import pandas as pd

# Read the Spanish CSV with proper encoding
spanish_df = pd.read_csv('EP machine park  2025 es.csv', header=None, encoding='latin-1')

# Create English data
english_data = [
    ['', '', '', '', '', '', ''],
    ['', '', '', '', '', '', ''],
    ['FIELD ZONE', '', 'TYPE', 'BRAND', 'MODEL', '', ''],
    ['', '', '', '', '', '', ''],
    ['GREENS', '', 'MANUAL', 'TORO', 'Greensmaster Flex 1021 No. 1', '', ''],
    ['', '', '', 'TORO', 'Greensmaster Flex 1021 No. 2', '', ''],
    ['', '', '', 'TORO', 'Greensmaster Flex 1021 No. 3', '', ''],
    ['', '', '', 'TORO', 'Greensmaster Flex 1021 No. 4', '', ''],
    ['', '', '', 'TORO', 'Greenmaster 1000', '', ''],
    ['', '', '', 'JOHN DEERE', '220B', '', ''],
    ['', '', 'TRANSPORT', 'TORO', 'Transport 80 rails No. 1', '', ''],
    ['', '', '', 'TORO', 'Transport 80 rails No. 2', '', ''],
    ['', '', '', 'TORO', 'Transport 80 rails No. 3', '', ''],
    ['', '', '', 'TORO', 'Transport 80 rails No. 4', '', ''],
    ['', '', 'TRIPLETS', 'JOHN DEERE', 'JD 2500 No. 1 - Verticut', '', ''],
    ['', '', '', 'JOHN DEERE', 'JD 2500 No. 2 - Maredo', '', ''],
    ['', '', '', 'JOHN DEERE', 'JD 2500 No. 4 - Retain', '', ''],
    ['', '', '', 'JOHN DEERE', 'JD 2500 No. 5 - Weekend Mowing', '', ''],
    ['', '', 'ROLLER', 'TRUE TURF', 'RB 48 No. 1', '', ''],
    ['', '', '', 'TRUE TURF', 'RB 48 No. 2', '', ''],
    ['', '', '', '', '', '', ''],
    ['', '', '', '', '', '', ''],
    ['TEES & COLLARS', '', 'MANUAL', 'TORO', 'Greenmaster 1026 No. 1', '', ''],
    ['', '', '', 'TORO', 'Greenmaster 1026 No. 2', '', ''],
    ['', '', '', 'TORO', 'Greenmaster 1026 No. 3', '', ''],
    ['', '', '', 'BARONESS', 'LM66TC', '', ''],
    ['', '', 'TRIPLETS', 'TORO', 'Reelmaster 3100-D No. 1', '', ''],
    ['', '', '', 'TORO', 'Reelmaster 3100-D No. 2', '', ''],
    ['', '', 'TRANSPORT', 'TORO', 'Transport 80 rails No. 1', '', ''],
    ['', '', '', 'TORO', 'Transport 80 rails No. 2', '', ''],
    ['', '', '', 'BARONESS', 'Baroness Transport', '', ''],
    ['', '', '', '', '', '', ''],
    ['', '', '', '', '', '', ''],
    ['FAIRWAYS', '', 'QUINTUPLE', 'BARONESS', 'LM 2700 No. 1', '', ''],
    ['', '', 'QUINTUPLE', 'BARONESS', 'LM 2700 No. 2', '', ''],
    ['', '', 'QUINTUPLE', 'JAKOBSEN', 'LF 3400 - Driving Range Mowing', '', ''],
    ['', '', '', '', '', '', ''],
    ['', '', '', '', '', '', ''],
    ['ROUGH', '', 'QUINTUPLE', 'TORO', 'Groundsmaster 4500-D 4WD No. 1', '', ''],
    ['', '', 'QUINTUPLE', 'TORO', 'Groundsmaster 4500-D 4WD No. 2', '', ''],
    ['', '', 'TRIPLET', 'TORO', 'Groundsmaster 3500-D Side Winder', '', ''],
    ['', '', '', '', '', '', ''],
    ['', '', '', '', '', '', ''],
    ['BUNKERS', '', 'RAKE', 'TORO', 'Sand Pro 3040 No. 1', '', ''],
    ['', '', 'RAKE', 'TORO', 'Sand Pro 3040 No. 2', '', ''],
    ['', '', 'RAKE', 'TORO', 'Sand Pro 3040 No. 3', '', ''],
    ['', '', '', '', '', '', ''],
    ['', '', '', '', '', '', ''],
    ['VEHICLES', '', 'CARS', 'TORO', 'Workman 2100 No. 1', '', ''],
