datawrangler.zoo.null

datawrangler.zoo.null.is_null(data)[source]

Test whether an object is None or empty.

Parameters

param data:: the to-be-tested object

Returns

return:: True if the object is None or empty and False otherwise.

datawrangler.zoo.null.wrangle_null(data, return_model=False, backend=None, model=None)[source]

Turn a null object (None or empty) into an empty DataFrame (pandas or Polars).

Parameters

param data:

the to-be-wrangled null object

param return_model:

if True, return a model (and its arguments and keyword arguments) for turning the null object into a DataFrame.

param backend:

str, optional The DataFrame backend to use (‘pandas’ or ‘polars’). If None, uses the default backend (pandas)

param model:

a function or constructor that will generate an empty DataFrame. This can also be specified as a dictionary with the following fields:

‘model’: a function or constructor

‘args’: a list of unnamed arguments to be passed to the given function or constructor

‘kwargs’: a dictionary of named arguments to be passed to the given function or constructor

If None, defaults to pandas.DataFrame or polars.DataFrame based on backend.

Returns

return:: an empty DataFrame (pandas or Polars based on backend)

Examples

>>> import datawrangler as dw
>>> # Create empty pandas DataFrame (default)
>>> df_pandas = dw.wrangle(None)
>>> # Create empty Polars DataFrame
>>> df_polars = dw.wrangle(None, backend='polars')