Pelage: Defensive analysis for Polars
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  • API Reference
  • Examples
  • Coming from dbt
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  1. Check functions
  2. has_no_infs
  • API Reference
  • Check functions
    • has_columns
    • has_dtypes
    • has_no_nulls
    • has_no_infs
    • unique
    • unique_combination_of_columns
    • accepted_values
    • not_accepted_values
    • accepted_range
    • maintains_relationships
    • column_is_within_n_std
    • custom_check
  • Checks with group_by
    • has_shape
    • at_least_one
    • not_constant
    • not_null_proportion
    • has_mandatory_values
    • mutually_exclusive_ranges
    • is_monotonic
  • Exceptions
    • PolarsAssertError

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  • has_no_infs
    • Parameters
    • Returns
    • Examples
  1. Check functions
  2. has_no_infs

has_no_infs

checks.has_no_infs(data, columns=None)

Check if a DataFrame has any infinite (inf) values.

Parameters

data: PolarsLazyOrDataFrame

The input DataFrame to check for null values.

columns: Optional[PolarsColumnType] = None

Columns to consider for null value check. By default, all columns are checked.

Returns

Type Description
PolarsLazyOrDataFrame The original polars DataFrame or LazyFrame when the check passes

Examples

>>> import polars as pl
>>> import pelage as plg
>>> df = pl.DataFrame(
...     {
...         "a": [1, 2],
...         "b": [1.0, float("inf")],
...     }
... )
>>> plg.has_no_infs(df)
Traceback (most recent call last):
  ...
pelage.checks.PolarsAssertError: Details
shape: (1, 2)
┌─────┬─────┐
│ a   ┆ b   │
│ --- ┆ --- │
│ i64 ┆ f64 │
╞═════╪═════╡
│ 2   ┆ inf │
└─────┴─────┘
Error with the DataFrame passed to the check function:
--> The were unexpeted infinites in the dataframe. See above.
>>> plg.has_no_infs(df, ["a"])  # or  plg.has_no_infs(df, "a")
shape: (2, 2)
┌─────┬─────┐
│ a   ┆ b   │
│ --- ┆ --- │
│ i64 ┆ f64 │
╞═════╪═════╡
│ 1   ┆ 1.0 │
│ 2   ┆ inf │
└─────┴─────┘
has_no_nulls
unique