ENH: Add index_col parameter to the Dataframe constructor

[tomhoq]

Feature Type

• Adding new functionality to pandas

• Changing existing functionality in pandas

• Removing existing functionality in pandas

Problem Description

Currently, the only way to set a DataFrame's index column is by calling the set_index method on it.

data = {
        'Name': ['Alice', 'Bob', 'Charlie', 'David'],
        'Age': [25, 30, 35, 40],
        'City': ['New York', 'Los Angeles', 'Chicago', 'Houston']
}

df = pd.DataFrame(data)
print(df)

      Name  Age         City
0    Alice   25     New York
1      Bob   30  Los Angeles
2  Charlie   35      Chicago
3    David   40      Houston

df = df.set_index("Name")
print(df)

         Age         City
Name
Alice     25     New York
Bob       30  Los Angeles
Charlie   35      Chicago
David     40      Houston

Feature Description

I propose adding a new parameter to the Dataframe constructor: index_col.

data = {
        'Name': ['Alice', 'Bob', 'Charlie', 'David'],
        'Age': [25, 30, 35, 40],
        'City': ['New York', 'Los Angeles', 'Chicago', 'Houston']
}

df = pd.DataFrame(data, index_col="Name")
print(df)

         Age         City
Name
Alice     25     New York
Bob       30  Los Angeles
Charlie   35      Chicago
David     40      Houston

With this addition you would be able to remove/change the default index column without having to call the set_index method, simplifying code. It would also make pandas overall more coherent as for example, the read_csv and read_excel, both return a DataFrame and already have this functionality in them.

To add upon this, I would also propose adding an index_col to the read_parquet function, working in a similar way.

Alternative Solutions

n/a

Additional Context

No response

[mroeschke]

Thanks for the suggestion but I would be -1 on this feature. index_col seems to be highly tailored to when data is a mapping and wouldn't make much sense for other list-like data. I believe using set_index is an adequate alternative