python - 使用 pandas 为系列分配时间戳值会创建一个 int 而不是

Question

在 Python 中， Pandas :

g = pd.Series(dict(a = 5, b =datetime(2018, 1,1)))
g['datetime'] = pd.Timestamp('2018-01-02')

g 返回:

a                             5
b           2018-01-01 00:00:00
datetime    1514851200000000000
dtype: object

任何人都知道为什么时间戳在这里转换为它的 int 值，以及如何避免这个问题并正确地将时间戳附加到系列？

Answer 1

我同意@MrE，他说:

I think it makes sense: 5 is not a datetime object, so pandas is parsing the data and find that you have both a number and a datetime object, and it parses both as 'object' string, because the dtype needs to be consistent across all data in the Series. The string representation of a datetime is the date string, not timestamp. When you then add to it, you can modify the dtype of a cell

我真的同意，它必须找到一个 dtype 并找到 int，如果你删除 'a' 索引，它就会工作(这基本上是在检查以上内容是否属实):

g = pd.Series(dict(b =datetime(2018, 1,1)))
g['datetime'] = pd.Timestamp('2018-01-02')
print(g)

输出:

b          2018-01-01
datetime   2018-01-02
dtype: datetime64[ns]

原来如此。

解决问题:

只需在最后添加一行:

g['datetime']=pd.to_datetime(g['datetime'])

现在:

print(g)

是:

a                             5
b           2018-01-01 00:00:00
datetime    2018-01-02 00:00:00
dtype: object