Python 3.12.3
Polars 1.8.2
Polars-lts-cpu: 1.10.0
OS: Linux-lite 24.04 VM
I have the following code:
import polars as pl
countries = ['usa', 'france', 'brazil']
calling_codes = [1, 33, 55]
df = pl.DataFrame({'country': countries, 'calling_code': calling_codes })
capitals_dict = {'usa':'washington_dc', 'france': 'paris', 'brazil': 'brasilia'}
I would like to create a new column called capital
in df
that gets filled from the values in capitals_dict
if the country that is found in df['country']
is in the keys of capitals_dict
. I’m not entirely sure if that makes sense, so I can write some pseudo-code or something if that’s easier.
I have tried using filter
, replace
, with_columns
, and map_elements
but have thus far been unsuccessful. I have only known about polars
for a few days so I apologize for the simple question. Any help is much appreciated!
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