DataFrame.truncate(before=None, after=None, axis=None, copy=True) [source] Truncates a sorted NDFrame before and/or after some particular index value. If the axis contains only datetime values, before/after parameters are converted to datetime values. Parameters: before : date Truncate before index value after : date Truncate after index value axis : the truncation axis, defaults to the stat axis copy : boolean, default is True, return a copy of the truncated section Returns: trunc

Index.is_all_dates = None

Series.dt.ceil(*args, **kwargs) [source] ceil 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.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.slice_locs(start=None, end=None, step=None, kind=None) [source] Compute slice locations for input labels. Parameters: start : label, default None If None, defaults to the beginning end : label, default None If None, defaults to the end step : int, defaults None If None, defaults to 1 kind : {?ix?, ?loc?, ?getitem?} or None Returns: start, end : int

DatetimeIndex.daysinmonth The number of days in the month New in version 0.16.0.

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

Panel4D.cummax(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative max over requested axis. Parameters: axis : {labels (0), items (1), major_axis (2), minor_axis (3)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA Returns: cummax : Panel

pandas.pivot(index, columns, values) [source] Produce ?pivot? table based on 3 columns of this DataFrame. Uses unique values from index / columns and fills with values. Parameters: index : ndarray Labels to use to make new frame?s index columns : ndarray Labels to use to make new frame?s columns values : ndarray Values to use for populating new frame?s values Returns: DataFrame Notes Obviously, all 3 of the input arguments must have the same length