Indicators (clean)
Clean ESG/campus/operations indicators across several entities and periods: entity_id, period, category, metric, value, unit, denominator, source_note. Used for the Guided Lab.
DS 103 Practice Center
Use a synthetic ESG and operations indicator dataset to practice chart choice, axis integrity, accessibility, evidence statements, and dashboard prioritization.
Info
DS 103 practice data is synthetic teaching data. All entity names and values are illustrative and do not represent any real organization.
Warning
Use only the synthetic files provided for practice. Unless authorized, never paste confidential institutional or company data, personal data, or sensitive data into an AI tool; confirm your institution's rules before using real internal operations data.
Download the practice files
Indicators (practice, with challenges)
The same schema with intentional chart-design challenges: a metric with a natural zero baseline, a pair of metrics on very different scales, and a category best shown by shade or pattern alone. Used for the Practice Center and the Independent Lab.
資料字典（繁體中文）
Column type, unit, grain, allowed values and provenance for the indicators file, in Traditional Chinese.
Data dictionary (English)
English data dictionary; columns and units match the Chinese version.
Guided Lab starter notebook
A starter notebook with guidance and TODOs that runs top to bottom from a fresh kernel, producing three evidence charts.
Independent Lab starter notebook
A starter notebook and checklist template for the Evidence-Based Data Story.
Practice tasks
Practice A: Chart Choice Match
The practice data includes a comparison, a trend, and a distribution question about the same indicators. Match each question to the chart family that answers it, and note why the alternatives would distort or hide the comparison.
Files used: Indicators (practice, with challenges), Data dictionary (English)
Steps
- Load DS103_Indicators_Practice.csv and pick one metric with 5+ entities in one period.
- State the analytical question (comparison, trend, or distribution) each chart should answer.
- Choose a bar chart, line chart, or histogram accordingly, and sketch or build it.
- Write one sentence on why a pie chart or a 3-D chart would be a worse choice for this question.
What you produce
- One stated analytical question per chart
- One chart of the matched family
- A one-sentence rejection of a worse chart type
Practice B: Axis Integrity Review
One metric in the practice data has a natural zero baseline. Build a bar chart that starts at zero and one that does not, and compare how the same numbers look.
Files used: Indicators (practice, with challenges), Data dictionary (English)
Steps
- Pick a metric with a natural zero baseline (for example a count or an amount).
- Build a bar chart with the y-axis starting at 0.
- Build the same chart with the y-axis starting above 0, and note how the visual gap changes.
- Check whether a log scale would be appropriate for any other metric in the file, and state why or why not.
What you produce
- Two versions of the same bar chart (zero and non-zero baseline)
- A written comparison of the visual difference
- A judgment on log-scale suitability for one other metric
Practice C: Accessibility Repair
Build a chart that encodes a status category only by color, then repair it so the meaning survives grayscale printing and does not rely on color alone.
Files used: Indicators (practice, with challenges), Data dictionary (English)
Steps
- Build a chart that uses only red/green (or similarly close hues) to encode a status category.
- View or print the chart in grayscale and confirm the categories become hard to tell apart.
- Repair it with a direct label, a pattern, or a shape in addition to color.
- Write a one-sentence text summary of the chart suitable as an accessible alternative.
What you produce
- A before/after pair of the repaired chart
- A grayscale check result
- A one-sentence accessible text summary
Practice D: Evidence Statement Rewrite
Take an overstated claim about the practice data and rewrite it as an evidence statement that stays inside what the data can support.
Files used: Indicators (practice, with challenges), Data dictionary (English)
Steps
- Read the overstated claim provided with the practice data (or write one yourself from a chart you built).
- Identify which part is a fact directly readable from the data, and which part is interpretation.
- Rewrite the claim so it separates observation, interpretation, and what remains unknown.
- State one thing that would need to be checked before treating the claim as a causal statement.
What you produce
- The original overstated claim
- The rewritten evidence statement
- One stated verification need
Practice E: Dashboard Prioritization
Given eight candidate KPIs from the indicators file, choose the 3-4 that belong on an overview and design one drill-down path.
Files used: Indicators (practice, with challenges), Data dictionary (English)
Steps
- List eight candidate KPIs from the practice data.
- Select the 3-4 KPIs that best answer the audience's primary question, and justify the cut.
- Design one drill-down: what a viewer clicks or asks next after seeing the overview.
- Note one KPI you excluded and why including it would cause overload.
What you produce
- A prioritized list of 3-4 overview KPIs with justification
- One documented drill-down path
- One excluded KPI with a stated reason
The done mark is stored in this browser only (and synced once you join a cohort). Keep your work in your own files or notebook.