本文主要是介绍【Pandas】根据某列分组求和,希望对大家解决编程问题提供一定的参考价值,需要的开发者们随着小编来一起学习吧!
源数据:
data = [['API Management',10,"Apr-21"],['App Configuration',12,"Aug-21"],['Application Gateway',13,"Feb-21"],['Automation',13,"Apr-21"],['Azure Analysis Services',1,"Apr-21"]]
df = pd.DataFrame(data,columns=["serviceType", "cost", "date"],dtype=float)
print(df)>>serviceType cost date
0 API Management 10.0 Apr-21
1 App Configuration 12.0 Aug-21
2 Application Gateway 13.0 Feb-21
3 Automation 13.0 Apr-21
4 Azure Analysis Services 1.0 Apr-21
根据date分组求和cost:
df=df.groupby(by=['date'])['cost'].sum().reset_index()
print(df)
>>date cost
0 Apr-21 24.0
1 Aug-21 12.0
2 Feb-21 13.0注:sum()后生成的数据类型是Series,如果进一步需要将其转换为dataframe,可以调用Series中的to_frame()方法或者reset_index().
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