Sum Specific Columns Among Rows

summing rows of specific columns then dividing by the sum

Try this way to specify the column (by sub-setting Df), and then indicating the margin as 1

Df_new = t(apply(Df[,c(1:3)], 1, \(x) x/sum(x)))

       lose      draw       win
[1,] 0.5000 0.1428571 0.3571429
[2,] 0.0625 0.1250000 0.8125000

sum cells of certain columns for each row

You could do something like this:

summed <- rowSums(zscore[, c(1, 2, 3, 5)])

SUM specific column values that have integers where row meets a condition and place in new row

you can use rolling window to calculate the sum of pair of two columns, then concat the result

col=[1,0,1,0]
df2=pd.concat([df, 
               df.loc[df['ID'].isin(['AA','BB']) ]
               .rolling(2, axis=1).sum() # calc rolling windows sum of two columns
               .shift(-1, axis=1) # shift result to left
               .fillna(0) # fill null values
               .mul(col) # multipley to keep sum in alternate columns
              ]
             )
df2.sort_index(axis=0, inplace=True)

#create a column with a new ID
df2['ID2']=df2['ID']+'_New'

# fill NA values with the row above
df2['ID2'].fillna(method='ffill', inplace=True)

#reset index
df2=df2.reset_index()

# where the ID is null (our new summed row), assign the ID2 to ID
df2.loc[df2['ID'].isna(), 'ID'] =   df2['ID2']

#drop unwanted columns
df2.drop(columns=['ID2', 'index'], inplace=True)
df2

    ID      Q121    Q221    Q321    Q421
0   AA       8.0    4.8     3.1     5.3
1   AA_New  12.8    0.0     8.4     0.0
2   BB       0.6    0.7     0.3     0.9
3   BB_New  1.3     0.0     1.2     0.0```

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