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How Python is Tested

While SQL is essential for querying and manipulating data, some data analytics roles—especially senior or specialized positions—require Python for more advanced analysis, automation, and machine learning.

Python excels in areas where SQL falls short, such as:

  • Data cleaning and preprocessing beyond simple filtering and joins.
  • Statistical analysis and machine learning using libraries like pandas, scikit-learn, and statsmodels.
  • Automation and scripting to handle large-scale data workflows.
  • Data visualization for more flexible and customized charts beyond SQL-based BI tools.

If your job description explicitly requires Python, we recommend completing our Python Coding Questions for Data Scientists course to build a strong foundation and confidently tackle Python-based interview questions.

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