How to create a automatic discounted price list from Easyocr result?

Question

So we are tasked to create a code where the result of the Easyocr into a table (specifically food menus). The brick wall starts right after obtaining the result from easyocr since it I tried sorting the result but it sorts per character and number instead of words and price. I know that creating a list manually will solve it but it beats the purpose of automating the code of applying discount on a ocr.

We read the text:

result2 = reader.readtext(IMAGE_PATH, detail=0, slope_ths= 0.2)

result2 contains the following:

['SIZZLING SPECIALS',
 'Spareribs',
 '195.00',
 'Pork Katsudon',
 '175.00',
 'Sizzling Sisig',
 '180.00',
 'Sisig Pulutan',
 '160.00',
 'Pork',
 'Barbeque',
 '160.00',
 'Pork Teriyaki',
 '160.00',
 'Peruvian Chicken',
 '160.,00',
 'Stuffed Squid',
 '345.00',
 'Boneless Bangus',
 '150.00',
 "Tokwa't Baboy",
 '150.00',
 'Sizzling Lomi',
 '110.00']

I wanted to have a result where in the food name and the price are in separate columns. As well as to apply discount to the price.

Column 1	Column 2
Spareribs	195.00-20%
Pork Katsudon	175.00-20%
...	...
...	...
...	...
Sizzling lomi	115.00-20%

Answer 1

You would need to do some data cleaning, but try the following:

import pandas as pd

result2 = ['SIZZLING SPECIALS',
           'Spareribs',
           '195.00',
           'Pork Katsudon',
           '175.00',
           'Sizzling Sisig',
           '180.00',
           'Sisig Pulutan',
           '160.00',
           'Pork',
           'Barbeque',
           '160.00',
           'Pork Teriyaki',
           '160.00',
           'Peruvian Chicken',
           '160.,00',
           'Stuffed Squid',
           '345.00',
           'Boneless Bangus',
           '150.00',
           "Tokwa't Baboy",
           '150.00',
           'Sizzling Lomi',
           '110.00']

# Remove SIZZING SPECIALS and Pork
result2 = result2[1::]
del result2[result2.index("Pork")]

result_final = pd.DataFrame([
    {"Column 1": result2[2*i],
     "Column 2": result2[2*i+1]} for i in range(len(result2) // 2)])

result_final

Column 1	Column 2
Spareribs	195.00
Pork Katsudon	175.00
Sizzling Sisig	180.00
Sisig Pulutan	160.00
Barbeque	160.00
Pork Teriyaki	160.00
Peruvian Chicken	160.,00
Stuffed Squid	345.00
Boneless Bangus	150.00
Tokwa't Baboy	150.00
Sizzling Lomi	110.00