Series.pipe()

Series.pipe(func, *args, **kwargs) [source]

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

New in version 0.16.2.

Parameters:

Parameters:	func : function function to apply to the NDFrame. `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 NDFrame. args : positional arguments passed into `func`. kwargs : a dictionary of keyword arguments passed into `func`.
Returns:	object : the return type of `func`.

func : function

function to apply to the NDFrame. 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 NDFrame.

args : positional arguments passed into func.

kwargs : a dictionary of keyword arguments passed into func.

Returns:

object : the return type of func.

Notes

Use .pipe when chaining together functions that expect on Series or DataFrames. Instead of writing

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

You can write

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

Links:

http://pandas.pydata.org/pandas-docs/version/0.19.2/generated/pandas.Series.pipe.html

doc_Pandas

2017-01-12 04:54:24

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