您可以使用boolean indexing
与条件,其中由isnull
检查NaT
值创建to_datetime
与参数errors='coerce'
- 它创造NaT
哪里都是无效的日期时间:
allData1 = allData[pd.to_datetime(allData['Col1'], errors='coerce').isnull()]
样品:
allData = pd.DataFrame({'Col1':['2015-01-03','a','2016-05-08'],
'B':[4,5,6],
'C':[7,8,9],
'D':[1,3,5],
'E':[5,3,6],
'F':[7,4,3]})
print (allData)
B C Col1 D E F
0 4 7 2015-01-03 1 5 7
1 5 8 a 3 3 4
2 6 9 2016-05-08 5 6 3
print (pd.to_datetime(allData['Col1'], errors='coerce'))
0 2015-01-03
1 NaT
2 2016-05-08
Name: Col1, dtype: datetime64[ns]
print (pd.to_datetime(allData['Col1'], errors='coerce').isnull())
0 False
1 True
2 False
Name: Col1, dtype: bool
allData1 = allData[pd.to_datetime(allData['Col1'], errors='coerce').isnull()]
print (allData1)
B C Col1 D E F
1 5 8 a 3 3 4
出于某种原因,如果一个错误被检测到,整列被制成NaT。有任何想法吗? ALLDATA [ 'GPS_DateTime'] = pd.to_datetime(ALLDATA [ 'GPS_DateTime'],错误= '要挟') errordata子= ALLDATA [ALLDATA [ 'GPS_DateTime']。ISNULL()] – user1035217
我认为你需要将其交换:'errorData = allData [allData ['GPS_DateTime']。isnull()]'仅用于检查,所以首先检查它,然后通过'allData ['GPS_DateTime'] = pd.to_datetime(allData ['GPS_DateTime' ],error ='coerce')' – jezrael
allData ['GPS_DateTime'] = pd.to_datetime(allData ['GPS_DateTime'],errors ='coerce')给出了整列NaT – user1035217