我如何根据条件为特定列迭代值的总和

Question

这是 DataFrame 和我的代码

import pandas as pd
 
    
data = {
    'year': ['2000','2000', '2000', '2000','2000','2000','2000','2000','2000','2000','2000','2000','2000','2000','2000',
            '2001','2001','2001','2001','2001','2001','2001','2001','2001','2001','2001','2001','2001','2001','2001',
            '2002','2002','2002','2002','2002','2002','2002','2002','2002','2002','2002','2002','2002','2002','2002'],     
    'type':[2,2,2,2,2,3,3,3,3,3,4,4,4,4,4,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4],    
    'other_type':[0,1,2,3,4,0,1,2,3,4,0,1,2,3,4,0,1,2,3,4,0,1,2,3,4,0,1,2,3,4,0,1,2,3,4,0,1,2,3,4,0,1,2,3,4],    
    'Fee':[0,0,0,0,0,33,40,50,2,33,0,0,0,0,0,
                  30,50,10,200,45,0,0,0,0,0,0,0,0,0,0,
                 0,0,0,0,0,0,0,0,0,0,30,50,10,200,45]
}  
dfobj = pd.DataFrame(data)
dfobj.head()

我想根据列类型的条件进行筛选，如果值等于 3，并且如果列 other_type 为 0 和 1，则对 Fee 列的这些值求和。 这就是我所拥有的

row_Sum = data.loc[(data['type']==3)&(data['other_type'] <2)].sum(axis=0,numeric_only=True)

但问题是所有年份都被分组到结果中，我试过这个但它是低效的，因为每年都是一年，真正的 df 就像数千行和许多列和年份。

row_Sum = dfobj.loc[(dfobj['year']==2000)&(dfobj['type']==3)&(dfobj['other_type'] <2)].sum(axis=0,numeric_only=True)

主要目标是对所有年份应用求和条件。

非常感谢您能提供的任何帮助，谢谢！

Answer 1

您可以过滤并使用groupby.sum ：

m = dfobj['type'].eq(3) & dfobj['other_type'].isin([0, 1])

out = dfobj.loc[m, 'Fee'].groupby(dfobj['year']).sum()

output：

year
2000    73
2001     0
2002     0
Name: Fee, dtype: int64