Pandas的时间序列Period,period_range---详解（29）

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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：

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 

本文标签： 序列详解时间pandasperiodrange