Descriptive Analysis of API Data

I have a series of JSON feeds that I pull directly from online APIs and now need them translated into clear, actionable insights. The scope is strictly descriptive: summary statistics, trends over time, key distributions, and any notable correlations that can be uncovered without predictive or prescriptive modelling.

The data arrive as raw JSON, so part of the assignment is to extract, clean, and structure these feeds efficiently—Python (pandas, NumPy), R (tidyverse), or any equivalent toolset is fine as long as the workflow is reproducible. Visual output matters; charts or dashboards that let a non-technical stakeholder grasp the story at a glance are essential.

Deliverables
• Reproducible code or notebooks that read the API endpoints, normalise the JSON, and store the tidy data
• A concise report (PDF, HTML, or slide deck) summarising the descriptive findings with clear visuals
• Exported, clean dataset in CSV or parquet for future use

Acceptance criteria
• All API calls handled with proper pagination/authentication where required
• No missing-value handling left undocumented
• Visuals labelled clearly, with sources and date stamps
• Scripts run end-to-end on my machine with minimal configuration

Feel free to recommend additional charts or summary metrics if they help illuminate the data story more effectively.

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