Panel4D.interpolate(method='linear', axis=0, limit=None, inplace=False, limit_direction='forward', downcast=None, **kwargs) [source] Interpolate values according to different methods. Please note that only method='linear' is supported for DataFrames/Series with a MultiIndex. Parameters: method : {?linear?, ?time?, ?index?, ?values?, ?nearest?, ?zero?, ?slinear?, ?quadratic?, ?cubic?, ?barycentric?, ?krogh?, ?polynomial?, ?spline?, ?piecewise_polynomial?, ?from_derivatives?, ?pchip?, ?aki

Index.intersection(other) [source] Form the intersection of two Index objects. This returns a new Index with elements common to the index and other. Sortedness of the result is not guaranteed. Parameters: other : Index or array-like Returns: intersection : Index Examples >>> idx1 = pd.Index([1, 2, 3, 4]) >>> idx2 = pd.Index([3, 4, 5, 6]) >>> idx1.intersection(idx2) Int64Index([3, 4], dtype='int64')

CategoricalIndex.map(mapper) [source] Apply mapper function to its categories (not codes). Parameters: mapper : callable Function to be applied. When all categories are mapped to different categories, the result will be Categorical which has the same order property as the original. Otherwise, the result will be np.ndarray. Returns: applied : Categorical or np.ndarray.

Series.str.cat(others=None, sep=None, na_rep=None) [source] Concatenate strings in the Series/Index with given separator. Parameters: others : list-like, or list of list-likes If None, returns str concatenating strings of the Series sep : string or None, default None na_rep : string or None, default None If None, NA in the series are ignored. Returns: concat : Series/Index of objects or str Examples When na_rep is None (default behavior), NaN value(s) in the Series are ignored. >

CategoricalIndex.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

Expanding.std(ddof=1, *args, **kwargs) [source] expanding standard deviation Parameters: ddof : int, default 1 Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements. Returns: same type as input See also pandas.Series.expanding, pandas.DataFrame.expanding

TimedeltaIndex.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

DataFrame.plot.kde(**kwds) [source] Kernel Density Estimate plot New in version 0.17.0. Parameters: **kwds : optional Keyword arguments to pass on to pandas.DataFrame.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

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.reindex(target, method=None, level=None, limit=None, tolerance=None) [source] Create index with target?s values (move/add/delete values as necessary) Parameters: target : an iterable Returns: new_index : pd.Index Resulting index indexer : np.ndarray or None Indices of output values in original index