pandas provides various facilities for easily combining together Series, DataFrame, and Panel objects with various kinds of set logic for the indexes and relational algebra functionality in the case of join / merge-type operations. Concatenating objects The concat function (in the main pandas namespace) does all of the heavy lifting of performing concatenation operations along an axis while performing optional set logic (union or intersection) of the indexes (if any) on the other axes. Note t

class pandas.MultiIndex [source] A multi-level, or hierarchical, index object for pandas objects Parameters: levels : sequence of arrays The unique labels for each level labels : sequence of arrays Integers for each level designating which label at each location sortorder : optional int Level of sortedness (must be lexicographically sorted by that level) names : optional sequence of objects Names for each of the index levels. (name is accepted for compat) copy : boolean, default Fa

Panel4D.to_dense() [source] Return dense representation of NDFrame (as opposed to sparse)

Panel.ndim Number of axes / array dimensions

DatetimeIndex.is_year_end Logical indicating if last day of year (defined by frequency)

MultiIndex.flags

pandas.read_excel(io, sheetname=0, header=0, skiprows=None, skip_footer=0, index_col=None, names=None, parse_cols=None, parse_dates=False, date_parser=None, na_values=None, thousands=None, convert_float=True, has_index_names=None, converters=None, true_values=None, false_values=None, engine=None, squeeze=False, **kwds) [source] Read an Excel table into a pandas DataFrame Parameters: io : string, path object (pathlib.Path or py._path.local.LocalPath), file-like object, pandas ExcelFile, or

pandas.to_datetime(*args, **kwargs) [source] Convert argument to datetime. Parameters: arg : string, datetime, list, tuple, 1-d array, Series errors : {?ignore?, ?raise?, ?coerce?}, default ?raise? If ?raise?, then invalid parsing will raise an exception If ?coerce?, then invalid parsing will be set as NaT If ?ignore?, then invalid parsing will return the input dayfirst : boolean, default False Specify a date parse order if arg is str or its list-likes. If True, parses dates with the d

Series.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

MultiIndex.get_indexer_for(target, **kwargs) [source] guaranteed return of an indexer even when non-unique