Pandas Dataframe Index

The index in a Pandas DataFrame represents the labels assigned to each row. It helps in identifying and accessing data efficiently and can be either default numeric values or custom-defined labels.

Accessing and Modifying the Index

Accessing and modifying the index allows to understand how rows are labeled and customize them as needed. One can view the existing index using the .index attribute and later update it based on your requirements.

RangeIndex(start=0, stop=3, step=1)

Setting a Custom Index

The set_index() method is used to change the index of a DataFrame by setting one or more columns as the new index.

 Age Salary
Name 
Jake 25 50000
Mike 30 55000

Resetting the Index

If one need to reset the index back to default integer index, use reset_index() method. This will convert the current index into a regular column and create a new default index.

 Name Age
0 Jake 25
1 Maria 30
2 Sam 22

Indexing with loc

The loc[] method in pandas allows to access rows and columns of a dataFrame using their labels, making it easy to retrieve specific data points.

age 25
city NY
Name: Alice, dtype: object

Changing the Index

The set_index() method is used to change the index of a DataFrame by setting one or more columns as the new index.

 Name Salary
Age 
25 Jake 50000
30 Mike 55000
22 Sam 40000