使用两级 groupby 计算随时间推移的累积次数

Counting culmulative occurences over time with a two-level groupby

我有一个如下所示的数据集:

    country            date_added
0   United States       01/2013
1   United Kingdom      03/2014
2   Egypt               03/2014
3   United States       03/2014
4   United States       03/2014
5   United Kingdom      06/2015
6   United States       06/2015

我想要 运行 每个国家/地区按日期的累计总数,即:

    date_added         country         cumulative_count
0   01/2013             United States          1
1   03/2014             United Kingdom         1
2   03/2014             Egypt                  1
3   03/2014             United States          2
4   06/2015             United Kingdom         2
5   06/2015             United States          4

我试过 grouping by two levels 但 .count() 不起作用(计数根本不显示)而 .size() 确实:

cumulative_by_date = new_df.groupby(['date_added','country']).size()

我不知道如何应用 this question's solution 和 .size() 来获得累计和。

按照第二个链接问题的方法,这里有一个带有 cumsumreset_index 的双 groupby

df.groupby(['date_added', 'country']).size()
  .groupby(['country']).cumsum().reset_index(name='cumulative_count')

输出:

  date_added         country  cumulative_count
0    01/2013   United States                 1
1    03/2014           Egypt                 1
2    03/2014  United Kingdom                 1
3    03/2014   United States                 3
4    06/2015  United Kingdom                 2
5    06/2015   United States                 4

步骤:

# size by date and country
print(df.groupby(['date_added', 'country']).size())

# output
date_added  country       
01/2013     United States     1
03/2014     Egypt             1
            United Kingdom    1
            United States     2
06/2015     United Kingdom    1
            United States     1
# cumulative sum by country
print(df.groupby(['date_added', 'country']).size()
        .groupby(['country']).cumsum())

# output
date_added  country       
01/2013     United States     1
03/2014     Egypt             1
            United Kingdom    1
            United States     3
06/2015     United Kingdom    2
            United States     4
# reset index
print(df.groupby(['date_added', 'country']).size()
        .groupby(['country']).cumsum().reset_index(name='cumulative_count'))

# output
  date_added         country  cumulative_count
0    01/2013   United States                 1
1    03/2014           Egypt                 1
2    03/2014  United Kingdom                 1
3    03/2014   United States                 3
4    06/2015  United Kingdom                 2
5    06/2015   United States                 4