Index.is_monotonic_decreasing return if the index is monotonic decreasing (only equal or decreasing) values.

MultiIndex.unique() [source] Return Index of unique values in the object. Significantly faster than numpy.unique. Includes NA values. The order of the original is preserved. Returns: uniques : Index

HDFStore.put(key, value, format=None, append=False, **kwargs) [source] Store object in HDFStore Parameters: key : object value : {Series, DataFrame, Panel} format : ?fixed(f)|table(t)?, default is ?fixed? fixed(f) : Fixed format Fast writing/reading. Not-appendable, nor searchable table(t) : Table format Write as a PyTables Table structure which may perform worse but allow more flexible operations like searching / selecting subsets of the data append : boolean, default False This w

TimedeltaIndex.dtype

Series.dot(other) [source] Matrix multiplication with DataFrame or inner-product with Series objects Parameters: other : Series or DataFrame Returns: dot_product : scalar or Series

TimedeltaIndex.nbytes return the number of bytes in the underlying data

MultiIndex.is_monotonic alias for is_monotonic_increasing (deprecated)

MultiIndex.equal_levels(other) [source] Return True if the levels of both MultiIndex objects are the same

Panel4D.iteritems() [source] Iterate over (label, values) on info axis This is index for Series, columns for DataFrame, major_axis for Panel, and so on.

CategoricalIndex.get_indexer_for(target, **kwargs) [source] guaranteed return of an indexer even when non-unique