Compute percentage for each row in pandas dataframe

Question

                  country_name  country_code  val_code  \\
   United States of America           231                     1   
   United States of America           2         


        

Answer 1

Ge the total for all the columns of interest and then add the percentage column:

In [35]:
total = np.sum(df.ix[:,'y191':].values)
df['percent'] = df.ix[:,'y191':].sum(axis=1)/total * 100
df

Out[35]:
               country_name  country_code  val_code      y191      y192  \
0  United States of America           231         1  47052179  43361966   
1  United States of America           231         1   1187385   1201557   
2  United States of America           231         1  28211467  27668273   
3  United States of America           231         1    179000    193000   
4  United States of America           231         1  12613922  12864425   

       y193      y194      y195    percent  
0  42736682  43196916  41751928  50.149471  
1   1172941   1176366   1192173   1.363631  
2  29742374  27543836  28104317  32.483447  
3    233338    276639    249688   0.260213  
4  13240395  14106139  15642337  15.743237  

So np.sum will sum all the values:

In [32]:
total = np.sum(df.ix[:,'y191':].values)
total

Out[32]:
434899243

We then call .sum(axis=1)/total * 100 on the cols of interest to sum row-wise, divide by the total and multiply by 100 to get a percentage.