KASNEB DD31 — Python Data Visualisation | Theory Companion

A self-paced study companion for KASNEB DD31, with 28 lessons and 6 theory quizzes. Learn through explanations, worked examples, guided practice and answer checks.

What you will learn

• Write and check readable Python scripts.
• Import fictional tables and validate joins.
• Choose and interpret charts with accurate labels.
• Interpret statistical outputs and retain reproducible evidence.

Course coverage

Python syntax and environments; data import and merging; chart selection; descriptive statistics, distributions, tests and regression.

Practical study

Python and a permitted local environment with pandas, Matplotlib and SciPy for the relevant exercises. Use fictional data, preserve original inputs and retain calculations or code with independent checks. All worked-example inputs are supplied in the lessons.

Continue practical work at the DD31 Analytics Lab checkpoint, or use a permitted local calculation environment. Retain your own evidence files; opening a checkpoint is not a graded submission.

Assessment

Complete the topic checks and the eight-question final quiz. The final quiz allows three attempts, has a 20-minute limit and requires 70% to pass. Guided practical work is self-checked; this companion does not include instructor grading of uploaded practical files.

Official examination preparation

This is an independent study companion and does not award a KASNEB qualification or guarantee an examination result. Check the current syllabus and requirements for your sitting on the official KASNEB website. The course topic list is not a certification of complete current syllabus coverage.