python - Pandas 在不应该返回 NaT 的情况下返回 NaT

Question

我的数据框是

time  NTCS001G002  NTCS001W005
0  2013-05-30 23:00:00          NaN          NaN
1  2013-06-30 23:00:00          249           60
2  2013-07-31 23:00:00          161            2
3  2013-09-01 23:00:00          151           11
4  2013-09-04 23:00:00           14            0
5  2013-10-01 23:00:00          162           64
6  2013-11-01 00:00:00          281          175
7  2013-12-03 00:00:00          482          168
8  2014-01-02 00:00:00          378          NaN
9  2014-01-03 00:00:00          NaN          NaN
10 2014-02-03 00:00:00          NaN          167
11 2014-03-03 00:00:00          502          167

当我迭代行时 对于索引，diffs.iterrows() 中的行: 打印“错误”，row.tolist()

[12 rows x 3 columns]
err [Timestamp('2013-05-30 23:00:00', tz=None), NaT, NaT]
err [Timestamp('2013-06-30 23:00:00', tz=None), 249.0, 60.0]
err [Timestamp('2013-07-31 23:00:00', tz=None), 161.0, 2.0]
err [Timestamp('2013-09-01 23:00:00', tz=None), 151.0, 11.0]
err [Timestamp('2013-09-04 23:00:00', tz=None), 14.0, 0.0]
err [Timestamp('2013-10-01 23:00:00', tz=None), 162.0, 64.0]
err [Timestamp('2013-11-01 00:00:00', tz=None), 281.0, 175.0]
err [Timestamp('2013-12-03 00:00:00', tz=None), 482.0, 168.0]
err [Timestamp('2014-01-02 00:00:00', tz=None), 378.0, nan]
err [Timestamp('2014-01-03 00:00:00', tz=None), NaT, NaT]
err [Timestamp('2014-02-03 00:00:00', tz=None), nan, 167.0]
err [Timestamp('2014-03-03 00:00:00', tz=None), 502.0, 167.0]

我不确定那些 NaT 是否是一个错误。我认为它们应该是 NaN能否让 Pandas 不返回 NaT，如果不能，我如何检查它们，因为我必须在列表中替换它们。

谢谢

Answer 1

原因是iterrows将每一行变成一个Series，并且这一行被强制转换为datetime64....

In [11]: pd.Series([pd.Timestamp('2014-01-03 00:00:00', tz=None), np.nan, np.nan])
Out[11]:
0   2014-01-03
1          NaT
2          NaT
dtype: datetime64[ns]