How to modify column names when combining rows of multiple columns into single rows in a dataframe based on a categorical value. + selective sum/mean

Question

I'm using the pandas .groupby function to combine multiple rows into a single row.

Currently I have a dataframe df_clean which has 405 rows, and 85 columns. There are up to 3 rows that correspond to a single Batch.

My current code for combining the multiple rows is:

num_V = 84 #number of rows -1 for the row "Batch" that they are being grouped by
max_row = df_clean.groupby('Batch').Batch.count().max()
df2= (
        df_clean.groupby('Batch')
        .apply(lambda x: x.values[:,1:].reshape(1,-1)[0])
        .apply(pd.Series)
)

This code works creating a dataframe df2 which groups the rows by Batch, however the columns in the resulting dataframe are simply numbered (0,1,2,3,...249,250,251) note that 84*3=252, ((number of columns - Batch column)*3)=252, Batch becomes the index.

I'm cleaning some data for analysis and I want to combine the data of several (generally 1-3) Sub_Batch values on separate rows into a single row based on their Batch. Ideally I would like to be able to determine which columns are grouped into a row and remain separate columns in the row, as well as which columns the average, or total value is reported.

for example desired input/output:

Original dataframe

Output dataframe note: naming of columns, and that all columns are copied over and that the columns are ordered according to which sub-batch they belong to. ie Weight_2 will always correspond to the second sub_batch that is a part of that Batch, Weight_3 will correspond to the third Sub_batch that is part of the Batch.

Ideal output dataframe note: naming of columns, and that in this dataframe there is only a single column that records the Color as they are identical for all Sub-Batch values within a Batch. The individual Temperature values are recorded, as well as the average of the Temperature values for a Batch. The individual Weight values are recorded as well as the sum of the weight values in the column 'Total_weight`

I am 100% okay with the Output Dataframe scenario as I will simply add the values that I want afterwards using .mean and .sum for the values that I desire, I am simply asking if it can be done using `.groupby' as it is not something that I have worked with before, and I know that it does have some ability to sum or average results.