pandas.DataFrame.filter#

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

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

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

Parameters:

itemslist-like

Keep labels from axis which are in items.

likestr

Keep labels from axis for which “like in label == True”.

regexstr (regular expression)

Keep labels from axis for which re.search(regex, label) == True.

axis{0 or ‘index’, 1 or ‘columns’, None}, default None

The axis to filter on, expressed either as an index (int)or axis name (str). By default this is the info axis, ‘columns’ forDataFrame. ForSeries this parameter is unused and defaults toNone.

Returns:

same type as input object

See also

DataFrame.loc

Access a group of rows and columns by label(s) or a boolean array.

Notes

Theitems,like, andregex parameters areenforced to be mutually exclusive.

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

Examples

>>>df=pd.DataFrame(np.array(([1,2,3],[4,5,6])),...index=['mouse','rabbit'],...columns=['one','two','three'])>>>df        one  two  threemouse     1    2      3rabbit    4    5      6

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

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

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