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Python libraries - Pandas, NumPy, Matplotlib for data processing

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
Nihilent
Key Concepts Tested
etlpythonspark
Expert AnswerPremium
102 wordsInterview-ready
**Why Each Library:** Pandas—tabular ETL, missing data, time series; built on NumPy. NumPy—vectorized math, arrays; C-speed. Matplotlib—viz; use seaborn for stats plots. **Scalability Limits:** Pandas holds data in memory—~1M rows comfortably; 10M+ consider chunking, Dask, or Spark. NumPy scales to hundreds of MB for arrays. Matplotlib is single-process—use Datashader or plotly for big data viz. **Cost Trade-off:** Pandas on single node = cheap, fast for small data....
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