How to fill the values in the list and convert it into the dataframe?(Part II)

I have a modified data frame from the previous question: How to fill the values in the list and convert it into the dataframe?

Item       Photo1     Photo2    Photo3    Photo4   Description1  Description2  Description 3

A           A1.jpg      A2.jpg                        Nice           Beautiful
B           B1.jpg      B2.jpg    B3.jpg    B4.jpg    Ugly           Damaged
C           C1.jpg                                    Cute           Handsome     Nice

I want to use the code from the previous question on the two fields:

photo_df= df1.fillna('').filter(like='Photo')
vals = [(i, y) for i, x in enumerate(photo_df.to_numpy())
          for y in vals[:3] + [['PH',z] 
          for z in photo_df.columns[x!='']]]

What i tried is:

photo_df= df1.fillna('').filter(like='Photo')
product_df = df1.fillna('').filter(like='Description')

vals = [(i, y) for i, x in enumerate(photo_df.to_numpy())
          for y in vals[:3] + [['PH',z] 
          for z in photo_df.columns[x!='']]]
vals = [(i, y) for i, x in enumerate(product_df.to_numpy())
          for y in vals[:4] + [['Description',z] 
          for z in product_df.columns[x!='']]]
L = [df1.loc[df1.index[[i]], x].set_axis(range(len(x)), axis=1) for i, x in vals]

df  = pd.concat(L)

but this gives the list out of the list,

Again I tried, I divided the dataframes into two parts:

photo_df= df1.fillna('').filter(like='Photo')
photo_df = photo_df.fillna('')
product_df = df1.fillna('').filter(like='Description')
product_df = product_df.fillna('')

vals = [(i, y) for i, x in enumerate(photo_df.to_numpy())
          for y in vals[:3] + [['PH',z] 
          for z in photo_df.columns[x!='']]]
vals2 = [(i, y) for i, x in enumerate(product_df.to_numpy())
          for y in vals[:0] + [['Description',z] 
          for z in product_df.columns[x!='']]]
L = [df1.loc[df1.index[[i]], x].set_axis(range(len(x)), axis=1) for i, x in vals]
M = [df2.loc[df2.index[[i]], x].set_axis(range(len(x)), axis=1) for i, x in vals2]

df  = pd.concat(L)
 
df3 = pd.concat(M)

df = pd.concat([df,df3])

Output:

 I             A
PH           A1.jpg
PH           A2.jpg
 I             B
PH           B1.jpg
PH           B2.jpg
PH           B3.jpg
PH           B4.jpg
 I             C
PH           C1.jpg
Description Nice
Description Beauiful
Description Ugly
Description Damaged
Description Cute
Description Handsome
Description Nice
 

How to properly concatenate in the below format?

Expected Dataframe is similar like to the previous question, with description added.

Expected Output:

I             A
PH           A1.jpg
PH           A2.jpg
Description Nice
Description Beauiful
I             B
PH           B1.jpg
PH           B2.jpg
PH           B3.jpg
PH           B4.jpg
Description Ugly
Description Damaged
I             C
PH           C1.jpg
Description Cute
Description Handsome
Description Nice

from How to fill the values in the list and convert it into the dataframe?(Part II)