Utils

Utility functions for the pandas_checks package.

_display_line(line, lead_in=None, colors={})

Displays a line of text with optional formatting.

Parameters:

Name	Type	Description	Default
line	str	The text to display.	required
lead_in	Union[str, None]	The optional text to display before the main text.	None
colors	Dict	An optional dictionary containing color options for the text and lead-in text. See syntax in docstring for _render_text().	{}

Returns:

Type	Description
None	None

_has_nulls(data, fail_message, raise_exception=True, exception_to_raise=DataError)

Utility function to check for nulls as part of a larger check

_is_type(data, dtype)

Utility function to check if a dataframe's columns or one series has an expected type. Includes special handling for strings, since 'object' type in Pandas may not mean a string

_lambda_to_string(lambda_func)

Create a string representation of a lambda function.

Parameters:

Name	Type	Description	Default
lambda_func	Callable	An arbitrary function in lambda form	required

Returns:

Type	Description
str	A string version of lambda_func

Todo

This still returns all arguments to the calling function. They get entangled with the argument when it's a lambda function. Try other ways to get just the argument we want.

_series_is_type(s, dtype)

Utility function to check if a series has an expected type. Includes special handling for strings, since 'object' type in Pandas may not mean a string