[FIXED] What's the polars equivalent to the pandas `.iloc` method?

Issue

I'm looking for the recommended way to select an individual row of a polars.DataFrame by row number: something largely equivalent to pandas.DataFrame's .iloc[[n]] method for a given integer n.

For polars imported as pl and a polars DataFrame df, my current approach would be:

# for example
n = 3

# create row count, filter for individual row, drop the row count.
new_df = (
    df.with_row_count()
    .filter(pl.col('row_nr') == n)
    .select(pl.exclude('row_nr'))
)

I'm migrating from Pandas, and I've read the Pandas-to-Polars migration guide, but a slick solution to this specific case wasn't addressed there. Edit: to clarify, I am looking for an approach that returns a polars.DataFrame object for the chosen row.

Does anyone have something slicker?

Solution

This is a very good sheet by: @Liam Brannigan

Credit to them.

https://www.rhosignal.com/posts/polars-pandas-cheatsheet/

A glimse from the sheet:

You can find other information related to Filtering Rows using iloc and its equivalent in polars in the sheet.

Answered By - Goku - stands with Palestine