eland.groupby.DataFrameGroupBy.mad¶
-
DataFrameGroupBy.mad(numeric_only: bool = True) → pd.DataFrame¶ Compute the median absolute deviation value for each group.
- Parameters
- numeric_only: {True, False, None} Default is True
Which datatype to be returned - True: Returns all values as float64, NaN/NaT values are removed - None: Returns all values as the same dtype where possible, NaN/NaT are removed - False: Returns all values as the same dtype where possible, NaN/NaT are preserved
- Returns
- pandas.DataFrame
median absolute deviation value for each numeric column of each group
See also
Examples
>>> df = ed.DataFrame( ... "localhost", "flights", ... columns=["AvgTicketPrice", "Cancelled", "dayOfWeek", "timestamp", "DestCountry"] ... ) >>> df.groupby("DestCountry").mad() # doctest: +SKIP AvgTicketPrice Cancelled dayOfWeek DestCountry AE 233.697174 NaN 1.5 AR 189.250061 NaN 2.0 AT 195.823669 NaN 2.0 AU 202.539764 NaN 2.0 CA 203.344696 NaN 2.0 ... ... ... ... RU 206.431702 NaN 2.0 SE 178.658447 NaN 2.0 TR 221.863434 NaN 1.0 US 228.461365 NaN 2.0 ZA 192.162842 NaN 2.0 <BLANKLINE> [32 rows x 3 columns]