DatetimeIndex.tzinfo Alias for tz attribute

TimedeltaIndex.shift(n, freq=None) [source] Specialized shift which produces a DatetimeIndex Parameters: n : int Periods to shift by freq : DateOffset or timedelta-like, optional Returns: shifted : DatetimeIndex

DataFrame.squeeze(**kwargs) [source] Squeeze length 1 dimensions.

Panel.subtract(other, axis=0) [source] Subtraction of series and other, element-wise (binary operator sub). Equivalent to panel - other. Parameters: other : DataFrame or Panel axis : {items, major_axis, minor_axis} Axis to broadcast over Returns: Panel See also Panel.rsub

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

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

Panel.to_hdf(path_or_buf, key, **kwargs) [source] Write the contained data to an HDF5 file using HDFStore. Parameters: path_or_buf : the path (string) or HDFStore object key : string indentifier for the group in the store mode : optional, {?a?, ?w?, ?r+?}, default ?a? 'w' Write; a new file is created (an existing file with the same name would be deleted). 'a' Append; an existing file is opened for reading and writing, and if the file does not exist it is created. 'r+' It is s

DataFrame.copy(deep=True) [source] Make a copy of this objects data. Parameters: deep : boolean or string, default True Make a deep copy, including a copy of the data and the indices. With deep=False neither the indices or the data are copied. Note that when deep=True data is copied, actual python objects will not be copied recursively, only the reference to the object. This is in contrast to copy.deepcopy in the Standard Library, which recursively copies object data. Returns: copy : t

Series.str.slice(start=None, stop=None, step=None) [source] Slice substrings from each element in the Series/Index Parameters: start : int or None stop : int or None step : int or None Returns: sliced : Series/Index of objects

DataFrame.rmul(other, axis='columns', level=None, fill_value=None) [source] Multiplication of dataframe and other, element-wise (binary operator rmul). Equivalent to other * dataframe, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with this value.