Select

The .select() method lets you choose specific columns of your data to keep. Each selection may include:

  • Specifying column(s) to include

  • Excluding (dropping) some columns

  • Renaming columns via a dictionary

  • Searching columns using helper functions like contains or starts_with

import tidypolars_extra as tp

mtcars = tp.tibble(tp.read_data(fn="tidypolars_extra/data/mtcars.csv", sep=",", silently=True))

mtcars

Selecting columns by name

The simplest way to select columns is by passing their names as strings.

mtcars.select("mpg", "cyl")

shape: (32, 2)
┌──────┬─────┐
│ mpg  ┆ cyl │
╞══════╪═════╡
│ 21.0 ┆ 6   │
│ 21.0 ┆ 6   │
│ 22.8 ┆ 4   │
│ …    ┆ …   │
└──────┴─────┘

You can also pass column names using tp.col():

mtcars.select(tp.col("mpg"), tp.col("cyl"))

Excluding columns

To remove columns, use the .drop() method:

mtcars.drop("mpg", "cyl")

shape: (32, 10)
┌───────────────────┬───────┬─────┬───┬─────┬─────┬──────┬──────┐
│ name              ┆ disp  ┆ hp  ┆ … ┆ vs  ┆ am  ┆ gear ┆ carb │
╞═══════════════════╪═══════╪═════╪═══╪═════╪═════╪══════╪══════╡
│ Mazda RX4         ┆ 160.0 ┆ 110 ┆ … ┆ 0   ┆ 1   ┆ 4    ┆ 4    │
│ Mazda RX4 Wag     ┆ 160.0 ┆ 110 ┆ … ┆ 0   ┆ 1   ┆ 4    ┆ 4    │
│ …                 ┆ …     ┆ …   ┆ … ┆ …   ┆ …   ┆ …    ┆ …    │
└───────────────────┴───────┴─────┴───┴─────┴─────┴──────┴──────┘

Renaming columns during selection

You can rename columns in a select by passing a dictionary mapping old names to new names:

mtcars.select({"mpg": "miles_per_gallon"}, "cyl")

shape: (32, 2)
┌─────────────────┬─────┐
│ miles_per_gallon ┆ cyl │
╞═════════════════╪═════╡
│ 21.0            ┆ 6   │
│ 21.0            ┆ 6   │
│ 22.8            ┆ 4   │
│ …               ┆ …   │
└─────────────────┴─────┘

Searching with helper functions

tidypolars-extra provides several helper functions to select columns by pattern matching.

contains — match columns containing a substring

mtcars.select(tp.contains("c"))

shape: (32, 3)
┌─────┬───────┬──────┐
│ cyl ┆ qsec  ┆ carb │
╞═════╪═══════╪══════╡
│ 6   ┆ 16.46 ┆ 4    │
│ 6   ┆ 17.02 ┆ 4    │
│ 4   ┆ 18.61 ┆ 1    │
│ …   ┆ …     ┆ …    │
└─────┴───────┴──────┘

starts_with — match columns starting with a prefix

mtcars.select(tp.starts_with("c"))

shape: (32, 2)
┌─────┬──────┐
│ cyl ┆ carb │
╞═════╪══════╡
│ 6   ┆ 4    │
│ 6   ┆ 4    │
│ 4   ┆ 1    │
│ …   ┆ …    │
└─────┴──────┘

ends_with — match columns ending with a suffix

mtcars.select(tp.ends_with("p"))

matches — match columns using a regex pattern

mtcars.select(tp.matches("^d"))

everything — select all columns

mtcars.select(tp.everything())

where — select columns by type

# Select only numeric (float) columns
mtcars.select(tp.where("float"))

Combining selection strategies

You can combine different selection strategies in a single call:

mtcars.select("name", tp.starts_with("c"))