如何遍历 Pandas 组并检查每个组中是否有一个字符串? [英] How do I iterate through a pandas group and check to see if a string is in each group?

问题描述

我有一个 Pandas 数据框，其中包含特定日期的一堆记录.我需要按日期对它们进行分组，并检查第二天是否有前一天的记录，特别是我需要输出哪些记录被删除.

I have a pandas dataframe with a bunch of records on certain dates. I need to group them by date, and do a check to see if the next day has records that are also in the prior day, specifically I need to output what records were deleted.

这是一个示例数据集:

Date        Item
20160101    apple
20160101    pear
20160101    banana
20160102    apple
20160102    pear
20160102    beans

我需要弄清楚每个日期发生的差异，因此对于 2016 年 1 月 2 日的此示例，添加了一个字符串 'beans'，并从组中删除了一个 'banana'.

I need to figure out the differences that occur for each date, so for this example from 01/02/2016 there is a an added string 'beans' and a 'banana' was removed from the group.

到目前为止，我的代码是:

So far I have as my code:

groups = frame['Item'].groupby(frame['Date'])

for date, item in groups:
    for i in item:
        if i not in item[:-1]:
            print date, item, 'Deleted'

这似乎不起作用.我应该期待:

This doesn't seem to be working. I should be expecting:

20160102 , banana, Deleted

感谢您的帮助！

推荐答案

diffs = frame.groupby(frame.columns.tolist()).size().unstack(fill_value=0).diff()
diffs

diffs.mask(diffs.eq(0)).stack().map({-1: 'deleted', 1: 'added'})

Date      Item  
20160102  banana    deleted
          beans       added
dtype: object

这篇关于如何遍历 Pandas 组并检查每个组中是否有一个字符串?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！