如何基于Python中的特定日期提取前两年的数据? [英] How to extract data from previous 2 years based on particular date in Python?

问题描述

我有一个csv文件，其中包含最近3年的时间序列月度数据.根据今天的日期，我只想读取前两年的数据来预测未来.

I have a csv file consisting of last 3 years of timeseries monthly data. Based on today's date, I would like to read only the previous 2 years of data for forecasting the future.

Data file example (has data from 01-01-15 to 31-10-19):  

    Date,Value
    01-01-17,2   
    01-02-17,5   
    01-03-17,8     
    01-04-17,4  
    01-05-17,2  
    01-06-17,9  
    01-07-17,8  
    01-08-17,7  
    01-09-17,5  
    01-10-17,1  
    01-11-17,2  
    01-12-17,3  
    01-01-18,5  
    01-02-18,6  
    01-03-18,8  
    01-04-18,2  
    01-05-18,5   
    01-06-18,6  

所需结果:
如果今天的日期是19年1月1日，我希望我的训练数据是17年1月1日至18年12月31日之间的数据.

Desired result:
If today's date is 01/01/19, I want my training data to be data from 01/01/17 - 31/12/18.

我尝试过:
df [df ['date']>(pd.to_datetime('2019-01-01'，format ='％Y-％m-％d')-relativedelta(years = 2))]

但是，我正在从01-01-17到31-10-19(最后一条记录)获取数据，而不是从01-01-17到31-12-18.

However, I am getting data from 01-01-17 to 31-10-19(last record) instead of from 01-01-17 to 31-12-18.

推荐答案

您可以尝试以下

>>> from dateutil.relativedelta import relativedelta
>>> df[df.Date > datetime.now() - relativedelta(years=2)]
         Date  Value
12 2018-01-01      5
13 2018-01-02      6
14 2018-01-03      8
15 2018-01-04      2
16 2018-01-05      5
17 2018-01-06      6

更新

>>> from dateutil.relativedelta import relativedelta
>>> from datetime import date

>>> start_date = pd.Timestamp(datetime.now() - relativedelta(years=2))
>>> end_date = pd.Timestamp(date(date.today().year-1, 12, 31))

>>> df[(df.Date >= start_date) & (df.Date <= end_date)]

---

         Date  Value
12 2018-01-01      5
13 2018-01-02      6
14 2018-01-03      8
15 2018-01-04      2
16 2018-01-05      5
17 2018-01-06      6

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