Series.tz_convert(tz, axis=0, level=None, copy=True) [source] Convert tz-aware axis to target time zone. Parameters: tz : string or pytz.timezone object axis : the axis to convert level : int, str, default None If axis ia a MultiIndex, convert a specific level. Otherwise must be None copy : boolean, default True Also make a copy of the underlying data Raises: TypeError If the axis is tz-naive.

Panel4D.rfloordiv(other, axis=0) [source] Integer division of series and other, element-wise (binary operator rfloordiv). Equivalent to other // panel. Parameters: other : Panel or Panel4D axis : {labels, items, major_axis, minor_axis} Axis to broadcast over Returns: Panel4D See also Panel4D.floordiv

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

DataFrame.pivot_table(data, values=None, index=None, columns=None, aggfunc='mean', fill_value=None, margins=False, dropna=True, margins_name='All') [source] Create a spreadsheet-style pivot table as a DataFrame. The levels in the pivot table will be stored in MultiIndex objects (hierarchical indexes) on the index and columns of the result DataFrame Parameters: data : DataFrame values : column to aggregate, optional index : column, Grouper, array, or list of the previous If an array is pas

Panel.prod(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return the product of the values for the requested axis Parameters: axis : {items (0), major_axis (1), minor_axis (2)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a DataFrame numeric_only : boolean, default No

Panel.round(decimals=0, *args, **kwargs) [source] Round each value in Panel to a specified number of decimal places. New in version 0.18.0. Parameters: decimals : int Number of decimal places to round to (default: 0). If decimals is negative, it specifies the number of positions to the left of the decimal point. Returns: Panel object See also numpy.around

Panel.loc Purely label-location based indexer for selection by label. .loc[] is primarily label based, but may also be used with a boolean array. Allowed inputs are: A single label, e.g. 5 or 'a', (note that 5 is interpreted as a label of the index, and never as an integer position along the index). A list or array of labels, e.g. ['a', 'b', 'c']. A slice object with labels, e.g. 'a':'f' (note that contrary to usual python slices, both the start and the stop are included!). A boolean array.

DataFrame.pivot(index=None, columns=None, values=None) [source] Reshape data (produce a ?pivot? table) based on column values. Uses unique values from index / columns to form axes of the resulting DataFrame. Parameters: index : string or object, optional Column name to use to make new frame?s index. If None, uses existing index. columns : string or object Column name to use to make new frame?s columns values : string or object, optional Column name to use for populating new frame?s va

DatetimeIndex.take(indices, axis=0, allow_fill=True, fill_value=None, **kwargs) [source] return a new %(klass)s of the values selected by the indices For internal compatibility with numpy arrays. Parameters: indices : list Indices to be taken axis : int, optional The axis over which to select values, always 0. allow_fill : bool, default True fill_value : bool, default None If allow_fill=True and fill_value is not None, indices specified by -1 is regarded as NA. If Index doesn?t hold N

DataFrame.between_time(start_time, end_time, include_start=True, include_end=True) [source] Select values between particular times of the day (e.g., 9:00-9:30 AM). Parameters: start_time : datetime.time or string end_time : datetime.time or string include_start : boolean, default True include_end : boolean, default True Returns: values_between_time : type of caller