Pandas的时间序列Period,period

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Period

Pandas的Period可以定义一个时期，或者说具体的一个时段。有这个时段的起始时间start_time、终止时间end_time等属性信息，其参数freq和之前的date_range里的freq参数类似，可以取'S'、'D'等。

import pandas as pd

p = pd.Period('2018-12-15', freq = "A")

print p.start_time, p.end_time, p + 1, p

print pd.Period('2013-1-9 11:22:33', freq='S') + 1

print pd.Period('2013-1-9 11:22:33', freq='T') + 1

print pd.Period('2013-1-9 11:22:33', freq='H') + 1

print pd.Period('2013-1-9 11:22:33', freq='D') + 1

print pd.Period('2013-1-9 11:22:33', freq='M') + 1

print pd.Period('2013-1-9 11:22:33', freq='A') + 1

程序的执行结果如下：

2018-12-01 00:00:00 2018-12-31 23:59:59.999999999 2019-01

2018-01-01 00:00:00 2018-12-31 23:59:59.999999999 2019 2018

2013-01-09 11:22:34 # S 秒

2013-01-09 11:23 # T 分

2013-01-09 12:00 # H 时

2013-01-10 # D 天

2013-02 # M 月

2014 # A 年

Period数据类型的属性有：

dayGet day of the month that a Period falls on.dayofweekReturn the day of the week.dayofyearReturn the day of the year.days_in_monthGet the total number of days in the month that this period falls on.daysinmonthGet the total number of days of the month that the Period falls in.hourGet the hour of the day component of the Period.minuteGet minute of the hour component of the Period.secondGet the second component of the Period.start_timeGet the Timestamp for the start of the period.weekGet the week of the year on the given Period.

下面可以编写程序使用一下这些属性。

import pandas as pd

att = ["S", "T", "H", "D", "M", "A"]

for a in att:

p = pd.Period('2018-12-19 11:22:33', freq= a)

print "freq =", a

print "Start from:", p.start_time, " End at:", p.end_time

print "Day",p.day, "Dayofweek", p.dayofweek,"dayofyear", p.dayofyear,"daysinmonth", p.daysinmonth

print "hour", p.hour, "minute", p.minute, "second", p.second, "\n"

程序的执行结果：

freq = S

Start from: 2018-12-19 11:22:33 End at: 2018-12-19 11:22:33.999999999

Day 19 Dayofweek 2 dayofyear 353 daysinmonth 31

hour 11 minute 22 second 33

freq = T

Start from: 2018-12-19 11:22:00 End at: 2018-12-19 11:22:59.999999999

Day 19 Dayofweek 2 dayofyear 353 daysinmonth 31

hour 11 minute 22 second 0

freq = H

Start from: 2018-12-19 11:00:00 End at: 2018-12-19 11:59:59.999999999

Day 19 Dayofweek 2 dayofyear 353 daysinmonth 31

hour 11 minute 0 second 0

freq = D

Start from: 2018-12-19 00:00:00 End at: 2018-12-19 23:59:59.999999999

Day 19 Dayofweek 2 dayofyear 353 daysinmonth 31

hour 0 minute 0 second 0

freq = M

Start from: 2018-12-01 00:00:00 End at: 2018-12-31 23:59:59.999999999

Day 31 Dayofweek 0 dayofyear 365 daysinmonth 31

hour 0 minute 0 second 0

freq = A

Start from: 2018-01-01 00:00:00 End at: 2018-12-31 23:59:59.999999999

Day 31 Dayofweek 0 dayofyear 365 daysinmonth 31

hour 0 minute 0 second 0

 period_range

可以通过pandas的period_range函数产生时间序列作为series的index。

import pandas as pd

import numpy as np

att = ["S", "T", "H", "D", "M", "A"]

vi = np.random.randn(5)

for a in att:

pi = pd.period_range('2018-12-19 11:22:33', periods = 5, freq= a)

ts = pd.Series(vi, index = pi)

print ts, "\n"

程序的执行结果：

2018-12-19 11:22:33 -0.275161

2018-12-19 11:22:34 -0.763390

2018-12-19 11:22:35 -2.012351

2018-12-19 11:22:36 -1.126492

2018-12-19 11:22:37 0.843842

Freq: S, dtype: float64

2018-12-19 11:22 -0.275161

2018-12-19 11:23 -0.763390

2018-12-19 11:24 -2.012351

2018-12-19 11:25 -1.126492

2018-12-19 11:26 0.843842

Freq: T, dtype: float64

2018-12-19 11:00 -0.275161

2018-12-19 12:00 -0.763390

2018-12-19 13:00 -2.012351

2018-12-19 14:00 -1.126492

2018-12-19 15:00 0.843842

Freq: H, dtype: float64

2018-12-19 -0.275161

2018-12-20 -0.763390

2018-12-21 -2.012351

2018-12-22 -1.126492

2018-12-23 0.843842

Freq: D, dtype: float64

2018-12 -0.275161

2019-01 -0.763390

2019-02 -2.012351

2019-03 -1.126492

2019-04 0.843842

Freq: M, dtype: float64

2018 -0.275161

2019 -0.763390

2020 -2.012351

2021 -1.126492

2022 0.843842

Freq: A-DEC, dtype: float64

网址：Pandas的时间序列Period,period https://www.yuejiaxmz.com/news/view/239609

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