To rename index values of pandas DataFrame use rename() method or index attribute. In this article, I will explain multiple ways of how to rename a single index value and multiple index values of the pandas DataFrame using functions like DataFrame.rename(), DataFrame.index property with examples. When you update multiple row index values, you would need to create a Dict with key-value pair and use it with rename() function.
Related: pandas Rename Column of DataFrame & pandas rename Index Name
1. Quick Examples of Rename Index Values of DataFrame
If you are in a hurry, below are some quick examples of how to rename index values of DataFrame.
# Below are quick example
# Assign Indexs to DataFrame.index
df.index = ['index_1', 'index_2', 'index_3', 'index_4']
# Using DataFrame.rename() to rename index values
df2 = df.rename(index={'r3': 'Index_3'})
# Rename multiple index value
df2 = df.rename(index={'r1':'Index_1','r2':'Index_2'})
# Changing the DataFrame inplace
df.rename(index={'r3': 'Index_3','r4': 'Index_4'}, inplace=True)
# Append a value to DataFrame index row Using lambda function
df2 = df.rename(index=lambda Index: Index+'_Index')
Now, let’s create a DataFrame with a few rows and columns, execute these examples and validate results. Our DataFrame contains column names Courses, Fee, Duration, and Discount.
import pandas as pd
technologies = {
'Courses':["Spark","PySpark","Python","pandas"],
'Fee' :[20000,25000,22000,30000],
'Duration':['30days','40days','35days','50days'],
'Discount':[1000,2300,1200,2000]
}
index_labels=['r1','r2','r3','r4']
df = pd.DataFrame(technologies,index=index_labels)
print(df)
Yields below output.
Courses Fee Duration Discount
r1 Spark 20000 30days 1000
r2 PySpark 25000 40days 2300
r3 Python 22000 35days 1200
r4 pandas 30000 50days 2000
2. Changing the Row Index Using DataFrame.index() Attribute
In order to rename/change the values for all row index, create a list with new indexes and assign it to DataFrame.index attribute. Note that If your DataFrame is small and for a huge DataFrame this is not an idle solution.
# Change the row indexes
df.index = ['index_1', 'index_2', 'index_3', 'index_4']
print(df)
Yields below output.
Courses Fee Duration Discount
index_1 Spark 20000 30days 1000
index_2 PySpark 25000 40days 2300
index_3 Python 22000 35days 1200
index_4 pandas 30000 50days 2000
3. Rename Specific Index Values
pandas.DataFrame.rename() accepts a dictionary as a param for index values you wanted to rename. So you just pass a dict with key-value pair; the key is an existing index you would like to rename and the value would be your preferred index value. The below examples changes the index to'r3' from 'Index_3'.
# Using DataFrame.rename() to rename index values
df = pd.DataFrame(technologies,index=index_labels)
df2 = df.rename(index={'r3': 'Index_3'})
print(df2)
Yields below output.
Courses Fee Duration Discount
r1 Spark 20000 30days 1000
r2 PySpark 25000 40days 2300
Index_3 Python 22000 35days 1200
r4 pandas 30000 50days 2000
4. Rename Multiple Row Indexes
You can also use the same approach to rename multiple index values or all indexes of pandas DataFrame.
# Rename multiple index value
df = pd.DataFrame(technologies,index=index_labels)
df2 = df.rename(index={'r1':'Index_1','r2':'Index_2'})
print(df2)
Yields below output.
Courses Fee Duration Discount
Index_1 Spark 20000 30days 1000
Index_2 PySpark 25000 40days 2300
r3 Python 22000 35days 1200
r4 pandas 30000 50days 2000
5. Change the DataFrame Inplace
DataFrame.rename() takes parameter inplace=True to change the DataFrame inplace. In this case, no new DataFrame is returned, and the return value is None.
# Changing the DataFrame inplace
df = pd.DataFrame(technologies,index=index_labels)
df.rename(index={'r3': 'Index_3','r4': 'Index_4'}, inplace=True)
print(df)
Yields below output.
Courses Fee Duration Discount
r1 Spark 20000 30days 1000
r2 PySpark 25000 40days 2300
Index_3 Python 22000 35days 1200
Index_4 pandas 30000 50days 2000
6. Append a Value to DataFrame Index
Another approach would be using the lambda function. The below example add’s ‘_Index’ to all index values. This approach helps you to update/rename all indexes
# Append a value to DataFrame index row Using lambda function
df2 = df.rename(index=lambda Index: Index+'_Index')
print(df2)
Yields below output.
Courses Fee Duration Discount
r1_Index Spark 20000 30days 1000
r2_Index PySpark 25000 40days 2300
r3_Index Python 22000 35days 1200
r4_Index pandas 30000 50days 2000
7. Complete Example For Rename Index Values of DataFrame
import pandas as pd
technologies = {
'Courses':["Spark","PySpark","Python","pandas"],
'Fee' :[20000,25000,22000,30000],
'Duration':['30days','40days','35days','50days'],
'Discount':[1000,2300,1200,2000]
}
index_labels=['r1','r2','r3','r4']
df = pd.DataFrame(technologies,index=index_labels)
print(df)
# Change the row indexes
df.index = ['index_1', 'index_2', 'index_3', 'index_4']
print(df)
# Using DataFrame.rename() to rename index values
df2 = df.rename(index={'r3': 'Index_3'})
print(df2)
# Rename multiple index value
df2 = df.rename(index={'r1':'Index_1','r2':'Index_2'})
print(df2)
# Changing the DataFrame inplace
df.rename(index={'r3': 'Index_3','r4': 'Index_4'}, inplace=True)
print(df)
# Append a value to DataFrame index row Using lambda function
df2 = df.rename(index=lambda Index: Index+'_Index')
print(df2)
Conclusion
In this article, you have learned how to rename index values of pandas DataFrame using DataFrame.index, DataFrame.rename() and lambda functions with examples. You have also learned how to rename single and multilevel Index values.
Happy Learning !!
Related Articles
- Pandas Rename Index of DataFrame
- Pandas Rename Column with Examples
- Rename Specific Columns in Pandas
- How to Print Pandas DataFrame without Index
- Pandas Remap Values in Column with a Dictionary (Dict)
- How to Rename Multiple Columns in pandas
- How to Rename Column by Index in pandas
- How to Rename Specific Columns in Pandas
