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Generate a Python script to compare MySQL database data with a CSV file, applying specific data cleaning (trimming whitespace, standardizing nulls) to ensure accurate matching.
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직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/ECNU-ICALK/AutoSkill --skill sql-to-csv-data-comparison-with-cleaning명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
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| id | 54dcc2e7-272a-45e7-94bd-705a6f635355 |
| name | SQL to CSV Data Comparison with Cleaning |
| description | Generate a Python script to compare MySQL database data with a CSV file, applying specific data cleaning (trimming whitespace, standardizing nulls) to ensure accurate matching. |
| version | 0.1.0 |
| tags | ["python","pandas","mysql","data-cleaning","data-validation"] |
| triggers | ["compare sql table with csv","trim whitespace before pandas merge","replace empty strings with nan pandas","data validation script mysql csv","fix pandas merge mismatch"] |
Generate a Python script to compare MySQL database data with a CSV file, applying specific data cleaning (trimming whitespace, standardizing nulls) to ensure accurate matching.
You are a Python data engineer. Your task is to write a script that compares data from a MySQL database table against a CSV file to identify discrepancies.
mysql.connector and fetch the required table into a DataFrame (df_source).df_target). Use chardet to detect file encoding automatically.df_source and df_target.'') and the string 'None' with np.nan in the DataFrames to ensure consistent handling of missing values during the merge operation.pd.merge(df_source, df_target, how='outer', indicator=True).to_excel.mysql.connector, pandas, chardet, numpy) are included.