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Series.searchsorted(v, side='left', sorter=None)
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Find indices where elements should be inserted to maintain order.
Find the indices into a sorted Series
self
such that, if the corresponding elements inv
were inserted before the indices, the order ofself
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 ofnp.argsort
.Returns: indices : array of ints
Array of insertion points with the same shape as
v
.See also
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
Series.searchsorted()
2017-01-12 04:54:42
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