountant','Engineer','Doctor','Lawyer','Banker'], 'Country': ['Italy','Spain','Brazil','Mexico','France'] } df = pd.DataFrame(data, columns= ['Name','Age','Profession','Country']) print (df)
Run the code in Python, and you’ll get the following DataFrame:
Name Age Profession Country
0 Jack 22 Accountant Italy
1 Maria 31 Engineer Spain
2 Emma 43 Doctor Brazil
3 Rick 25 Lawyer Mexico
4 Sophia 52 Banker France
As you can see, the order of the columns is:
Name, Age, Profession, Country
Step 3: Change the Order of the Columns in the DataFrame
Let’s say that you want to change the order of the columns to:
Name, Country, Age, Profession
In that case, you’ll need to add the following syntax to the code:
df = df[['Name','Country','Age','Profession']]
So this is the complete code to reorder your columns in the DataFrame:
import pandas as pd data = {'Name': ['Jack','Maria','Emma','Rick','Sophia'], 'Age': [22,31,43,25,52], 'Profession': ['Accountant','Engineer','Doctor','Lawyer','Banker'], 'Country': ['Italy','Spain','Brazil','Mexico','France'] } df = pd.DataFrame(data, columns= ['Name','Age','Profession','Country']) df = df[['Name','Country','Age','Profession']] print (df)
Once you run the code, you’ll get the DataFrame below with the ordered columns:
Name Country Age Profession
0 Jack Italy 22 Accountant
1 Maria Spain 31 Engineer
2 Emma Brazil 43 Doctor
3 Rick Mexico 25 Lawyer
4 Sophia France 52 Banker
You may also wish to check the following page for additional Python tutorials.