问题描述
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
我想按日期计算每个国家/地区的累计总数,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
我尝试了 grouping by two levels 但 .count() 不起作用(计数根本不显示)而 .size() 起作用:
cumulative_by_date = new_df.groupby(['date_added','country']).size()
我不知道如何将 this question's solution 与 .size() 一起应用以获得累积总和。
解决方法
按照第二个链接问题的方法,这是一个带有 groupby
和 cumsum
的双 reset_index
:
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
分步骤:
# 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