Combine multiple rows into Single row based on specific column using python - python-3.x

Question

I need to modify available value in billable and non-billable utilization, earlier its default now the value is dynamic.
I have a Billable column value as 'Yes' and 'No'
If Value is 'Yes' then it will sum row-wise and created new columns as 'Billable Utilization'
Billing_utilization = df[Billing_utilization] * sum/available * 100
If value is 'No' then it will be sum row-wise and created new column as 'Non-Billable Utilization'.
Non-Billing_utilization = df[Non-Billing_utilization] * sum/ available1 * 100
Data:
| Employee Name | Java | Python | .Net | React | Billable |
| Priya | 10 | | 5 | | Yes |
| Priya | | 10 | | 5 | No |
| Krithi | | 10v | 20 | | No |
Output
Priya is in both billable and non-billable, priya name appears in two rows. I need to merge in single row with Employee Name. So expected output should be
| Employee Name | Java | Python | .Net | React | Total | Billing | Non-Billing |
| Priya | 10 | 10 | 5 | 5 | 30 | 8.928571429 | 8.928571429 |
| Krithi | 10 | 20 | | | 30 | | 17.85714286 |
df['Billable Status'] = np.where ( df['Billable Status'] == 'Billable', 'Billable Utilization','Non Billable Utilization' )
df2 = (df.groupby ( ['Employee Name', 'Billable Status'])[list_column].sum ().sum ( axis=1 ).unstack ().div (available2).mul(100)).round ( 2 ))
df = df1.join ( df2 ).reset_index ()
df.index = df.index
# Round the column value
df['Total'] = df['Total'].round ( 2 )
# df= df.round(2)

Answer 1

Try:
cols = df.select_dtypes ( 'number' ).columns.tolist ()
df['Total'] = df.groupby('Employee Name')[cols].transform('sum').sum(1)
df['Billing'] = df.mask(df['Billable'] == 'No')[cols].sum(1) / df['Total']
df['Non-Billing'] = df.mask(df['Billable'] == 'Yes')[cols].sum(1) / df['Total']
aggfuncs = dict(zip(cols, ['sum']*len(cols)))
aggfuncs.update({'Total': 'first', 'Billing': 'sum', 'Non-Billing': 'sum'})
out = df.pivot_table(aggfuncs, 'Employee Name', aggfunc=aggfuncs,
sort=False, fill_value=0)[aggfuncs].reset_index()
Output:
>>> out
Employee Name Java Python .Net React Total Billing Non-Billing
0 Priya 10 10 5 5 30 0.5 0.5
1 Krithi 0 10 20 0 30 0.0 1.0