Add a single string value as a new column to polars DataFrame [duplicate]

Question

Being a new user to polars coming from pandas, I have searched polars GitHub pages, user guide, stackoverflow and discord channel on how to add a new column to a polars dataframe. I have only found polars examples on how to add new columns based on existing ones.

How should the following pandas example be converted to polars syntax?

import polars as pl

df = pl.DataFrame({'existing_column': [1, 2, 3]})

df_pd = df.to_pandas()
df_pd['new_column'] = 'some text'

With expected content of final dataframe:

existing_column	new_column
1	some_text
2	some_text
3	some_text

Luca · Accepted Answer · 2023-03-13 09:32:06Z

34

you can use with_columns and pl.lit to add a new column with Polars that is a constant and not based on existing columns.

You can use it for both text and numbers.

Here is an example:

df.with_columns(
    new_column = pl.lit('some_text')
)

The advantage of Polars is that all new columns added and all columns transformed within the same with_columns will be calculated in parallel.

answered Mar 13, 2023 at 9:32

Luca

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2 Comments

E.Serra Over a year ago

Just a note after a good 20 min of time wasting, if you have a column name you can just do: df.with_columns(**{col_name_var: pl.lit('some_text')}) Which will be translated to df.with_columns(ACTUALVALUEOFcol_name_var = pl.lit('some_text'))

Hericks Over a year ago

@E.Serra To any future reader: For that there existspl.Expr.alias.

Hericks · Accepted Answer · 2024-05-07 10:50:40Z

11

Polars provides the user with pl.lit, which can be used within pl.DataFrame.with_columns to create a new column with a literal value (string, int, float).

df.with_columns(
    pl.lit("some_text").alias("new_column")
)

pl.Expr.alias is used to assign a name to the new column.

answered May 7, 2024 at 10:50

Hericks

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