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Home/Questions/Python/Coding/Read data from three files into a Pandas DataFrame, perform transformations, remove columns, filter rows, search for strings

Read data from three files into a Pandas DataFrame, perform transformations, remove columns, filter rows, search for strings

Python/Codingeasy0.5 min readPremium
Frequency
Low
Asked at 1 company
Category
179
questions in Python/Coding
Difficulty Split
127E|24M|28H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
JP Morgan
Key Concepts Tested
etl
Expert AnswerPremium
98 wordsInterview-ready
**Why This Pattern:** Multi-file concat + transform + filter is the core ETL pattern. At JP Morgan, regulatory data often comes as daily files—concat, validate, filter, load. **Scalability:** pd.concat([df1,df2,df3]) loads all into memory. For 3 large files: read each with chunksize, concat chunks, process incrementally. Or use Dask for out-of-core....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like JP Morgan. The answer also includes follow-up discussion points that interviewers commonly explore.

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