本文介绍了根据日期将数据框拆分为两个的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我有这样的 1000 行数据集
I have dataset with 1000 rows like this
Date, Cost, Quantity(in ton), Source, Unloading Station
01/10/2015, 7, 5.416, XYZ, ABC
我想根据日期拆分数据.例如截至日期 20.12.2016 是训练数据，之后是测试数据.
i want to split the data on the base of date. For e.g. till date 20.12.2016 is a training data and after that it is test data.
我应该如何拆分?有可能吗?
How should i split? Is it possible?
推荐答案
您可以通过将列转换为 pandas to_datetime 类型并将其设置为索引来轻松地做到这一点.
You can easily do that by converting your column to pandas to_datetime type and set it as index.
import pandas as pd
df['Date'] = pd.to_datetime(df['Date'])
df = df.set_index(df['Date'])
df = df.sort_index()
一旦你有了这种格式的数据，你可以简单地使用日期作为索引来创建分区，如下所示:
Once you have your data in this format, you can simply use date as index for creating partition as follows:
# create train test partition
train = df['2015-01-10':'2016-12-20']
test = df['2016-12-21':]
print('Train Dataset:',train.shape)
print('Test Dataset:',test.shape)
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