eland.groupby.DataFrameGroupBy.agg¶
-
DataFrameGroupBy.agg(func: Union[str, List[str]], numeric_only: Optional[bool] = False) → pd.DataFrame¶ Used to groupby and aggregate
- Parameters
- func:
Functions to use for aggregating the data.
Accepted combinations are: - function - list of functions
- numeric_only: {True, False, None} Default is None
Which datatype to be returned - True: returns all values with float64, NaN/NaT are ignored. - False: returns all values with float64. - None: returns all values with default datatype.
- Returns
- pandas.DataFrame
aggregation value for each numeric column of each group
Examples
>>> df = ed.DataFrame( ... "localhost", "flights", ... columns=["AvgTicketPrice", "Cancelled", "dayOfWeek", "DestCountry"] ... ) >>> df.groupby("DestCountry").aggregate(["min", "max"]) # doctest: +NORMALIZE_WHITESPACE AvgTicketPrice ... dayOfWeek min max ... min max DestCountry ... AE 110.799911 1126.148682 ... 0 6 AR 125.589394 1199.642822 ... 0 6 AT 100.020531 1181.835815 ... 0 6 AU 102.294312 1197.632690 ... 0 6 CA 100.557251 1198.852539 ... 0 6 ... ... ... ... ... .. RU 101.004005 1196.742310 ... 0 6 SE 102.877190 1198.621582 ... 0 6 TR 142.876465 855.935547 ... 0 6 US 100.145966 1199.729004 ... 0 6 ZA 102.002663 1196.186157 ... 0 6 <BLANKLINE> [32 rows x 6 columns]