我需要在单独的函数中从熊猫框架值转换日期:
def myfunc(lat, lon, when):
ts = (when - np.datetime64('1970-01-01T00:00:00Z','s')) / np.timedelta64(1, 's')
date = datetime.datetime.utcfromtimestamp(ts)
print("Numpy date= ", when, " Python date= ", date)
return float(90) - next_func(lat, lon, date)
调用此功能:
new_df['new_column'] = np.vectorize(my_func)(lat, lon, new_df['datetime(LT)'])
但是它会引发错误:
ufunc subtract cannot use operands with types dtype('int64') and dtype('<M8[s]')
如何将numpy datetime64 [ns]转换为python datetime?
答案 0 :(得分:1)
我想知道您是否需要所有这些转换工作。在正确的时间单位下,datetime64
可以直接产生一个datetime
对象。
我不确定您的when
变量,但是我们假设它来自pandas
,类似于DatetimeIndex
:
In [56]: time = pandas.date_range('6/28/2013', periods=5, freq='5D')
In [57]: time
Out[57]:
DatetimeIndex(['2013-06-28', '2013-07-03', '2013-07-08', '2013-07-13',
'2013-07-18'],
dtype='datetime64[ns]', freq='5D')
等效的numpy数组
In [58]: time.values
Out[58]:
array(['2013-06-28T00:00:00.000000000', '2013-07-03T00:00:00.000000000',
'2013-07-08T00:00:00.000000000', '2013-07-13T00:00:00.000000000',
'2013-07-18T00:00:00.000000000'], dtype='datetime64[ns]')
In [59]: time.values.tolist()
Out[59]:
[1372377600000000000,
1372809600000000000,
1373241600000000000,
1373673600000000000,
1374105600000000000]
对于[ns]
,结果是一个大整数,某种形式的“时间戳”。但是,如果我将时间单位转换为秒,甚至是微秒(美国),则为
In [60]: time.values.astype('datetime64[s]')
Out[60]:
array(['2013-06-28T00:00:00', '2013-07-03T00:00:00',
'2013-07-08T00:00:00', '2013-07-13T00:00:00',
'2013-07-18T00:00:00'], dtype='datetime64[s]')
In [61]: time.values.astype('datetime64[s]').tolist()
Out[61]:
[datetime.datetime(2013, 6, 28, 0, 0),
datetime.datetime(2013, 7, 3, 0, 0),
datetime.datetime(2013, 7, 8, 0, 0),
datetime.datetime(2013, 7, 13, 0, 0),
datetime.datetime(2013, 7, 18, 0, 0)]
结果是datetime
个对象的列表。
答案 1 :(得分:1)
我更喜欢这种解决方法,因为有时np.datetime64具有不同的分辨率
def ___convert_to_datetime(d):
return datetime.strptime(np.datetime_as_string(d,unit='s'), '%Y-%m-%dT%H:%M:%S')
获取时间戳
def ___convert_to_ts(d):
return datetime.strptime(np.datetime_as_string(d,unit='s'), '%Y-%m-%dT%H:%M:%S').timestamp()
例如
import numpy as np
from datetime import datetime
def ___convert_to_datetime(d):
return datetime.strptime(np.datetime_as_string(d,unit='s'), '%Y-%m-%dT%H:%M:%S')
def ___convert_to_ts(d):
return datetime.strptime(np.datetime_as_string(d,unit='s'), '%Y-%m-%dT%H:%M:%S').timestamp()
print(___convert_to_datetime(np.datetime64('2005-02-25')))
my_ns_date = np.datetime64('2009') + np.timedelta64(20, 'ns')
print(my_ns_date)
print(___convert_to_datetime(my_ns_date))
输出将为
2005-02-25 00:00:00
2009-01-01T00:00:00.000000020
2009-01-01 00:00:00
答案 2 :(得分:0)
def myfunc(lat, lon, when):
ts = (when - np.datetime64('1970-01-01T00:00:00Z','s')) / np.timedelta64(1, 's')
date = datetime.utcfromtimestamp(ts)
print("Numpy date= ", when, " Python date= ", date)
return float(90) - next_func(lat, lon, date)
尝试此代码
要将numpy datetime64 [ns]转换为python datetime,只需尝试以下代码段
from datetime import datetime
datetime.utcfromtimestamp('your_time_stamp')