tidypolars_extra.helpers

Classes

DescCol

Expressions that can be used in various contexts.

Functions

across(cols[, fn, names_prefix, names_suffix])	Apply a function across a selection of columns
contains(match[, ignore_case])	Contains a literal string
desc(x)	Mark a column to order in descending
ends_with(match[, ignore_case])	Ends with a suffix
everything()	Selects all columns
lag(x[, n, default])	Get lagging values
matches(match[, ignore_case])	Matches pattern
starts_with(match[, ignore_case])	Starts with a prefix
where(col_type)	Select columns by type using a string

Module Contents

class tidypolars_extra.helpers.DescCol

Bases: polars.Expr

Expressions that can be used in various contexts.

tidypolars_extra.helpers.across(cols, fn=lambda x: ..., names_prefix=None, names_suffix=None)

Apply a function across a selection of columns

Parameters:

• cols (list) – Columns to operate on

• fn (lambda) – A function or lambda to apply to each column

• names_prefix (Optional - str) – Prefix to append to changed columns

Examples

>>> df = tp.tibble(x = ['a', 'a', 'b'], y = range(3), z = range(3))
>>> df.mutate(across(['y', 'z'], lambda x: x * 2))
>>> df.mutate(across(tp.Int64, lambda x: x * 2, names_prefix = "double_"))
>>> df.summarize(across(['y', 'z'], tp.mean), by = 'x')

tidypolars_extra.helpers.contains(match, ignore_case=True)

Contains a literal string

Parameters:

• match (str) – String to match columns

• ignore_case (bool) – If TRUE, the default, ignores case when matching names.

Examples

>>> df = tp.tibble({'a': range(3), 'b': range(3), 'c': ['a', 'a', 'b']})
>>> df.select(contains('c'))

tidypolars_extra.helpers.desc(x)

Mark a column to order in descending

tidypolars_extra.helpers.ends_with(match, ignore_case=True)

Ends with a suffix

Parameters:

• match (str) – String to match columns

• ignore_case (bool) – If TRUE, the default, ignores case when matching names.

Examples

>>> df = tp.tibble({'a': range(3), 'b_code': range(3), 'c_code': ['a', 'a', 'b']})
>>> df.select(ends_with('code'))

tidypolars_extra.helpers.everything()

Selects all columns

Examples

>>> df = tp.tibble({'a': range(3), 'b': range(3), 'c': ['a', 'a', 'b']})
>>> df.select(everything())

tidypolars_extra.helpers.lag(x, n: int = 1, default=None)

Get lagging values

Parameters:

• x (Expr, Series) – Column to operate on

• n (int) – Number of positions to lag by

• default (optional) – Value to fill in missing values

Examples

>>> df.mutate(lag_x = tp.lag(col('x')))
>>> df.mutate(lag_x = tp.lag('x'))

tidypolars_extra.helpers.matches(match, ignore_case=False)

Matches pattern

Parameters:

• match (str) – String to match columns

• ignore_case (bool) – If True, the default, ignores case when matching names.

Examples

>>> df = tp.tibble({'a': range(3), 'add': range(3), 'sub': ['a', 'a', 'b']})
>>> df.select(tp.matches('a'))

tidypolars_extra.helpers.starts_with(match, ignore_case=True)

Starts with a prefix

Parameters:

• match (str) – String to match columns

• ignore_case (bool) – If TRUE, the default, ignores case when matching names.

Examples

>>> df = tp.tibble({'a': range(3), 'add': range(3), 'sub': ['a', 'a', 'b']})
>>> df.select(starts_with('a'))

tidypolars_extra.helpers.where(col_type)

Select columns by type using a string

Options:

character : factor (ordered or unordered) and string string : only strings, exclude factors factor : ordered or unordered factors ordered : only ordered factors unordered : only unordered factors

numeric : float or integet float : only float integer : only integer

date : date datetime : data and time

Examples

>>> from tidypolars_extra.data import mtcars
>>> df = mtcars
>>> df.select(tp.where("integer"))
>>> df.select(tp.where("numeric"))
>>> df.select(tp.where("string") | tp.where("integer"))