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import pandas as pd
import os
from pathlib import Path
class ExcelToCsvConverter:
"""
Convert an Excel file to CSV files.
"""
def __init__(self, excel_path, output_dir=None):
self.excel_path = excel_path
self.output_dir = output_dir
def convert_excel_to_csv(excel_path, output_dir=None):
"""
Convert each sheet of an Excel file to a separate CSV file.
Args:
excel_path (str): Path to the Excel file
output_dir (str): Output directory for CSV files. If None, uses same directory as Excel file
"""
try:
# Set up output directory
if output_dir is None:
output_dir = os.path.dirname(excel_path)
# Create output directory if it doesn't exist
Path(output_dir).mkdir(parents=True, exist_ok=True)
# Read Excel file
excel_file = pd.ExcelFile(excel_path)
converted_files = []
for i, sheet_name in enumerate(excel_file.sheet_names, 1):
# Read the sheet
df = pd.read_excel(excel_path, sheet_name=sheet_name)
# Create a safe filename for the CSV
safe_filename = "".join(c for c in sheet_name if c.isalnum() or c in (' ', '-', '_')).rstrip()
#for specific sheet name, save the file name and use it later
self.sheet_name = sheet_name
self.safe_filename = safe_filename
safe_filename = safe_filename.replace(' ', '_')
csv_filename = f"{safe_filename}.csv"
csv_path = os.path.join(output_dir, csv_filename)
# Save as CSV
df.to_csv(csv_path, index=False, encoding='utf-8')
converted_files.append(csv_path)
print(f"✅ {i}. '{sheet_name}' → {csv_filename}")
print(f" - Saved {len(df)} rows, {len(df.columns)} columns")
print(f"\n🎉 Successfully converted {len(converted_files)} sheets to CSV files!")
return converted_files
except Exception as e:
print(f"❌ Error converting Excel to CSV: {e}")
return None
def convert_specific_sheet_to_csv(excel_path, sheet_name, output_dir=None):
"""
Convert a specific sheet of an Excel file to a CSV file.
"""
if output_dir is None:
output_dir = os.path.dirname(excel_path)
df = pd.read_excel(excel_path, sheet_name=sheet_name)
safe_filename = "".join(c for c in sheet_name if c.isalnum() or c in (' ', '-', '_')).rstrip()
safe_filename = safe_filename.replace(' ', '_')
csv_filename = f"{safe_filename}.csv"
csv_path = os.path.join(output_dir, csv_filename)
df.to_csv(csv_path, index=False, encoding='utf-8')
print(f"✅ {sheet_name} → {csv_filename}")
return csv_path
def main():
"""Main function to analyze and convert Excel file"""
# Define paths
excel_path = "data/real_data_excel/AI Project document.xlsx"
output_dir = "data/real_data_excel/converted_csv"
# Check if Excel file exists
if not os.path.exists(excel_path):
print(f"❌ Excel file not found: {excel_path}")
return
print("=" * 60)
print("📊 EXCEL TO CSV CONVERTER")
print("=" * 60)
# Step 1: Analyze Excel structure
sheet_info = analyze_excel_structure(excel_path)
if sheet_info is None:
return
# Step 2: Convert to CSV
converted_files = convert_excel_to_csv(excel_path, output_dir)
if converted_files:
print("\n📂 Converted files:")
for file_path in converted_files:
print(f" - {file_path}")
if __name__ == "__main__":
main() |