If you’re preparing for your first data analyst role, one tool you can’t ignore is Python. It’s the most popular language in analytics because it’s beginner-friendly and powerful enough to handle real-world datasets.
Most recruiters hiring freshers won’t test you on advanced machine learning. Instead, they’ll check if you can:
Work with files like CSV and Excel.
Clean and manipulate messy data.
Use Pandas and NumPy at a basic level.
Create simple visualisations to explain results.
Mastering these will already put you ahead of many candidates.
Common Python Questions in Data Analyst Interviews
Here are some entry-level questions you should definitely practise:
What is Python, and why is it used in data analytics?
Difference between Lists, Tuples, and Dictionaries.
What is Pandas, and what are DataFrames?
How to deal with missing values using dropna() and fillna().
Difference between .loc[] and .iloc[] in Pandas.
Why Python is more reliable than Excel for larger datasets.
Quick Tip for Freshers
Along with Python, practise SQL queries and build small projects (like analysing sales reports or survey data). This shows recruiters that you can apply theory to actual business problems.
Final Thoughts
Python is the foundation for starting a career in data analytics. Once you’re comfortable with it, moving to advanced tools and techniques will be much easier.
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