英文:
Pandas new column based in sum a column from another pandas
问题
Sure, here's the translated code portion you requested:
我有两个数据框，第一个是：
unit year
0 1 2020
1 2 2021
2 3 2022
第二个是：
unit observations
0 1 0
1 2 1
2 2 2
3 2 3
4 2 4
5 3 5
我需要在第一个数据框中添加一个列，该列是第二个数据框中单位的观察值之和，最终结果如下：
unit year observations
0 1 2020 0
1 2 2021 10
2 3 2022 5
我尝试了使用 df_1.iterrows 并基于第一个数据框的单位进行查询来进行求和，它有效，但我在谈论有约 400 万行的数据框，这个解决方案将需要几天时间。有人有更快的解决方案吗？
英文:
I have two dataframes, being the first one:
unit year
0 1 2020
1 2 2021
2 3 2022
and the second:
unit observations
0 1 0
1 2 1
2 2 2
3 2 3
4 2 4
5 3 5
I need to add a column at the first dataframe as a sum of observations for the unit at the second dataframe, I have something like this at the end
unit year observations
0 1 2020 0
1 2 2021 10
2 3 2022 5
I tried to df_1.iterrows and using a query based in the unit from the first df to sum, and it worked, but I'm talking about a df with about to 4 million rows, this solution will take days. Someone have a quicker solution?
答案1
得分: 2
使用Series.map与第二个数据框中的sum进行聚合：
df1['observations'] = df1['unit'].map(df2.groupby('unit')['observations'].sum())
print(df1)
unit year observations
0 1 2020 0
1 2 2021 10
2 3 2022 5
英文:
Use Series.map with aggregate sum in second DataFrame:
df1['observations'] = df1['unit'].map(df2.groupby('unit')['observations'].sum())
print (df1)
unit year observations
0 1 2020 0
1 2 2021 10
2 3 2022 5
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