pandas.Series.searchsorted — pandas 0.18.1 documentation (original) (raw)
Series.searchsorted(v, side='left', sorter=None)¶
Find indices where elements should be inserted to maintain order.
Find the indices into a sorted Series self such that, if the corresponding elements in v were inserted before the indices, the order of self would be preserved.
| Parameters: | v : array_like Values to insert into self. side : {‘left’, ‘right’}, optional If ‘left’, the index of the first suitable location found is given. If ‘right’, return the last such index. If there is no suitable index, return either 0 or N (where N is the length of self). sorter : 1-D array_like, optional Optional array of integer indices that sort self into ascending order. They are typically the result of np.argsort. |
|---|---|
| Returns: | indices : array of ints Array of insertion points with the same shape as v. |
Notes
Binary search is used to find the required insertion points.
Examples
x = pd.Series([1, 2, 3]) x 0 1 1 2 2 3 dtype: int64 x.searchsorted(4) array([3]) x.searchsorted([0, 4]) array([0, 3]) x.searchsorted([1, 3], side='left') array([0, 2]) x.searchsorted([1, 3], side='right') array([1, 3])
x = pd.Categorical(['apple', 'bread', 'bread', 'cheese', 'milk' ]) [apple, bread, bread, cheese, milk] Categories (4, object): [apple < bread < cheese < milk] x.searchsorted('bread') array([1]) # Note: an array, not a scalar x.searchsorted(['bread']) array([1]) x.searchsorted(['bread', 'eggs']) array([1, 4]) x.searchsorted(['bread', 'eggs'], side='right') array([3, 4]) # eggs before milk