如何使用.query()通过时间戳函数过滤Pandas数据帧 [英] How to filter a Pandas dataframe by timestamp functon using .query()

问题描述

我正在尝试按日期(今天和昨天)过滤Pandas df.为了自动化，我希望使用时间戳功能进行过滤.在R中这是非常无缝的:

I am trying to filter a Pandas df by dates (today and yesterday). For automation purposes I wish to filter using a timestamp function. This is pretty seamless in R:

df %>% 
  filter(date >= today() - 1)

但是，到目前为止，我在熊猫中复制的尝试并未取得任何成功:昨天结果很好，但是.query()无法识别它?

However, my attempts to replicate in Pandas are not reaching any success so far: Yesterday comes out fine, but .query() doesnt recognise it?

yesterday = (date.today() - timedelta(days=6)).strftime('%Y-%m-%d')
df.\
   query('date >= yesterday')

理想情况下，我正在寻找所有包含以下内容的东西:

Ideally I am seeking something all encompassing like:

df.\
   query('date >= (date.today() - timedelta(days=6)).strftime('%Y-%m-%d')')

推荐答案

尝试: df.query('date> = @yesterday').您需要 @ ，以便熊猫识别出它是一个变量.

Try: df.query('date >= @yesterday'). You need @ so pandas recognizes it's a variable.

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