如何根据Pandas中具有特定值的列将多行合并为一行

Question

I have a DataFrame like this way:

item_id    revenue    month    year
1          10.0       01       2014
1          5.0        02       2013
1          6.0        04       2013
1          7.0        03       2013
2          2.0        01       2013
2          3.0        03       2013
3          5.0        04       2013

And I try to get the revenue of each item from January to March 2013 like following DataFrame:

item_it    revenue    year
1          12.0       2013
2          5.0        2013
3          0          2013

BUT, I am confused on how to implement it in Pandas. Any help would be appreciated.

Answer 1

You can slice first, then groupby and reindex to include 0 values.

month_start, month_end = 1, 3
year = 2013

res = df.loc[df['month'].between(month_start, month_end) & df['year'].eq(year)]\
        .groupby('item_id')['revenue'].sum()\
        .reindex(df['item_id'].unique()).fillna(0)\
        .reset_index('revenue').assign(year=year)

print(res)

   item_id  revenue  year
0        1     12.0  2013
1        2      5.0  2013
2        3      0.0  2013

Answer 2

You can use groupby first then sum method to get the desire output.

df.groupby(['year', 'item_id']).sum().reset_index().drop('month', axis=1).set_index('item_id')

         year  revenue
item_id               
1        2013     18.0
2        2013      5.0
3        2013      5.0
1        2014     10.0