Index.copy()

Index.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.

Index.get_slice_bound()

Index.get_slice_bound(label, side, kind) [source] Calculate slice bound that corresponds to given label. Returns leftmost (one-past-the-rightmost if side=='right') position of given label. Parameters: label : object side : {?left?, ?right?} kind : {?ix?, ?loc?, ?getitem?}

Resampler.pad()

Resampler.pad(limit=None) [source] Forward fill the values Parameters: limit : integer, optional limit of how many values to fill See also Series.fillna, DataFrame.fillna

Series.resample()

Series.resample(rule, how=None, axis=0, fill_method=None, closed=None, label=None, convention='start', kind=None, loffset=None, limit=None, base=0, on=None, level=None) [source] Convenience method for frequency conversion and resampling of time series. Object must have a datetime-like index (DatetimeIndex, PeriodIndex, or TimedeltaIndex), or pass datetime-like values to the on or level keyword. Parameters: rule : string the offset string or object representing target conversion axis : in

MultiIndex.is_()

MultiIndex.is_(other) [source] More flexible, faster check like is but that works through views Note: this is not the same as Index.identical(), which checks that metadata is also the same. Parameters: other : object other object to compare against. Returns: True if both have same underlying data, False otherwise : bool

DatetimeIndex.weekofyear

DatetimeIndex.weekofyear The week ordinal of the year

DatetimeIndex.union_many()

DatetimeIndex.union_many(others) [source] A bit of a hack to accelerate unioning a collection of indexes

GroupBy.get_group()

GroupBy.get_group(name, obj=None) [source] Constructs NDFrame from group with provided name Parameters: name : object the name of the group to get as a DataFrame obj : NDFrame, default None the NDFrame to take the DataFrame out of. If it is None, the object groupby was called on will be used Returns: group : type of obj

Panel4D.bool()

Panel4D.bool() [source] Return the bool of a single element PandasObject. This must be a boolean scalar value, either True or False. Raise a ValueError if the PandasObject does not have exactly 1 element, or that element is not boolean

CategoricalIndex.dtype_str

CategoricalIndex.dtype_str = None