View and Inspect Polars DataFrames

Polars truncates output by default so a print does not flood your terminal. That is great until you actually want to see everything. Here is how to inspect a frame, print all rows, add row numbers, and pull data out.

Print all rows and columns

Raise the display limits with pl.Config. Pass -1 to show every row. Wrap it in a context manager if you only want it for one print.

• pl.Config.set_tbl_rows(-1) # show all rows

• pl.Config.set_tbl_cols(-1) # show all columns

• print(df)

• # temporary, just for this block:

• with pl.Config(tbl_rows=-1):

• print(df)

Add row numbers

with_row_index adds a 0-based index column, which is the Polars way to get line numbers for a DataFrame. (In older versions this was with_row_count.)

• df = df.with_row_index("row")

• # start at 1:

• df = df.with_row_index("row", offset=1)

Convert a column to a list

Pull a column out as a plain Python list with to_list. This answers using to_list() in Polars.

• values = df["a"].to_list()

• # or explicitly:

• values = df.get_column("a").to_list()

Quick looks

A few one-liners for a fast read on any frame.

• df.head(5)

• df.tail(5)

• df.sample(5)

• df.describe()

• df.schema # column names and types

• df.shape # (rows, columns)

Stack frames: hstack and vstack

hstack adds columns side by side, vstack stacks rows. For many frames at once, pl.concat is cleaner. This is what hstack does in Polars.

• df.hstack([other]) # add columns (same number of rows)

• df.vstack(other) # add rows (same columns)

• pl.concat([df1, df2]) # stack many frames by rows

• pl.concat([df1, df2], how="horizontal") # side by side

To build the frames you are inspecting, see creating DataFrames; to narrow them down, see filtering rows. Everything else is in the Python Polars cheat sheet.