Python for Data Analysts
🐍 Python for Data Analysts
Python is the second most important skill for data analysts after SQL. It's what separates analysts who can clean a spreadsheet from analysts who can build a full automated reporting pipeline.
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Why Python for Data Analysis?
- Automation — stop doing the same report manually every Monday
- Scale — analyse millions of rows that would crash Excel
- Flexibility — join, reshape, and clean data in ways no spreadsheet can
- Visualisation — Matplotlib and Seaborn produce publication-quality charts
- Career value — Python adds an average 12–22% salary premium for analysts
Python Learning Path for Analysts
- Week 1: Python Basics — Variables, loops, functions, lists, dictionaries
- Week 2: Pandas Fundamentals — Loading data, filtering, selecting, cleaning nulls
- Week 3: Pandas Advanced — GroupBy, merge, pivot tables, apply()
- Week 4: Visualisation — Matplotlib line charts, Seaborn bar charts, heatmaps
- Week 5: NumPy + Stats — Arrays, mean, median, std, percentiles
- Week 6: Real Projects — Sales analysis, RFM segmentation, weekly report automation
Essential Pandas Code Reference
| Task | Code |
|---|---|
| Load CSV | df = pd.read_csv('file.csv') |
| Filter rows | df[df['salary'] > 60000] |
| Group and aggregate | df.groupby('dept')['salary'].mean() |
| Handle missing values | df.fillna(df.mean()) |
| Sort values | df.sort_values('revenue', ascending=False) |
| Merge dataframes | pd.merge(df1, df2, on='id', how='left') |
| Export to Excel | df.to_excel('output.xlsx', index=False) |
Free Python Learning Resources
- 💻 Kaggle's Python Course — free, interactive, beginner-friendly
- 💻 Pandas Official Tutorials — straight from the source
- 💻 Real Python — excellent articles and tutorials for every level
- 💻 Corey Schafer on YouTube — best free Python video tutorials available
Get the Full Python Ebook
Our Python for Data Analysis ebook covers everything on this page in full depth — with code examples, exercises, and 3 complete end-to-end projects you can put on your portfolio.