我有一些数据，我需要计算车辆行驶的公里数，而另一个条件为真。
我可能问错了问题，可能有一个明显的方法可以做到这一点，但不幸的是我没能找到它。 这里有两个问题，希望没问题，因为它是相关的。
所以我想做的是添加一个系列，用最后已知的状态填充行。 因此，如果车辆 1 打开左前窗，我会将系列设置为 True，直到 window 再次关闭。 然后我会以某种方式(我也没有弄清楚)计算车辆 1 在左前窗打开时行驶的公里数。
然后我会对右窗和所有车辆执行相同的操作。
下面是数据的例子，
import pandas as pd
matrix = [(1, 'Front Left Window Open', True),
(2, 'Engine Started', True),
(3, 'Engine Started', True),
(4, 'Front Left Window Open', True),
(1, 'Engine Started', True),
(2, 'Engine Started', True),
(3, 'Engine Started', True),
(1, 'Odometer', 254),
(1, 'Engine Started', True),
(2, 'Engine Started', True),
(3, 'Engine Started', True),
(1, 'Front Right Window Open', True),
(1, 'Engine Started', True),
(1, 'Odometer', 257),
(3, 'Engine Started', True),
(1, 'Odometer', 259),
(1, 'Front Left Window Open', False),
(1, 'Engine Started', True),
(1, 'Odometer', 261),
(3, 'Engine Started', True),
(1, 'Front Left Window Open', True),
(1, 'Odometer', 265),
]
# Create a DataFrame object
dfObj = pd.DataFrame(matrix, columns=['Vehicle', 'Event', 'State'])
print (dfObj)
state = [True,True,True,True,True,True, True, True, True, True, True, True, True, True, True,True, False, False, False, False, True, True]
dfObj["FrontLeftWindowOpen"] = state
print ("\n\n\n")
print (dfObj[dfObj.Vehicle == 1])
print ("\n\n\n")
matrix = [(1, 'Front Left Window Open', 5),
(1, 'Front Right Window Open', 2),
(2, 'Front Left Window Open', 15),
(2, 'Front Right Window Open', 12)
]
# Create a DataFrame object
dfObj = pd.DataFrame(matrix, columns=['Vehicle', 'state', 'km'])
print (dfObj)
输出
Vehicle Event State
0 1 Front Left Window Open True
1 2 Engine Started True
2 3 Engine Started True
3 4 Front Left Window Open True
4 1 Engine Started True
5 2 Engine Started True
6 3 Engine Started True
7 1 Odometer 254
8 1 Engine Started True
9 2 Engine Started True
10 3 Engine Started True
11 1 Front Right Window Open True
12 1 Engine Started True
13 1 Odometer 257
14 3 Engine Started True
15 1 Odometer 259
16 1 Front Left Window Open False
17 1 Engine Started True
18 1 Odometer 261
19 3 Engine Started True
20 1 Front Left Window Open True
21 1 Odometer 265
添加了一个包含左前窗口当前状态的列
Vehicle Event State FrontLeftWindowOpen
0 1 Front Left Window Open True True
4 1 Engine Started True True
7 1 Odometer 254 True
8 1 Engine Started True True
11 1 Front Right Window Open True True
12 1 Engine Started True True
13 1 Odometer 257 True
15 1 Odometer 259 True
16 1 Front Left Window Open False False
17 1 Engine Started True False
18 1 Odometer 261 False
20 1 Front Left Window Open True True
21 1 Odometer 265 True
最后计算所有车辆的里程表以及它们在右侧或左侧打开 window 时行驶的公里数。
Vehicle state km
0 1 Front Left Window Open 5
1 1 Front Right Window Open 2
2 2 Front Left Window Open 15
3 2 Front Right Window Open 12
最佳答案
使用.where 和正向填充:
df['LeftWindowOpen'] = df.State.where(df.Event.eq('Front Left Window Open')).ffill()
Vehicle Event State FrontLeftWindowOpen
0 1 Front Left Window Open True True
1 2 Engine Started True True
2 3 Engine Started True True
3 4 Front Left Window Open True True
4 1 Engine Started True True
5 2 Engine Started True True
6 3 Engine Started True True
7 1 Odometer 254 True
8 1 Engine Started True True
9 2 Engine Started True True
10 3 Engine Started True True
11 1 Front Right Window Open True True
12 1 Engine Started True True
13 1 Odometer 257 True
14 3 Engine Started True True
15 1 Odometer 259 True
16 1 Front Left Window Open False False
17 1 Engine Started True False
18 1 Odometer 261 False
19 3 Engine Started True False
20 1 Front Left Window Open True True
21 1 Odometer 265 True
对于每辆车的分析，您可以使用 groupby 和相同的逻辑
df.groupby('Vehicle')[['Event', 'State']]\
.apply(lambda s: s['State'].where(s['Event'].eq('Front Left Window Open'))\
.reindex(df.index)\
.ffill()
)
State 0 1 2 3 4 ... 17 18 19 20 21
Vehicle ...
1 True True True True True ... False False False True True
2 NaN NaN NaN NaN NaN ... NaN NaN NaN NaN NaN
3 NaN NaN NaN NaN NaN ... NaN NaN NaN NaN NaN
4 NaN NaN NaN True True ... True True True True True
关于python - Pandas :如果条件为真，则在 2 个值之间填充列，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/58102419/