Python for Data Analysis
pandas, cleaning, and getting a messy dataset into a state you can trust
Created by Priya Raghunathan
What you will learn
- Load data from CSV, Excel, JSON and SQL into pandas
- Clean missing, duplicated and inconsistently coded values deliberately
- Reshape data between wide and long formats without losing track
- Group, aggregate and join datasets correctly
- Produce clear exploratory charts
- Document an analysis so someone else can reproduce it
Course content
14 sections · 162 lectures · 24h total length
- What this course covers, and what it does notPreview03:00
- How to get the most out of itPreview04:00
- Setting up and downloading the exercise files06:00
- Python for analysts, a refresherPreview04:00
- Python for analysts, a refresher in detail09:00
- A closer look at python for analysts, a refresher08:00
- Worked example: python for analysts, a refresher12:00
- Where python for analysts, a refresher goes wrong11:00
- Exercise: python for analysts, a refresher03:00
- Python for analysts, a refresher in practice15:00
- Two approaches to python for analysts, a refresher07:00
- Python for analysts, a refresher — questions from previous students15:00
- Reviewing your work on python for analysts, a refresher07:00
- Python for analysts, a refresher — the edge cases07:00
- A second worked example: python for analysts, a refresher11:00
- Applying python for analysts, a refresher to your own project03:00
- When python for analysts, a refresher is not enough08:00
Topics covered
Requirements
- Basic Python — loops, functions, lists and dictionaries
- No statistics background required
- Anaconda or a Python environment (setup is covered)
Description
Real data arrives inconsistent, incomplete and badly labelled, and most of the job is dealing with that. This course spends its time where the work actually is: loading, cleaning, reshaping and validating data, with analysis as the reward at the end.
Your instructor
Data scientist working in health research
Priya moved from academic statistics into applied health data and has never lost the habit of asking what a number actually measures. Expect a lot of attention to how data is collected before any model appears.
Learner reviews
- 5 star73%
- 4 star22%
- 3 star3%
- 2 star1%
- 1 star1%
- DDDmitri D.21 January 2026
Very practical. I applied something from module four at work the same week.
- IWIngrid W.11 March 2026
Genuinely well structured. I have started three courses on this topic and this is the first one I finished.
- JLJonas L.20 November 2025
Concise and honest about what it does not cover, which I appreciated.
- SOSam O.16 January 2026
Useful, though it assumes a bit more background than the description suggests.
- ODOlive D.15 April 2026
Excellent. The examples are realistic rather than the usual toy versions.
- OROlive R.25 December 2025
Genuinely well structured. I have started three courses on this topic and this is the first one I finished.
- SLSam L.16 March 2026
Good balance between theory and doing. I would have liked a couple more exercises, but that is a small complaint.
- COCarla O.12 May 2026
The instructor answers questions properly rather than pointing you at the documentation.
- CNCarla N.28 December 2025
Very practical. I applied something from module four at work the same week.
Showing 9 of 9,315 reviews.
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