Prerequisites: Pandas
A column of a data frame can be changed using the position it is in known as its index. Just by the use of index a column can be renamed. This article discusses all such possible methods.
Approach:
- Import required python library.
- Create data
- Provide index of the column to be renamed as argument to rename() function.
Pandas rename() method is used to rename any index, column or row.
Syntax: rename(mapper=None, index=None, columns=None, axis=None, copy=True, inplace=False, level=None)
Parameters:
- mapper, index and columns: Dictionary value, key refers to the old name and value refers to new name. Only one of these parameters can be used at once.
- axis: int or string value, 0/’row’ for Rows and 1/’columns’ for Columns
- copy: Copies underlying data if True.
- inplace: Makes changes in original Data Frame if True.
- level: Used to specify level in case data frame is having multiple level index.
Return Type: Data frame with new names
Given below are various implementation to achieve our required functionality:
Example 1: Switching both column names with each other using column index.
Python3
import pandas as pd # Sample DataFramedf = pd.DataFrame({'a': [1, 2], 'b': [3, 4]}) # Changing columns name with index numberdf.columns.values[0] = "b"df.columns.values[1] = "a" # Displaydisplay(df) |
Output:
Example 2: Using another method to rename the column with index.
Python3
import pandas as pd # Sample DataFramedf = pd.DataFrame({'a': [1, 2], 'b': [3, 4]}) # Changing columns name with index numbersu = df.rename(columns={df.columns[1]: 'new'}) # Displaydisplay(su) |
Output:
Example 3: Renaming two/more columns in a single command using an index number.
Python3
import pandas as pd # Sample DataFramedf = pd.DataFrame({'a': [1, 2], 'b': [3, 4], 'c': [7, 8]}) # Changing columns name with index numbermapping = {df.columns[0]: 'new0', df.columns[1]: 'new1'}su = df.rename(columns=mapping) # Displaydisplay(su) |
Output:
Example 4: Renaming column name with an index number of the CSV file.
File in use: Data1.csv
Link: Click here
Python3
import pandas as pd # reading a csv filedf1 = pd.read_csv("data1.csv") # change 2nd column name with index numberdf1.columns.values[2] = "city" # Display DataFramedisplay(df1) |
Output:
