我正在尝试读取csv文件并将其转换为数据帧以用作时间序列。 csv文件属于这种类型:
#Date Time CO_T1_AHU.01_CC_CTRV_CHW__SIG_STAT
0 NaN NaN %
1 NaN NaN Cooling Coil Hydronic Valve Position
2 2014-01-01 00:00:00 0
3 2014-01-01 01:00:00 0
4 2014-01-01 02:00:00 0
5 2014-01-01 03:00:00 0
6 2014-01-01 04:00:00 0
我使用以下方式阅读文件:
df = pd.read_csv ('filepath/file.csv', sep=';', parse_dates = [[0,1]])
产生这个结果:
#Date_Time FCO_T1_AHU.01_CC_CTRV_CHW__SIG_STAT
0 nan nan %
1 nan nan Cooling Coil Hydronic Valve Position
2 2014-01-01 00:00:00 0
3 2014-01-01 01:00:00 0
4 2014-01-01 02:00:00 0
5 2014-01-01 03:00:00 0
6 2014-01-01 04:00:00 0
继续将字符串转换为datetime并将其用作索引:
pd.to_datetime(df.values[:,0])
df.set_index([df.columns[0]], inplace=True)
所以我明白了:
FCO_T1_AHU.01_CC_CTRV_CHW__SIG_STAT
#Date_Time
nan nan %
nan nan Cooling Coil Hydronic Valve Position
2014-01-01 00:00:00 0
2014-01-01 01:00:00 0
2014-01-01 02:00:00 0
2014-01-01 03:00:00 0
2014-01-01 04:00:00 0
但是,pd.to_datetime无法转换为datetime。有没有办法找出错误是什么?
非常感谢。 路易斯
答案 0 :(得分:1)
字符串条目' nan nan'无法使用to_datetime
进行转换,因此请使用空字符串替换它们,以便现在可以将它们转换为NaT
:
In [122]:
df['Date_Time'].replace('nan nan', '',inplace=True)
df
Out[122]:
Date_Time index CO_T1_AHU.01_CC_CTRV_CHW__SIG_STAT
0 0 %
1 1 Cooling Coil Hydronic Valve Position
2 2014-01-01 00:00:00 2 0
3 2014-01-01 01:00:00 3 0
4 2014-01-01 02:00:00 4 0
5 2014-01-01 03:00:00 5 0
6 2014-01-01 04:00:00 6 0
In [124]:
df['Date_Time'] = pd.to_datetime(df['Date_Time'])
df
Out[124]:
Date_Time index CO_T1_AHU.01_CC_CTRV_CHW__SIG_STAT
0 NaT 0 %
1 NaT 1 Cooling Coil Hydronic Valve Position
2 2014-01-01 00:00:00 2 0
3 2014-01-01 01:00:00 3 0
4 2014-01-01 02:00:00 4 0
5 2014-01-01 03:00:00 5 0
6 2014-01-01 04:00:00 6 0
<强>更新强>
实际上,如果您只是设置coerce=True
,那么转换正常:
df['Date_Time'] = pd.to_datetime(df['Date_Time'], coerce=True)