Pandas curriculum

Start here — the syntax and mental models everything else builds on.

1. 1

   Series & DataFrames

   ~6 min · 1 lesson

   Load a table and inspect its shape, columns and types.

   DataFrameSeries.head().info()

   • Series and DataFramesup next6m
2. 2

   Selecting rows

   ~7 min · 1 lesson

   Filter and sort rows like a spreadsheet — but repeatably.

   .locboolean masks.query()sort_values

   • Filtering and sorting7m

Combine data from several places and reshape it into answers.

1. 1

   GroupBy & aggregation

   ~17 min · 2 lessons

   Summarise sales by category, country or month.

   groupbyaggassignapply

   • GroupBy and aggregation9m
   • Pipelines with assign and pipe8m
2. 2

   Merging & reshaping

   ~17 min · 2 lessons

   Merge tables and pivot data between long and wide.

   mergeconcatpivot_tablemelt

   • Merging and reshaping9m
   • MultiIndex basics8m
3. 3

   Cleaning data

   ~15 min · 2 lessons

   Fix missing values, duplicates and messy text.

   fillnadropnadrop_duplicates.str

   • Missing data and cleaning7m
   • Text and categorical columns8m

The techniques that show up in real interviews and real pipelines.

1. 1

   Time series

   ~26 min · 3 lessons

   Resample daily data to weekly and compute rolling averages.

   to_datetimeresamplerolling.dt

   • Datetime columns and indexes8m
   • Resampling9m
   • Rolling windows and shifts9m
2. 2

   Performance & scale

   ~17 min · 2 lessons

   Make big DataFrames fast and memory-friendly.

   vectorisedtypescategory

   • Vectorisation vs apply9m
   • Dtypes and memory8m