65 lines
2.3 KiB
Python
65 lines
2.3 KiB
Python
# import pandas as pd
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# def normalize_row(row):
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# return tuple(
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# str(cell).strip().replace(".0", "") if isinstance(cell, float) and cell.is_integer() else str(cell).strip()
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# for cell in row
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# )
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# def find_unmatched_rows(sheet1_df, sheet2_df):
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# # Ensure column names are clean
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# sheet1_df.columns = sheet1_df.columns.str.strip()
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# sheet2_df.columns = sheet2_df.columns.str.strip()
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# # Normalize rows for comparison
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# sheet1_normalized = sheet1_df.apply(normalize_row, axis=1)
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# sheet2_normalized = sheet2_df.apply(normalize_row, axis=1)
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# # Find unmatched rows
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# unmatched_in_sheet1 = sheet1_df[~sheet1_normalized.isin(sheet2_normalized)]
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# unmatched_in_sheet2 = sheet2_df[~sheet2_normalized.isin(sheet1_normalized)]
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# # Mark source
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# unmatched_in_sheet1["Source"] = "Sheet1"
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# unmatched_in_sheet2["Source"] = "Sheet2"
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# # Combine
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# unmatched_combined = pd.concat([unmatched_in_sheet1, unmatched_in_sheet2], ignore_index=True)
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# return unmatched_combined
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import pandas as pd
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def normalize_row(row):
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return tuple(
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str(cell).strip().replace(".0", "") if isinstance(cell, float) and cell.is_integer() else str(cell).strip()
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for cell in row
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)
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def find_unmatched_rows(sheet1_df, sheet2_df):
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# Clean column names
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sheet1_df.columns = sheet1_df.columns.str.strip()
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sheet2_df.columns = sheet2_df.columns.str.strip()
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# Choose the comparison columns
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comparison_columns = ['Date', 'GSTIN/UIN']
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# Ensure required columns exist
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for col in comparison_columns:
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if col not in sheet1_df.columns or col not in sheet2_df.columns:
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raise ValueError(f"Missing column '{col}' in one of the sheets.")
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# Create keys for comparison
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sheet1_keys = sheet1_df[comparison_columns].apply(normalize_row, axis=1)
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sheet2_keys = sheet2_df[comparison_columns].apply(normalize_row, axis=1)
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# Find unmatched rows
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unmatched_in_sheet1 = sheet1_df[~sheet1_keys.isin(sheet2_keys)].copy()
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unmatched_in_sheet2 = sheet2_df[~sheet2_keys.isin(sheet1_keys)].copy()
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# Mark source
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unmatched_in_sheet1["Source"] = "Sheet1"
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unmatched_in_sheet2["Source"] = "Sheet2"
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# Combine
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unmatched_combined = pd.concat([unmatched_in_sheet1, unmatched_in_sheet2], ignore_index=True)
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return unmatched_combined
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