Series.filter()

Series.filter(items=None, like=None, regex=None, axis=None) [source]

Subset rows or columns of dataframe according to labels in the specified index.

Note that this routine does not filter a dataframe on its contents. The filter is applied to the labels of the index.

Parameters:

Parameters:	items : list-like List of info axis to restrict to (must not all be present) like : string Keep info axis where ?arg in col == True? regex : string (regular expression) Keep info axis with re.search(regex, col) == True axis : int or string axis name The axis to filter on. By default this is the info axis, ?index? for Series, ?columns? for DataFrame
Returns:	same type as input object

items : list-like

List of info axis to restrict to (must not all be present)

like : string

Keep info axis where ?arg in col == True?

regex : string (regular expression)

Keep info axis with re.search(regex, col) == True

axis : int or string axis name

The axis to filter on. By default this is the info axis, ?index? for Series, ?columns? for DataFrame

Returns:

same type as input object

The items, like, and regex parameters are enforced to be mutually exclusive.

axis defaults to the info axis that is used when indexing with [].

>>> df
one  two  three
mouse     1    2      3
rabbit    4    5      6

>>> # select columns by name
>>> df.filter(items=['one', 'three'])
one  three
mouse     1      3
rabbit    4      6

>>> # select columns by regular expression
>>> df.filter(regex='e$', axis=1)
one  three
mouse     1      3
rabbit    4      6

>>> # select rows containing 'bbi'
>>> df.filter(like='bbi', axis=0)
one  two  three
rabbit    4    5      6

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2017-01-12 04:53:56

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