Skip to content
Learn Netverks

Track

pandas

Pandas

36 lessons: DataFrames, groupby, merges, time series—Python playground + 108 MCQs.

Mode
server_script
Practice
Server runner
Lessons
36 units
Start lesson 1 → Introduction to Pandas

Before you start

Pandas DataFrames: loading, cleaning, grouping, merging, and time-series operations.

Most day-to-day analyst work is tabular manipulation—Pandas is the default tool.

CSV/Parquet analysis, ETL notebooks, and ad hoc reporting.

Runnable Python snippets in lessons plus scenario-based MCQs.

After NumPy basics—when you work with real-world messy tables.

Lesson order

Sequential — follow top to bottom

36 lessons are live in this track. Start from step 01 for the smoothest path.

  1. 01 intro Introduction to Pandas

    beginner

    Open →
  2. 02 what-is-pandas What is Pandas?

    beginner

    Open →
  3. 03 pandas-vs-sql-preview Pandas vs SQL preview

    beginner

    Open →
  4. 04 pandas-ecosystem-preview Pandas ecosystem preview

    beginner

    Open →
  5. 05 pandas-workflow Pandas workflow

    beginner

    Open →
  6. 06 series-dataframe-intro Series and DataFrame intro

    beginner

    Open →
  7. 07 reading-csv-concept Reading CSV concept

    beginner

    Open →
  8. 08 columns-selection Column selection

    beginner

    Open →
  9. 09 indexing-loc-iloc Indexing with loc and iloc

    beginner

    Open →
  10. 10 dtypes-casting Dtypes and casting

    beginner

    Open →
  11. 11 missing-values-intro Missing values intro

    beginner

    Open →
  12. 12 filtering-rows Filtering rows

    beginner

    Open →
  13. 13 sorting-ranking Sorting and ranking

    beginner

    Open →
  14. 14 adding-columns Adding and transforming columns

    intermediate

    Open →
  15. 15 apply-map-replace Apply, map, and replace

    intermediate

    Open →
  16. 16 string-methods String methods

    intermediate

    Open →
  17. 17 datetime-basics Datetime basics

    intermediate

    Open →
  18. 18 groupby-intro GroupBy intro

    intermediate

    Open →
  19. 19 aggregations-groupby Aggregations with groupby

    intermediate

    Open →
  20. 20 pivot-melt Pivot and melt

    intermediate

    Open →
  21. 21 merge-join Merge and join

    intermediate

    Open →
  22. 22 concat-append Concat and append

    intermediate

    Open →
  23. 23 duplicate-handling Duplicate handling

    intermediate

    Open →
  24. 24 categorical-data Categorical data

    intermediate

    Open →
  25. 25 time-series-resample Time series resample

    intermediate

    Open →
  26. 26 rolling-windows Rolling windows

    intermediate

    Open →
  27. 27 performance-tips Performance tips

    advanced

    Open →
  28. 28 export-parquet-concept Export Parquet concept

    intermediate

    Open →
  29. 29 multi-index-preview MultiIndex preview

    advanced

    Open →
  30. 30 pandas-with-numpy Pandas with NumPy

    intermediate

    Open →
  31. 31 matplotlib-pandas-preview Matplotlib and Pandas preview

    intermediate

    Open →
  32. 32 sklearn-pandas-preview scikit-learn and Pandas preview

    intermediate

    Open →
  33. 33 scipy-pandas-teaser SciPy and Pandas teaser

    intermediate

    Open →
  34. 34 interview-essentials-pandas Interview essentials for Pandas

    intermediate

    Open →
  35. 35 production-checklist-pandas Production checklist for Pandas

    advanced

    Open →
  36. 36 scipy-bridge-lesson SciPy bridge lesson

    intermediate

    Open →