pandas groupby差异 [英] Pandas groupby diff

问题描述

因此，我的数据框如下所示：

So my dataframe looks like this:

from pandas.compat import StringIO
d = StringIO('''
date,site,country,score
2018-01-01,google,us,100
2018-01-01,google,ch,50
2018-01-02,google,us,70
2018-01-03,google,us,60
2018-01-02,google,ch,10
2018-01-01,fb,us,50
2018-01-02,fb,us,55
2018-01-03,fb,us,100
2018-01-01,fb,es,100
2018-01-02,fb,gb,100
''')

df = pd.read_csv(d, sep=",")

每个网站都有不同的分数，具体取决于国家。我试图找出每个网站/国家/地区组合的1/3/5天的分数差异。

Each site has a different score depending on the country. I'm trying to find the 1/3/5 day difference of scores for each site/country combination.

输出结果应该是：

Output should be:

date,site,country,score,1_day_diff
2018-01-01,google,ch,50,0
2018-01-02,google,ch,10,-40
2018-01-01,google,us,100,0
2018-01-02,google,us,70,-30
2018-01-03,google,us,60,-10
2018-01-01,fb,es,100,0
2018-01-02,fb,gb,100,0
2018-01-01,fb,us,50,0
2018-01-02,fb,us,55,5
2018-01-03,fb,us,100,45

我首先尝试按网站/国家/日期进行排序，然后按网站和国家/地区进行分组，但我无法围绕分组对象获取差异。

I first tried sorting by site/country/date, then grouping by site and country but I'm not able to wrap my head around getting a difference from a grouped object.

推荐答案

首先，对DataFrame进行排序，然后您需要的只是 groupby.diff（）：

First, sort the DataFrame and then all you need is groupby.diff():

df = df.sort_values(by=['site', 'country', 'date'])

df['diff'] = df.groupby(['site', 'country'])['score'].diff().fillna(0)

df
Out: 
         date    site country  score  diff
8  2018-01-01      fb      es    100   0.0
9  2018-01-02      fb      gb    100   0.0
5  2018-01-01      fb      us     50   0.0
6  2018-01-02      fb      us     55   5.0
7  2018-01-03      fb      us    100  45.0
1  2018-01-01  google      ch     50   0.0
4  2018-01-02  google      ch     10 -40.0
0  2018-01-01  google      us    100   0.0
2  2018-01-02  google      us     70 -30.0
3  2018-01-03  google      us     60 -10.0

sort_values 不支持任意排序。如果您需要任意排序（例如fb之前的谷歌），您需要将它们存储在一个集合中，并将您的列设置为明确的。然后sort_values会尊重您在那里提供的订单。

sort_values doesn't support arbitrary orderings. If you need to sort arbitrarily (google before fb for example) you need to store them in a collection and set your column as categorical. Then sort_values will respect the ordering you provided there.

这篇关于 pandas groupby差异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！