dask.dataframe.Series.pipe

Series.pipe(func, *args, **kwargs)

Apply func(self, *args, **kwargs).

This docstring was copied from pandas.core.frame.DataFrame.pipe.

Some inconsistencies with the Dask version may exist.

Parameters
funcfunction

Function to apply to the Series/DataFrame. args, and kwargs are passed into func. Alternatively a (callable, data_keyword) tuple where data_keyword is a string indicating the keyword of callable that expects the Series/DataFrame.

argsiterable, optional

Positional arguments passed into func.

kwargsmapping, optional

A dictionary of keyword arguments passed into func.

Returns
objectthe return type of func.

See also

DataFrame.apply

Apply a function along input axis of DataFrame.

DataFrame.applymap

Apply a function elementwise on a whole DataFrame.

Series.map

Apply a mapping correspondence on a Series.

Notes

Use .pipe when chaining together functions that expect Series, DataFrames or GroupBy objects. Instead of writing

>>> func(g(h(df), arg1=a), arg2=b, arg3=c)  

You can write

>>> (df.pipe(h)  
...    .pipe(g, arg1=a)
...    .pipe(func, arg2=b, arg3=c)
... )  

If you have a function that takes the data as (say) the second argument, pass a tuple indicating which keyword expects the data. For example, suppose f takes its data as arg2:

>>> (df.pipe(h)  
...    .pipe(g, arg1=a)
...    .pipe((func, 'arg2'), arg1=a, arg3=c)
...  )