Panel.to_excel(path, na_rep='', engine=None, **kwargs) [source] Write each DataFrame in Panel to a separate excel sheet Parameters: path : string or ExcelWriter object File path or existing ExcelWriter na_rep : string, default ?? Missing data representation engine : string, default None write engine to use - you can also set this via the options io.excel.xlsx.writer, io.excel.xls.writer, and io.excel.xlsm.writer. Other Parameters: float_format : string, default None Format string

Resampler.first(_method='first', *args, **kwargs) [source] Compute first of group values See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

Series.rename_axis(mapper, axis=0, copy=True, inplace=False) [source] Alter index and / or columns using input function or functions. A scaler or list-like for mapper will alter the Index.name or MultiIndex.names attribute. A function or dict for mapper will alter the labels. Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Parameters: mapper : scalar, list-like, dict-like or function, optional axis : int or string, default 0 copy

CategoricalIndex.sort_values(return_indexer=False, ascending=True) [source] Return sorted copy of Index

Series.div(other, level=None, fill_value=None, axis=0) [source] Floating division of series and other, element-wise (binary operator truediv). Equivalent to series / other, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other: Series or scalar value fill_value : None or float value, default None (NaN) Fill missing (NaN) values with this value. If both Series are missing, the result will be missing level : int or name Broadcast across a lev

Panel.ne(other, axis=None) [source] Wrapper for comparison method ne

DatetimeIndex.inferred_type

MultiIndex.summary(name=None) [source]

CategoricalIndex.itemsize return the size of the dtype of the item of the underlying data

CategoricalIndex.is_all_dates = None