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Course 117 · Digital course 24

Make a Data Analysis Someone Else Can Repeat

Turn a small fictional attendance analysis into a result another learner can reconstruct and explain.

Before you start

Complete Programming with Python or know functions, loops and dictionaries.

See everything you’ll need

Practice materials and a worked example · Free download. Download the starter pack

What you’ll leave with

An executable notebook and script that regenerate checked attendance totals, with raw data, an exclusion log, a data dictionary and a controlled rerun.

Start course Start without an account. Sign in to save lesson progress across devices.

Your project

Start with the practice files. Build your project one lesson at a time.

Practice files are free without an account. Sign in to save your project record in My Proof: a description, checklist, and optional work link. Keep the original files in your own app or notebook; saving a project record does not upload them.

  1. Get your materialsDownload practice filesStart with the supplied materials, follow the lessons, and compare your work with the annotated example.
  2. Make your projectView the project checklist Work in your own notebook, document, or software. Use the supplied practice examples when you prefer.
  3. Keep a private recordSave a project record Sign in to save a description and checklist, then return to update them.
Optional course overview

Watch an introduction.

This overview from Corey Schafer introduces ideas you’ll practice in the lessons.

Watch directly on YouTube
Corey SchaferJupyter Notebook Tutorial: Introduction, Setup, and WalkthroughYouTube
Course handbook

Know the route before you begin.

Here’s what you’ll need and what you’ll make. You can return to this guide during any lesson.

Who this is for

Learners age 14+ who meet the stated prerequisites.

Prepare before lesson one
  • Complete Programming with Python or know functions, loops and dictionaries.
  • Use free JupyterLab/Python 3; notebook setup is extra. Analysis uses only the Python standard library.
  • Reading and core practice include the three checks. Initial software setup and optional video viewing take extra time.
Your final project

Finish with proof you can use.

An executable notebook and script that regenerate checked attendance totals, with raw data, an exclusion log, a data dictionary and a controlled rerun.

Save a project record in My Proof
See project checklist and review criteria

Keep your working files in your own notebook or software. Save a private description, checklist, and work link in My Proof.

What to include

  • Question and inclusion rules.
  • Preserved input and four-field dictionary.
  • Executable analysis with exclusion reasons.
  • Checked site/total reconciliation and interpretation.
  • Clean-session baseline, correction test and complete handoff.

Review and revise

Use these criteria to check your work and choose what to improve.

  • The stated metric matches the code.
  • Exclusions and guards are explicit.
  • Clean runs reproduce expected totals.
  • The package contains enough information to rerun and interpret it.
Three ideas to help you along the way
Three useful ideas

The rules behind the steps.

01

Preserve evidence

Keep raw inputs unchanged and identify the version used.

02

Make decisions executable

Cleaning and exclusion rules belong in saved code and notes.

03

Rerun cleanly

Restarting exposes hidden state that old displayed outputs can conceal.

What do these words mean?
Key words

Key terms worth knowing.

Notebook
A document combining executable code, results and narrative.
Kernel
The process that runs notebook code and holds its variables.
Provenance
A record of where data came from and how it changed.
Assertion
An executable check that a stated condition holds.
Content hash
A fingerprint of file bytes used to identify exact content.
Your route

6 lessons.
One useful project.

Work in order the first time. Each lesson makes something the next lesson can use.

  1. 1
    Up next

    Define a reproducible question

    Specify the population, metric and exclusions before analysis.

  2. 2
    31 min

    Preserve and document inputs

    Separate raw input, executable analysis and generated output.

  3. 3
    31 min

    Make cleaning explicit in code

    Record exclusion reasons and reject unexpected values.

  4. 4
    31 min

    Combine code and explanation

    Connect notebook outputs to a precise narrative and independent checks.

  5. 5
    31 min

    Rerun from a clean session

    Regenerate results without relying on hidden notebook state.

  6. 6
    31 min

    Package a reproducible result

    Demonstrate a controlled input change and deliver the complete analysis dependencies.

Use the tools

Tools to help you practice.

See all tools
ZIP · practice files

Make a Data Analysis Someone Else Can Repeat practice files

Start with the supplied materials, follow the lessons, and compare your work with the annotated example.

Text worksheet

Your course project worksheet

A downloadable text worksheet with each lesson’s working output, space for your answers, and the shared final-project checklist. Save your own copy.

Source transparency

Sources and further study.

Explore the references behind the lessons and take your learning further. Source notes explain access and reuse.

Reproducible Science Curriculum: Modifying data
Source & access notes · checked 2026-09-12

Opened and inspected on 2026-09-12: Preserving raw data and recording transformations.

Access: Free public web page; no paid enrollment required.

Reuse: The linked curriculum license page identifies instructional material as CC BY 4.0. Link only; LifeStarter data, code and explanations are independently authored.

JupyterLab: Notebooks
Source & access notes · checked 2026-09-12

Opened and inspected on 2026-09-12: Code, Markdown and notebook execution.

Access: Free public web page; no paid enrollment required.

Reuse: Public reference; link only. LifeStarter prose, exercises and files are independently authored.

JupyterLab: Exporting Notebooks
Source & access notes · checked 2026-09-12

Opened and inspected on 2026-09-12: Notebook export options and dependencies.

Access: Free public web page; no paid enrollment required.

Reuse: Public reference; link only. LifeStarter prose, exercises and files are independently authored.

Reproducible Science Curriculum: Data and Project Organization
Source & access notes · checked 2026-09-12

Opened and inspected on 2026-09-12: Directory structure, metadata and project handoff.

Access: Free public web page; no paid enrollment required.

Reuse: The linked curriculum license page identifies instructional material as CC BY 4.0. Link only; LifeStarter data, code and explanations are independently authored.

Jupyter Notebook Tutorial: Introduction, Setup, and Walkthrough
Source & access notes · checked 2026-09-12

Metadata retrieved and inspected on 2026-09-12: exact title and channel confirmed through YouTube oEmbed. Playback and full video content were not tested. Optional overview; the written lesson and supplied practice stand alone.

Access: Free public web page; no paid enrollment required.

Reuse: Link or provider embed only; do not copy video, audio or transcript.

Ready when you are

Start with the first useful move.

You’ll always know what to do, what to make, and where to go next.

Start lesson one