Pandas, merging two rows with different index names

Question

I have data frame, df, that looks like this:

              Done  Todo  Total                     
Painting       55    54    109
Fitting        17    26     43
Plumbing       10    26     36
Electricity     7    29     36
Piping         29     5     34
Roofing        12    20     32

I need to merge indexes 'Plumbing' and 'Piping' so that I have a data frame that looks like this:

              Done  Todo  Total                     
Painting       55    54    109
Fitting        17    26     43
Plumbing       39    46     68
Electricity     7    29     36
Piping         29     5     34

How can I achieve this is pandas?

I have tried the following

df.loc['Plumbing'] = df.loc['Plumbing'] + df.loc['Piping']

but this keeps the 'Piping' row in the data frame. Is there a way of doing it automatically so that the 'Piping row is automatically removed? This and this questions did not provide what I need.

Answer 1

Its not automaticaly but:

df.loc['Plumbing'] = df.loc['Plumbing'] + df.loc['Piping']
df.drop('Piping',axis=0,inplace=True)

Answer 2

The easier is drop.

But you can replace values in index (first call to_series, because replace is not implemented in index) and then groupby by index with sum:

df.index = df.index.to_series().replace({'Piping':'Plumbing'}) 
print df
             Done  Todo  Total
Painting       55    54    109
Fitting        17    26     43
Plumbing       10    26     36
Electricity     7    29     36
Plumbing       29     5     34
Roofing        12    20     32

print df.groupby(df.index, sort=False).sum()
             Done  Todo  Total
Painting       55    54    109
Fitting        17    26     43
Plumbing       39    31     70
Electricity     7    29     36
Roofing        12    20     32