pandas collapsing row data

Question

New to pandas, I m climbing my learning curve here. I have a dataframe that looks like:

Relinquished Degree Count DTD DNP outindefinitely seasonout 
------------         


        

Answer 1

df.groupby('Relinquished').sum()

Answer 2

You cannot replace missing values to empty strings in first step and then aggregate sum:

df = df.groupby('Relinquished').sum()

If want specify columns for sum:

print (df)
  Relinquished  Degree  Count  DTD  DNP  outindefinitely  seasonout
0      player1       1      1  1.0  NaN              NaN        NaN
1      player1       3      1  NaN  NaN              1.0        NaN

df = df.groupby('Relinquished')['DTD','DNP','outindefinitely','seasonout'].sum()
print (df)
              DTD  DNP  outindefinitely  seasonout
Relinquished                                      
player1       1.0  0.0              1.0        0.0