DatetimeIndex.floor(freq) [source] floor the index to the specified freq Parameters: freq : freq string/object Returns: index of same type Raises: ValueError if the freq cannot be converted

DatetimeIndex.drop(labels, errors='raise') [source] Make new Index with passed list of labels deleted Parameters: labels : array-like errors : {?ignore?, ?raise?}, default ?raise? If ?ignore?, suppress error and existing labels are dropped. Returns: dropped : Index

DatetimeIndex.rename(name, inplace=False) [source] Set new names on index. Defaults to returning new index. Parameters: name : str or list name to set inplace : bool if True, mutates in place Returns: new index (of same type and class...etc) [if inplace, returns None]

DatetimeIndex.indexer_between_time(start_time, end_time, include_start=True, include_end=True) [source] Select values between particular times of day (e.g., 9:00-9:30AM). Return values of the index between two times. If start_time or end_time are strings then tseres.tools.to_time is used to convert to a time object. Parameters: start_time, end_time : datetime.time, str datetime.time or string in appropriate format (?%H:%M?, ?%H%M?, ?%I:%M%p?, ?%I%M%p?, ?%H:%M:%S?, ?%H%M%S?, ?%I:%M:%S%p?,

DatetimeIndex.is_lexsorted_for_tuple(tup) [source]

Series.sum(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return the sum of the values for the requested axis Parameters: axis : {index (0)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar numeric_only : boolean, default None Include only float, int, boolean co

DatetimeIndex.to_series(keep_tz=False) [source] Create a Series with both index and values equal to the index keys useful with map for returning an indexer based on an index Parameters: keep_tz : optional, defaults False. return the data keeping the timezone. If keep_tz is True: If the timezone is not set, the resulting Series will have a datetime64[ns] dtype. Otherwise the Series will have an datetime64[ns, tz] dtype; the tz will be preserved. If keep_tz is False: Series will have a d

DatetimeIndex.isin(values) [source] Compute boolean array of whether each index value is found in the passed set of values Parameters: values : set or sequence of values Returns: is_contained : ndarray (boolean dtype)

DatetimeIndex.union(other) [source] Specialized union for DatetimeIndex objects. If combine overlapping ranges with the same DateOffset, will be much faster than Index.union Parameters: other : DatetimeIndex or array-like Returns: y : Index or DatetimeIndex

DatetimeIndex.asof(label) [source] For a sorted index, return the most recent label up to and including the passed label. Return NaN if not found. See also get_loc asof is a thin wrapper around get_loc with method=?pad?