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Showing content from http://pandas.pydata.org/pandas-docs/version/0.20/generated/pandas.Series.pipe.html below:

pandas.Series.pipe — pandas 0.20.3 documentation

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

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

New in version 0.16.2.

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.

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)
...  )

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