If your are looking for the answer “how to rename columns in Pandas DataFrame”. So you are at the right place. This article covers the answer to your question. In this article we are going to cover different ways or methods to answer the question “rename column in pandas”. Let’s see how to rename column from in Pandas.
It’s normal practice to rename dataframe columns, especially when we want to share some insights with other people and teams. This suggests that we might want to give column names additional significance so that readers can relate them to particular situations more readily.
Lets discuses best methods to rename column in pandas:
Rename columns in Pandas DataFrame
Method 1: By using rename() method of the DataFrame
The rename() function is used to alter axes labels. Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Extra labels listed don’t throw an error.
# Import pandas package
import pandas as pd
# Define a dictionary containing students information
data = {'Name': ['Rahul', 'Pooja',
'Ketan', 'Mili'],
'RollNo': [101, 102, 103, 104],
'Subject': ['Hindi', 'English',
'Math', 'Science'],
'Marks': [79, 85, 89, 95]}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=['Name', 'RollNo',
'Subject', 'Marks'])
print("Given Dataframe :\n", df)
# Rename a column name 'Marks' to Percentage
df.rename (columns = {'Marks':'Percentage'}, inplace=True )
# You can change any number of columns like :
# df.rename (columns = {'Marks':'Percentage' , 'Subject':'Stream'}, inplace=True )
# After rename
print("After Rename a column Dataframe is :\n", df)
Output:
After Rename a column Dataframe is :
Name RollNo Subject Percentage
0 Rahul 101 Hindi 79
1 Pooja 102 English 85
2 Ketan 103 Math 89
3 Mili 104 Science 95
Method 2: Rename All Columns
The columns can also be changed by directly changing the names of the columns by setting a list containing the new names to the columns attribute of the Dataframe object. The drawback of this approach is that, even if we only wish to rename part of the columns, we must offer new names for all of them.
# Import pandas package
import pandas as pd
# Define a dictionary containing students information
data = {'Name': ['Rahul', 'Pooja',
'Ketan', 'Mili'],
'RollNo': [101, 102, 103, 104],
'Subject': ['Hindi', 'English',
'Math', 'Science'],
'Marks': [79, 85, 89, 95]}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=['Name', 'RollNo',
'Subject', 'Marks'])
print("Given Dataframe :\n", df)
# Rename all columns
df.columns = ['Col1', 'Col2', 'Col3', 'Col4']
# After rename
print("After Rename all columns Dataframe is :\n", df)
Output:
After Rename all columns Dataframe is :
Col1 Col2 Col3 Col4
0 Rahul 101 Hindi 79
1 Pooja 102 English 85
2 Ketan 103 Math 89
3 Mili 104 Science 95
Method 3: Rename All Columns by using DataFrame set_axis() function
The set_axis() function is used to assign desired index to given axis. Indexes for column or row labels can be changed by assigning a list-like or Index.
# Import pandas package
import pandas as pd
# Define a dictionary containing students information
data = {'Name': ['Rahul', 'Pooja',
'Ketan', 'Mili'],
'RollNo': [101, 102, 103, 104],
'Subject': ['Hindi', 'English',
'Math', 'Science'],
'Marks': [79, 85, 89, 95]}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=['Name', 'RollNo',
'Subject', 'Marks'])
print("Given Dataframe :\n", df)
# Rename all columns
df.set_axis(['A', 'B', 'C', 'D'], axis='columns', inplace=True)
# After rename
print("After Rename all columns Dataframe is :\n", df)
Output:
After Rename all columns Dataframe is :
A B C D
0 Rahul 101 Hindi 79
1 Pooja 102 English 85
2 Ketan 103 Math 89
3 Mili 104 Science 95
Method 4: Replace specific texts of column names by using Dataframe.columns.str.replace function
You can also replace a specific tests of column names with the help of Dataframe.columns.str.replace function. Let’s check how this works?
# Import pandas package
import pandas as pd
# Define a dictionary containing students information
data = {'Name': ['Rahul', 'Pooja',
'Ketan', 'Mili'],
'RollNo': [101, 102, 103, 104],
'Subject': ['Hindi', 'English',
'Math', 'Science'],
'Marks': [79, 85, 89, 95]}
# Convert the dictionary into DataFrame
df = pd.DataFrame(data, columns=['Name', 'RollNo',
'Subject', 'Marks'])
print("Given Dataframe :\n", df)
# Rename Specific text of column names
df.columns = df.columns.str.replace('Marks', 'Percentage')
df.columns = df.columns.str.replace('Subject', 'Stream')
# After rename
print("After Rename specific columns Dataframe is :\n", df)
Output:
After Rename specific columns Dataframe is :
Name RollNo Stream Percentage
0 Rahul 101 Hindi 79
1 Pooja 102 English 85
2 Ketan 103 Math 89
3 Mili 104 Science 95
Final Thoughts about ‘rename column in pandas’
This article examined several approaches of renaming columns in a Pandas dataframe. The main takeaways are as follows:
- Use the pandas dataframe
rename()function to change the name of one or more columns. By passing{"OldName":"NewName"}to thecolumnsparameter. You can also pass a function to thecolumnsparameter to dynamically change the column names. - You can set the column names of the dataframe to new column names using the pandas dataframe
setaxis()function. Explicitly specifyaxis=1oraxis='columns'to indicate that you’re setting the columns’ axis. - You can change the column names of a dataframe by changing the
.columnsattribute of the dataframe. - You can also replace a specific tests of column names with the help of Dataframe.columns.str.replace function.
