pandas-根据数据框的2个单独列中的值构造列

Question

I have a pandas dataframe which looks similar to this(i have cooked up an example, since I can't share the data)

raw_data = {'regiment': ['Nighthawks', 'Nighthawks', 'Dragoons', 'Dragoons', 'Scouts'], 
        'company': ['1st', '2nd', '1st', '2nd', '2nd'],  
        'thisValue': [1, 2, 3, 2, 7],
        'total': [3, 3, 5, 5, 7]}
df = pd.DataFrame(raw_data, columns = ['regiment', 'company', 'thisValue', 'total'])
df

The output is :

    regiment    company thisValue   total
0   Nighthawks  1st         1         3
1   Nighthawks  2nd         2         3
2   Dragoons    1st         3         5
3   Dragoons    2nd         2         5
4   Scouts      2nd         7         7

I want to have statistics about count of values of eachValue for a regiment. That is I need the resulting dataframe to be like this:

regiment    1stCompanyValue 2nd_Company_Value   total
Nighthawks         1               2              3
Dragoons           3               2              5
Scouts             0               7              7

I tried grouping it on company values, but then not sure how to proceed. How can this be done in pandas?

Answer 1

We can make use of pivot , groupby and concat ie

one  = df.pivot(columns='company',values='thisValue',index='regiment').add_suffix('_company_value').fillna(0)
two = df.groupby('regiment')['total'].first()

ndf = pd.concat([one,two],1)

              1st_company_value  2nd_company_value  total
regiment                                               
Dragoons                  3.0                2.0      5
Nighthawks                1.0                2.0      3
Scouts                    0.0                7.0      7