Stage 1 of 10 · 7 lessons · ~5 weeks
Python for data: NumPy and pandas
Set up notebooks and a clean environment, then learn the data frame work you will do every day: loading, selecting, filtering, grouping, joining and reshaping.
Start: Notebooks and a clean environmentLessons· one lesson for each topic, in this order
Do this
- Set up a notebook tool and a per-project environment, and put the project in Git.
- Load a public dataset and check its shape, types and first rows.
- Write filters for three different populations and state each one in plain words.
- Produce a summary per group with a count column next to every average.
- Join two tables and check the row count before and after.
- Reshape one table from wide to long and back.
Start with· follow one of these
- CoursePaidGrokking Python Fundamentals
Design Gurus · Beginner · $50
Solid Python basics first: data types, collections, functions and files, the ground pandas stands on
- CourseFreeKaggle Learn
Kaggle · Beginner
Free: the Python and Pandas courses, short lessons with exercises that run in the browser
Practise
Keep handy
Also worth your time
Before moving on: A notebook that loads a real public dataset, checks its types, filters it to one clear population, joins a second table with a row-count check, reshapes it, and prints three summary tables, all rerunnable from a clean start.
Do not try to learn the whole library. Twenty operations cover most real work: learn those until you can write them without searching, and look the rest up when you need them. Use a real dataset you care about from the first week, because toy examples never show you the messy parts.