pandas 从 Python 中的 Dataframe 过滤多个条件
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Filtering multiple conditions from a Dataframe in Python
提问by Deepak M
I want to filter out data from a dataframe using multiple conditions using multiple columns. I tried doing so like this:
我想使用多列使用多个条件从数据框中过滤掉数据。我试着这样做：
arrival_delayed_weather = [[[flight_data_finalcopy["ArrDelay"] > 0]] & [[flight_data_finalcopy["WeatherDelay"]>0]]]
arrival_delayed_weather_filter = arrival_delayed_weather[["UniqueCarrier", "AirlineID"]]
print arrival_delayed_weather_filter
However I get this error message:
但是我收到此错误消息：
TypeError: unsupported operand type(s) for &: 'list' and 'list'
类型错误：& 的操作数类型不受支持：“列表”和“列表”
How do I solve this?
我该如何解决这个问题？
Thanks in advance
提前致谢
回答by jezrael
You need ()instead []:
您需要()改为[]：
arrival_delayed_weather = (flight_data_finalcopy["ArrDelay"] > 0) &
(flight_data_finalcopy["WeatherDelay"]>0)
But it seems you need ixfor selecting columns UniqueCarrierand AirlineIDby mask- a bit modified boolean indexing:
但似乎你需要ix的选择列UniqueCarrier，并AirlineID通过mask-有点修改boolean indexing：
mask = (flight_data_finalcopy["ArrDelay"] > 0) &
(flight_data_finalcopy["WeatherDelay"]>0)
arrival_delayed_weather_filter=flight_data_finalcopy.ix[mask, ["UniqueCarrier","AirlineID"]]
Sample:
样本：
flight_data_finalcopy = pd.DataFrame({'ArrDelay':[0,2,3],
'WeatherDelay':[0,0,6],
'UniqueCarrier':['s','a','w'],
'AirlineID':[1515,3546,5456]})
print (flight_data_finalcopy)
AirlineID ArrDelay UniqueCarrier WeatherDelay
0 1515 0 s 0
1 3546 2 a 0
2 5456 3 w 6
mask = (flight_data_finalcopy["ArrDelay"] > 0) & (flight_data_finalcopy["WeatherDelay"]>0)
print (mask)
0 False
1 False
2 True
dtype: bool
arrival_delayed_weather_filter=flight_data_finalcopy.ix[mask, ["UniqueCarrier","AirlineID"]]
print (arrival_delayed_weather_filter)
UniqueCarrier AirlineID
2 w 5456
