Python 从熊猫的专栏中总结观察结果

假设我有一个大数据框DS_df，其中包括列名year、dealamount和CCS等。从1985年到2020年，每年我都需要一个单独的熊猫系列，即sum_2019。如果CCS确实发生多次（如果只发生一次，则应将其添加到系列中），并且年份匹配，则我需要对dealamount求和：

    year    dealamount  CCS
0   2013    37,522,700  Albania_Azerbaijan
1   2013    37,522,700  Albania_Azerbaijan
2   2016    436,341,300 Albania_Greece
3   2019    763,189,200 Albania_Russia
4   2019    763,189,200 Albania_Russia
5   2019    763,189,200 Albania_Russia
6   2019    763,189,200 Albania_Russia
7   2017    150,931,000 Albania_Turkey
8   2016    275,293,750 Albania_Turkey
9   2009    258,328,000 Albania_Turkey
10  2019    153,452,000 Albania_Venezuela
11  2019    153,452,000 Albania_Venezuela
11  2017    153,452,000 Albania_Venezuela

因此，在这种情况下，sum_2019应该是一个熊猫系列，指数为CCS，总量为“观测值”

同样，对于sum_2013：

Albania_Azerbaijan 75,045,400

非常感谢您提供的任何帮助，因为我需要为很多数据点提供这些帮助，并且感到非常失落（对于python来说真的很陌生），我该如何正确地实现自动化呢

谢谢

你想要这个吗

df.dealamount = df.dealamount.str.replace(',','').astype(int)
new_df = df.groupby(['year','CCS']).agg({'dealamount': sum})

输出-

                         dealamount
year CCS                           
2009 Albania_Turkey       258328000
2013 Albania_Azerbaijan    75045400
2016 Albania_Greece       436341300
     Albania_Turkey       275293750
2017 Albania_Turkey       150931000
     Albania_Venezuela    153452000
2019 Albania_Russia      3052756800
     Albania_Venezuela    306904000

                         dealamount
year CCS                           
2009 Albania_Turkey       258328000
2013 Albania_Azerbaijan    75045400
2016 Albania_Greece       436341300
     Albania_Turkey       275293750
2017 Albania_Turkey       150931000
     Albania_Venezuela    153452000
2019 Albania_Russia      3052756800
     Albania_Venezuela    306904000

# to avoid scientific notation (e notation)
pd.set_option('display.float_format', lambda x: '%.d' % x) 

# first filter by 'year' then group by 'CSS' and finally sum by 'dealamount'
sum_2019 = df[df['year']==2019].groupby('CCS')['dealamount'].sum()

print(sum_2019)
CCS
Albania_Russia      3052756800
Albania_Venezuela    306904000
Name: dealamount, dtype: float64