## sample_missing()


Generate a dataset riddled with missing values.


Usage


``` python
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

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

True