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Python Data Analysis Exercises for Beginners | Pandas Practice Jupyter Notebook

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Highlights

★ LEARN PYTHON FOR DATA ANALYSIS THE RIGHT WAY — BY DOING ★

5 beginner Python exercises as Jupyter Notebooks (.ipynb) with realistic sales datasets. Every notebook includes guided structure so you know exactly what to write.

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📦 WHAT'S INSIDE
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• Python_Beginner_Tasks.ipynb — 5 exercise notebooks with guided structure
• Python_Beginner_Solutions.ipynb — complete solutions
• README.txt

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📋 EXERCISES
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1. Python Basics — variables, loops, functions, list comprehensions
2. Pandas Intro — read_csv, head, info, describe, shape
3. Filtering & Selecting — boolean indexing, loc, iloc, isin
4. Data Cleaning — missing values, dtypes, rename, dt accessor
5. Basic Analysis — groupby, value_counts, sort_values, agg

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🎯 PERFECT FOR
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✔ Beginners learning Python for data science
✔ Students taking their first data analysis course
✔ Anyone switching from Excel to Python
✔ Job seekers preparing for data analyst interviews

⚙️ Requirements: Python 3.8+, pandas, numpy (free) + Jupyter Lab or VS Code
⏱ Estimated time: 60–90 minutes
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