In pandas we can select columns from dataframe using df_new = df[["A","B"]]. How are columns selected in polars?
I tried usng df_new = df.get_columns(["A","B"]), but an error is raised.
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It would be better if you can also share the error.george– george2023-01-08 16:13:57 +00:00Commented Jan 8, 2023 at 16:13
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3 Answers
I suggest you to read or skim through Polars introduction in the User guide
It is nicely written with some good examples.
You can choose columns by using Polars select statement
df_new = df.select("A", "B")
Comments
In polars, you would use pl.DataFrame.select and pass the column names of interest directly as parameters.
import polars as pl
df = pl.DataFrame({
"id": [1, 2, 3],
"name": ["John", "Jane", "Jake"],
"age": [16, 20, 25],
})
df.select("id", "name")
shape: (3, 2)
┌─────┬──────┐
│ id ┆ name │
│ --- ┆ --- │
│ i64 ┆ str │
╞═════╪══════╡
│ 1 ┆ John │
│ 2 ┆ Jane │
│ 3 ┆ Jake │
└─────┴──────┘
Comments
Starting from Polars 0.18.1 You can use polars.selectors.by_name to select all columns matching the given names.
>>> import polars as pl
>>> import polars.selectors as cs
>>>
>>> df = pl.DataFrame(
... {
... "id": [1, 2, 3],
... "name": ["John", "Jane", "Jake"],
... "else": [10.0, 20.0, 30.0],
... }
... )
>>>
>>> print(df.select(cs.by_name('id', 'name')))
shape: (3, 2)
┌─────┬──────┐
│ id ┆ name │
│ --- ┆ --- │
│ i64 ┆ str │
╞═════╪══════╡
│ 1 ┆ John │
│ 2 ┆ Jane │
│ 3 ┆ Jake │
└─────┴──────┘
Comments
