Performance Data Visualization

I analyzed a dataset showing average position values from 0.17 to 1.00 across 20 time periods. This data demonstrates clear progression over time.


https://datawrapper.dwcdn.net/SxPyS/1/

The ranking chart shows later time periods achieved higher positions, with period T reaching 1.00 and period A starting at 0.17.



https://datawrapper.dwcdn.net/w7mYM/1/

The pie chart reveals most periods performed moderately (grouped as "Other"), while only four periods achieved top performance.

Part-to-Whole Reflection

Part-to-whole charts clearly show proportions and relationships between components. However, they make it difficult to compare small segments precisely and can hide individual details when data gets grouped into "Other" categories.


Design Choice: I selected a column chart for ranking because it clearly orders performance from highest to lowest, making comparisons easy. For part-to-whole, I chose a pie chart because it shows how individual time periods contribute proportionally to the total dataset."

Framework Insights: The ranking framework revealed the sequential progression of performance over time, highlighting which specific periods performed best. The part-to-whole framework showed a different insight, that exceptional performance was rare, with most periods clustered in moderate performance levels."

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