TimedeltaIndex.dropna(how='any') [source] Return Index without NA/NaN values Parameters: how : {?any?, ?all?}, default ?any? If the Index is a MultiIndex, drop the value when any or all levels are NaN. Returns: valid : Index

TimedeltaIndex.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

TimedeltaIndex.difference(other) [source] Return a new Index with elements from the index that are not in other. This is the set difference of two Index objects. It?s sorted if sorting is possible. Parameters: other : Index or array-like Returns: difference : Index Examples >>> idx1 = pd.Index([1, 2, 3, 4]) >>> idx2 = pd.Index([3, 4, 5, 6]) >>> idx1.difference(idx2) Int64Index([1, 2], dtype='int64')

TimedeltaIndex.delete(loc) [source] Make a new DatetimeIndex with passed location(s) deleted. Parameters: loc: int, slice or array of ints Indicate which sub-arrays to remove. Returns: new_index : TimedeltaIndex

TimedeltaIndex.days Number of days for each element.

TimedeltaIndex.data return the data pointer of the underlying data

TimedeltaIndex.copy(name=None, deep=False, dtype=None, **kwargs) [source] Make a copy of this object. Name and dtype sets those attributes on the new object. Parameters: name : string, optional deep : boolean, default False dtype : numpy dtype or pandas type Returns: copy : Index Notes In most cases, there should be no functional difference from using deep, but if deep is passed it will attempt to deepcopy.

TimedeltaIndex.components Return a dataframe of the components (days, hours, minutes, seconds, milliseconds, microseconds, nanoseconds) of the Timedeltas. Returns: a DataFrame

TimedeltaIndex.ceil(freq) [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

TimedeltaIndex.base return the base object if the memory of the underlying data is shared