将Pandas DatetimeIndex转换为数字格式
我想将DataFrame中的DatetimeIndex转换为浮点格式,可以在我的模型中进行分析。有人告诉我该怎么做吗?我需要使用date2num()函数吗? 非常感谢!将Pandas DatetimeIndex转换为数字格式
转换为Timedelta
和dt.total_seconds
提取总秒数:
data = \
{'date': {0: pd.Timestamp('2013-01-01 00:00:00'),
1: pd.Timestamp('2013-01-02 00:00:00'),
2: pd.Timestamp('2013-01-03 00:00:00'),
3: pd.Timestamp('2013-01-04 00:00:00'),
4: pd.Timestamp('2013-01-05 00:00:00'),
5: pd.Timestamp('2013-01-06 00:00:00'),
6: pd.Timestamp('2013-01-07 00:00:00'),
7: pd.Timestamp('2013-01-08 00:00:00'),
8: pd.Timestamp('2013-01-09 00:00:00'),
9: pd.Timestamp('2013-01-10 00:00:00')}}
df = pd.DataFrame.from_dict(data)
df
date
0 2013-01-01
1 2013-01-02
2 2013-01-03
3 2013-01-04
4 2013-01-05
5 2013-01-06
6 2013-01-07
7 2013-01-08
8 2013-01-09
9 2013-01-10
pd.to_timedelta(df.date).dt.total_seconds()
0 1.356998e+09
1 1.357085e+09
2 1.357171e+09
3 1.357258e+09
4 1.357344e+09
5 1.357430e+09
6 1.357517e+09
7 1.357603e+09
8 1.357690e+09
9 1.357776e+09
Name: date, dtype: float64
或者,也许,数据会更有用,如int
类型:
pd.to_timedelta(df.date).dt.total_seconds().astype(int)
0 1356998400
1 1357084800
2 1357171200
3 1357257600
4 1357344000
5 1357430400
6 1357516800
7 1357603200
8 1357689600
9 1357776000
Name: date, dtype: int64
使用astype浮动也就是说,如果你有一个像
df = pd.DataFrame({'date': ['1998-03-01 00:00:01', '2001-04-01 00:00:01','1998-06-01 00:00:01','2001-08-01 00:00:01','2001-05-03 00:00:01','1994-03-01 00:00:01'] })
df['date'] = pd.to_datetime(df['date'])
df['x'] = list('abcdef')
df = df.set_index('date')
一个数据帧然后
df.index.values.astype(float)
array([ 8.88710401e+17, 9.86083201e+17, 8.96659201e+17,
9.96624001e+17, 9.88848001e+17, 7.62480001e+17])
pd.to_datetime(df.index.values.astype(float))
DatetimeIndex(['1998-03-01 00:00:01', '2001-04-01 00:00:01',
'1998-06-01 00:00:01', '2001-08-01 00:00:01',
'2001-05-03 00:00:01', '1994-03-01 00:00:01'],
dtype='datetime64[ns]', freq=None)
请注意自2017年以来的秒数为10e9,因此10e17不正确。请参阅https://stackoverflow.com/a/46502880/4909087并运行https://stackoverflow.com/questions/4548684/how-to-get-the-seconds-since-epoch-from-the-time-date- gmtime-in-py的输出 –
但是,当您将其转换回pd.to_datetime时,返回原始日期na – Dark
是的,但是我认为OP想要使用历元时间。我不知道astype给出了什么,但它看起来像一个错误?这绝对不是时代。 –
尝试df.date.values.astype(float)一次 – Dark
@Bharathshetty'不能从类似datetimelike [datetime64 [ns]]到[float64]' –
它为我工作。 – Dark