Код: Выделить всё
data (140631115432592), ndim: 2, size: 3947910, shape: (232230, 17)
VIN (1-10) object
County object
City object
State object
Postal Code float64
Model Year int64
Make object
Model object
Electric Vehicle Type object
Clean Alternative Fuel Vehicle (CAFV) Eligibility object
Electric Range float64
Base MSRP float64
Legislative District float64
DOL Vehicle ID int64
Vehicle Location object
Electric Utility object
2020 Census Tract float64
dtype: object
VIN (1-10) County City State Postal Code ... Legislative District DOL Vehicle ID Vehicle Location Electric Utility 2020 Census Tract
0 2T3YL4DV0E King Bellevue WA 98005.0 ... 41.0 186450183 POINT (-122.1621 47.64441) PUGET SOUND ENERGY INC||CITY OF TACOMA - (WA) 5.303302e+10
1 5YJ3E1EB6K King Bothell WA 98011.0 ... 1.0 478093654 POINT (-122.20563 47.76144) PUGET SOUND ENERGY INC||CITY OF TACOMA - (WA) 5.303302e+10
2 5UX43EU02S Thurston Olympia WA 98502.0 ... 35.0 274800718 POINT (-122.92333 47.03779) PUGET SOUND ENERGY INC 5.306701e+10
3 JTMAB3FV5R Thurston Olympia WA 98513.0 ... 2.0 260758165 POINT (-122.81754 46.98876) PUGET SOUND ENERGY INC 5.306701e+10
4 5YJYGDEE8M Yakima Selah WA 98942.0 ... 15.0 236581355 POINT (-120.53145 46.65405) PACIFICORP 5.307700e+10
< /code>
Фильтрация и группировка: < /p>
filt = (data["Model Year"] >= 2018) & (data["Electric Vehicle Type"] == "Battery Electric Vehicle (BEV)")
data = data[filt].groupby(["State", "Make"], sort=False, observed=True, as_index=False).agg( avg_electric_range=pd.NamedAgg(column="Electric Range", aggfunc="mean"), oldest_model_year=pd.NamedAgg(column="Model Year", aggfunc="min"))
< /code>
В настоящее время он дает следующую таблицу: < /p>
State Make avg_electric_range oldest_model_year
0 WA TESLA 52.143448 2018
1 WA NISSAN 60.051874 2018
Подробнее здесь: https://stackoverflow.com/questions/794 ... olumn-of-e