python - 存储在新数据框中的 Pandas groupby

Question

我有以下代码:

import pandas as pd
df1 = pd.DataFrame({'Counterparty':['Bank','Bank','GSE','PSE'],
            'Sub Cat':['Tier1','Small','Small', 'Small'],
            'Location':['US','US','UK','UK'],
            'Amount':[50, 55, 65, 55],
            'Amount1':[1,2,3,4]})

df2=df1.groupby(['Counterparty','Location'])[['Amount']].sum()
df2.dtypes
df1.dtypes

df2 数据框没有我要聚合的列(交易对手和位置)。任何想法为什么会这样？ Amount 和 Amount1 都是数字字段。我只想对 Amount 求和并汇总 Amount1

Answer 1

对于来自索引的列，添加 as_index=False 参数或 reset_index :

df2=df1.groupby(['Counterparty','Location'])[['Amount']].sum().reset_index()
print (df2)
  Counterparty Location  Amount
0         Bank       US     105
1          GSE       UK      65
2          PSE       UK      55

df2=df1.groupby(['Counterparty','Location'], as_index=False)[['Amount']].sum()
print (df2)
  Counterparty Location  Amount
0         Bank       US     105
1          GSE       UK      65
2          PSE       UK      55

如果此处所有列的聚合发生automatic exclusion of nuisance columns - 列 Sub Cat 被省略:

df2=df1.groupby(['Counterparty','Location']).sum().reset_index()
print (df2)
  Counterparty Location  Amount  Amount1
0         Bank       US     105        3
1          GSE       UK      65        3
2          PSE       UK      55        4


df2=df1.groupby(['Counterparty','Location'], as_index=False).sum()