sample_missing()

Generate a dataset riddled with missing values.

Usage

sample_missing(n=15)

Parameters

n: int = 15

Number of rows.

Returns

dict[str, list]

Column-oriented dict where roughly 25 percent of values are None or float('nan').

Examples

>>> data = sample_missing(10)
>>> None in data["alpha"]
True