Build dataframe from python dictionary

This is indeed possible. Because your dictionary does not contain more than 1 key / value pair, I would suggest to merge it into a string:

my_string = f"{list(d1.keys())[0]} {list(d1.values())[0]}"

Next, you can flag the "constant" values of columns and rows:

COL_ROWS = ["Type 1 Result", "CO \(mg/km\)", "THC \(mg/km\)", "NMHC \(mg/km\)", "NOX \(mg/km\)", "THC \+  PM \(mg/km\)", "PN \(#\.1011/km\)", "Measured\(8\) \(9\)", "Ki x \(8\) \(10\)", "Ki \+ \(8\) \(10\)", "Mean value calculated with Ki \(M x Ki\) or M\+Ki\) \(9\)", "DF \(\+\) \(8\) \(10\)", "DF \(x\) \(8\) \(10\)", "Final mean value calculated with Ki and DF \(13\)", "Limit value"]

Subsequently, if you remove the strings that appear in COL_ROWS from my_string. Using: Remove substring from string if substring is contained in a list:

import re
p = re.compile('|'.join(COL_ROWS ))
my_string = p.sub("", my_string).strip() 

You will obtain a string where each value is separated by a space. You can then simply do elements = my_string.split() to have them neatly in a list.

Finally, you simply have to implement the logic to initialize a DataFrame using that data by iterating over the columns and elements.

A possibility is:

# separate headers from content
COLS, CONTENT = COL_ROWS[:8], COL_ROWS[8:]
    
all_cols = {}
for i in range(len(CONTENT)):
    # store column name
    col = [CONTENT[i].replace('\\', '']
    # add values
    col += el[i * 7: (i+1) * 7]
    # store in dict
    all_cols[COLS[i]] = col

# initialize DF with dict
final_df = pd.DataFrame(all_cols)