Numpy实践_时间日期和时间增量
文章目录
- datetime64 基础
- datetime64 和 timedelta64 运算
- datetime64 的应用
datetime64 基础
1.从字符串创建 datetime64 类型时，默认情况下，numpy 会根据字符串自动选择对应的单位。
import numpy as np
a = np.datetime64('2020-03-01')
print(a, a.dtype) # 2020-03-01 datetime64[D]
a = np.datetime64('2020-03')
print(a, a.dtype) # 2020-03 datetime64[M]
a = np.datetime64('2020-03-08 20:00:05')
print(a, a.dtype) # 2020-03-08T20:00:05 datetime64[s]
a = np.datetime64('2020-03-08 20:00')
print(a, a.dtype) # 2020-03-08T20:00 datetime64[m]
a = np.datetime64('2020-03-08 20')
print(a, a.dtype) # 2020-03-08T20 datetime64[h]
2.从字符串创建 datetime64 类型时，可以强制指定使用的单位。
import numpy as np
a = np.datetime64('2020-03', 'D')
print(a, a.dtype) # 2020-03-01 datetime64[D]
a = np.datetime64('2020-03', 'Y')
print(a, a.dtype) # 2020 datetime64[Y]
print(np.datetime64('2020-03') == np.datetime64('2020-03-01')) # True
print(np.datetime64('2020-03') == np.datetime64('2020-03-02')) #False
3.从字符串创建 datetime64 数组时，如果单位不统一，则一律转化成其中最小的单位。
import numpy as np
a = np.array(['2020-03', '2020-03-08', '2020-03-08 20:00'], dtype='datetime64')
print(a, a.dtype)
# ['2020-03-01T00:00' '2020-03-08T00:00' '2020-03-08T20:00'] datetime64[m]
4.使用arange()创建 datetime64 数组，用于生成日期范围。
import numpy as np
a = np.arange('2020-08-01', '2020-08-10', dtype=np.datetime64)
print(a)
# ['2020-08-01' '2020-08-02' '2020-08-03' '2020-08-04' '2020-08-05'
# '2020-08-06' '2020-08-07' '2020-08-08' '2020-08-09']
print(a.dtype) # datetime64[D]
a = np.arange('2020-08-01 20:00', '2020-08-10', dtype=np.datetime64)
print(a)
# ['2020-08-01T20:00' '2020-08-01T20:01' '2020-08-01T20:02' ...
# '2020-08-09T23:57' '2020-08-09T23:58' '2020-08-09T23:59']
print(a.dtype) # datetime64[m]
a = np.arange('2020-05', '2020-12', dtype=np.datetime64)
print(a)
# ['2020-05' '2020-06' '2020-07' '2020-08' '2020-09' '2020-10' '2020-11']
print(a.dtype) # datetime64[M]
datetime64 和 timedelta64 运算
1.timedelta64 表示两个 datetime64 之间的差。timedelta64 也是带单位的，并且和相减运算中的两个 datetime64 中的较小的单位保持一致。
import numpy as np
a = np.datetime64('2020-03-08') - np.datetime64('2020-03-07')
b = np.datetime64('2020-03-08') - np.datetime64('2020-03-07 08:00')
c = np.datetime64('2020-03-08') - np.datetime64('2020-03-07 23:00', 'D')
print(a, a.dtype) # 1 days timedelta64[D]
print(b, b.dtype) # 956178240 minutes timedelta64[m]
print(c, c.dtype) # 1 days timedelta64[D]
a = np.datetime64('2020-03') + np.timedelta64(20, 'D')
b = np.datetime64('2020-06-15 00:00') + np.timedelta64(12, 'h')
print(a, a.dtype) # 2020-03-21 datetime64[D]
print(b, b.dtype) # 2020-06-15T12:00 datetime64[m]
2.生成 timedelta64时，要注意年（‘Y’）和月（‘M’）这两个单位无法和其它单位进行运算（一年有几天？一个月有几个小时？这些都是不确定的）。
import numpy as np
a = np.timedelta64(1, 'Y')
b = np.timedelta64(a, 'M')
print(a) # 1 years
print(b) # 12 months
c = np.timedelta64(1, 'h')