    ['', '', '', 'TORO', 'Workman GTX No. 1', '', ''],
    ['', '', '', 'TORO', 'Workman GTX No. 2', '', ''],
    ['', '', '', 'TORO', 'Workman MDX-D No. 2', '', ''],
    ['', '', '', 'TORO', 'Workman MDX-D No. 3', '', ''],
    ['', '', '', 'TORO', 'Workman MD - Plumber', '', ''],
    ['', '', '', 'TORO', 'Workman MDX Gas No. 1', '', ''],
    ['', '', '', 'TORO', 'Workman MDX Gas No. 2', '', ''],
    ['', '', '', 'TORO', 'Workman MDX Gas No. 3', '', ''],
    ['', '', '', 'TORO', 'Workman MDX Gas No. 4', '', ''],
    ['', '', '', 'TORO', 'Workman MDX Gas No. 5', '', ''],
    ['', '', '', 'TORO', 'Workman MDX Gas No. 6', '', ''],
    ['', '', '', 'JOHN DEERE', 'Gator Turf No. 1', '', ''],
    ['', '', '', 'JOHN DEERE', 'Gator Turf No. 2', '', ''],
    ['', '', 'MULTI-PURPOSE', 'JOHN DEERE', 'Progator 2030 4WD No. 1', '', ''],
    ['', '', '', 'JOHN DEERE', 'Progator 2030 4WD No. 2', '', ''],
    ['', '', 'BUGGIES', 'EZGO', 'TXT Gas - Phytosanitary', '', ''],
    ['', '', '', 'EZGO', 'TXT Electric - Phytosanitary', '', ''],
    ['', '', '', 'CLUB CAR', 'Buggy Bar - Irrigation', '', ''],
    ['', '', '', 'EZGO', 'TXT Gas - Irrigation', '', ''],
    ['', '', '', 'EZGO', 'TXT Gas - Flag Changes', '', ''],
    ['', '', '', 'CLUB CAR', 'Head Greenkeeper', '', ''],
    ['', '', '', '', '', '', ''],
    ['', '', '', '', '', '', ''],
    ['MAINTENANCE', '', 'SPRAYING', 'TORO', 'Multipro 1750 - Greens', '', ''],
    ['', '', '', 'TORO', 'Multipro 5800 - Fairways', '', ''],
    ['', '', 'TOPDRESSING', 'TURFCO', '1520 Widespin', '', ''],
    ['', '', 'DEBRIS', 'TORO', 'Proforce No. 1', '', ''],
    ['', '', '', '', 'Proforce No. 2', '', ''],
    ['', '', '', '', 'Versavac', '', ''],
    ['', '', 'AERATION', 'TORO', 'Procore 548s + transport', '', ''],
    ['', '', '', 'WIEDEMAN', 'Fairway Aerator', '', ''],
    ['', '', '', 'REDEXIM', 'Vertidrain 7212 - Deep Tine Greens', '', ''],
    ['', '', 'SODCUTTER', 'RYAN', 'Sod Cutter', '', ''],
    ['', '', 'SEEDER', 'RYAN', 'Mataway', '', ''],
    ['', '', 'TRACTOR', 'JOHN DEERE', 'JD 5400 + Bucket', '', ''],
    ['', '', '', 'JOHN DEERE', 'JD 5400', '', ''],
    ['', '', '', 'KUBOTA', 'B2410', '', ''],
    ['', '', '', 'MASSEY FERG', '', '', ''],
    ['', '', 'DUMPER', 'TWAITES', '', '', ''],
    ['', '', 'BUCKET', 'AVANT 860I', 'Bucket+Clamp+Brush+Concrete Mixer+Stump Grinder', '', ''],
    ['', '', 'ROTARY', 'CATERPILLAR', '3025', '', ''],
    ['', '', 'GRINDER', 'BERNHARDT', 'Express Dual 3000', '', ''],
    ['', '', '', 'BERNHARDT', 'Angle Master 1000', '', ''],
    ['', '', '', 'FOLEY', 'Foley 365', '', '']
]

english_df = pd.DataFrame(english_data)

# Create Excel file with two worksheets
with pd.ExcelWriter('EP machine park 2025 bilingual.xlsx', engine='openpyxl') as writer:
    english_df.to_excel(writer, sheet_name='English', index=False, header=False)
    spanish_df.to_excel(writer, sheet_name='Spanish', index=False, header=False)

print('Excel file created successfully with English and Spanish worksheets!')