d = np.timedelta64(c, 'm')
print(c) # 1 hours
print(d) # 60 minutes
print(np.timedelta64(a, 'D'))
# TypeError: Cannot cast NumPy timedelta64 scalar from metadata [Y] to [D] according to the rule 'same_kind'
print(np.timedelta64(b, 'D'))
# TypeError: Cannot cast NumPy timedelta64 scalar from metadata [M] to [D] according to the rule 'same_kind'
3.timedelta64 的运算。
import numpy as np
a = np.timedelta64(1, 'Y')
b = np.timedelta64(6, 'M')
c = np.timedelta64(1, 'W')
d = np.timedelta64(1, 'D')
e = np.timedelta64(10, 'D')
print(a) # 1 years
print(b) # 6 months
print(a + b) # 18 months
print(a - b) # 6 months
print(2 * a) # 2 years
print(a / b) # 2.0
print(c / d) # 7.0
print(c % e) # 7 days
4.numpy.datetime64 与 datetime.datetime 相互转换
import numpy as np
import datetime
dt = datetime.datetime(year=2020, month=6, day=1, hour=20, minute=5, second=30)
dt64 = np.datetime64(dt, 's')
print(dt64, dt64.dtype)
# 2020-06-01T20:05:30 datetime64[s]
dt2 = dt64.astype(datetime.datetime)
print(dt2, type(dt2))
# 2020-06-01 20:05:30 <class 'datetime.datetime'>
datetime64 的应用
1.将指定的偏移量应用于工作日，单位天（‘D’）。计算下一个工作日，如果当前日期为非工作日，默认报错。可以指定 forward 或 backward 规则来避免报错。（一个是向前取第一个有效的工作日，一个是向后取第一个有效的工作日）
import numpy as np
# 2020-07-10 星期五
a = np.busday_offset('2020-07-10', offsets=1)
print(a) # 2020-07-13
#a = np.busday_offset('2020-07-11', offsets=1)
#print(a)
# ValueError: Non-business day date in busday_offset
a = np.busday_offset('2020-07-11', offsets=0, roll='forward')
b = np.busday_offset('2020-07-11', offsets=0, roll='backward')
print(a) # 2020-07-13
print(b) # 2020-07-10
a = np.busday_offset('2020-07-11', offsets=1, roll='forward')
b = np.busday_offset('2020-07-11', offsets=1, roll='backward')
print(a) # 2020-07-14
print(b) # 2020-07-13
2.返回指定日期是否是工作日。
import numpy as np
# 2020-07-10 星期五
a = np.is_busday('2020-07-10')
b = np.is_busday('2020-07-11')
print(a) # True
print(b) # False
3.统计一个 datetime64[D] 数组中的工作日天数。
import numpy as np
# 2020-07-10 星期五
begindates = np.datetime64('2020-07-10')
enddates = np.datetime64('2020-07-20')
a = np.arange(begindates, enddates, dtype='datetime64')
b = np.count_nonzero(np.is_busday(a))
print(a)
# ['2020-07-10' '2020-07-11' '2020-07-12' '2020-07-13' '2020-07-14'
# '2020-07-15' '2020-07-16' '2020-07-17' '2020-07-18' '2020-07-19']
print(b) # 6
4.自定义周掩码值，即指定一周中哪些星期是工作日。
import numpy as np
# 2020-07-10 星期五
a = np.is_busday('2020-07-10', weekmask=[1, 1, 1, 1, 1, 0, 0])
b = np.is_busday('2020-07-10', weekmask=[1, 1, 1, 1, 0, 0, 1])
print(a) # True
print(b) # False
5.返回两个日期之间的工作日数量。
import numpy as np
# 2020-07-10 星期五
begindates = np.datetime64('2020-07-10')
enddates = np.datetime64('2020-07-20')
a = np.busday_count(begindates, enddates)
b = np.busday_count(enddates, begindates)
print(a) # 6
print(b) # -6
参考：阿里云天池