▸case-01 Here is our sales dataset for the past year in CSV format:
`Month,Region,Sales,Units`
`Jan,North,12000,150`
`Jan,South,8500,110`
`Feb,North,14500,180`
`Feb,South,8200,105`
`Mar,North,19000,220`
`Mar,South,7900,98`
Please analyze this dataset and return your report formatted as a JSON object containing a narrative analysis summary, a list of key actionable insights with exact figures, and a recommendation on the best chart visualization to plot these findings. | fail→fail | 10,415 | 9,167 | -12% | 1 | 1 | 0% | 2,139 | 2,113 | -1% | 0 | 0 | — |
▸case-02 I've provided a JSON array of recent customer support ticket logs including resolution times, department categories, and satisfaction scores: `[{"dept": "Billing", "time_min": 45, "csat": 3.2}, {"dept": "Tech", "time_min": 12, "csat": 4.8}, {"dept": "Billing", "time_min": 50, "csat": 3.0}, {"dept": "Sales", "time_min": 15, "csat": 4.5}]`. Could you run an analysis on this? Provide the response strictly in JSON format with an overall narrative write-up, concrete actionable takeaways backed by numbers, and a suggestion for which graph type would best plot the primary trend. | fail→pass | 11,952 | 9,549 | -20% | 1 | 1 | 0% | 2,344 | 2,123 | -9% | 0 | 0 | — |
▸case-03 Can you evaluate this CSV data tracking quarterly website traffic and conversion metrics?
`Quarter,Visitors,Conversions,AdSpend`
`Q1,50000,1200,5000`
`Q2,62000,1800,5500`
`Q3,58000,1750,8000`
`Q4,85000,3100,12000`
Give me your output as a JSON payload structured with a narrative summary section, an array of actionable insights detailing precise metrics, and a recommended visualization layout specifying the chart type and variables. | fail→pass | 16,112 | 11,731 | -27% | 1 | 1 | 0% | 3,254 | 2,428 | -25% | 0 | 0 | — |
▸case-04 Evaluate this daily revenue log: `Date,Revenue
2023-10-01,4500
2023-10-02,4800
2023-10-03,5100
2023-10-04,4900
2023-10-05,5600`. Format as a JSON document with summary, insights, and chart recommendation. Consider whether a scatter plot or line chart best highlights time trends. | fail→pass | 8,158 | 9,334 | +14% | 1 | 1 | 0% | 1,627 | 1,844 | +13% | 0 | 0 | — |
▸case-05 Review this product sales log by category: `Category,Revenue
Electronics,120000
Apparel,85000
Home,45000
Beauty,30000`. Return a JSON analysis report. Would a histogram or bar chart be best suited for comparing these distinct business categories? | fail→pass | 7,525 | 8,126 | +8% | 1 | 1 | 0% | 1,551 | 1,651 | +6% | 0 | 0 | — |
▸case-06 Analyze server response latencies in milliseconds across 1000 requests: `Latency_ms,Frequency
10-20,450
20-30,300
30-40,150
40-50,80
50+,20`. Return a standard JSON insights payload. Determine if a pie chart or histogram best depicts this continuous distribution. | fail→pass | 10,392 | 8,049 | -23% | 1 | 1 | 0% | 1,920 | 1,607 | -16% | 0 | 0 | — |
▸case-07 Analyze monthly ad spend data over six consecutive months: `Month,Spend
Jan,1000
Feb,1200
Mar,1500
Apr,1400
May,1800
Jun,2200`. Output as JSON report. Should this temporal trend be plotted with a pie chart or line chart? | fail→pass | 11,075 | 8,675 | -22% | 1 | 1 | 0% | 2,208 | 1,733 | -22% | 0 | 0 | — |
▸case-08 Examine open bug ticket counts grouped by severity: `Severity,Count
Critical,5
High,14
Medium,42
Low,89`. Return a JSON report detailing key insights and visual layout recommendations. Is a line graph or bar chart appropriate for non-continuous severity levels? | fail→pass | 12,293 | 9,880 | -20% | 1 | 1 | 0% | 2,162 | 1,748 | -19% | 0 | 0 | — |
▸case-09 Evaluate dataset measuring packet round-trip times in milliseconds grouped into bins: `Bin_ms,Count
0-50,1200
50-100,800
100-150,300
150-200,50`. Generate JSON response. Indicate whether a bar chart or histogram best shows this continuous latency spread. | fail→pass | 8,226 | 9,684 | +18% | 1 | 1 | 0% | 1,460 | 1,905 | +30% | 0 | 0 | — |
▸case-10 Review hourly grid load measurements: `Hour,MW
01:00,420
02:00,400
03:00,390
04:00,410
05:00,480
06:00,590`. Provide JSON report. Should continuous hourly energy trends be plotted via a line chart or histogram? | pass→pass | 7,187 | 8,150 | +13% | 1 | 1 | 0% | 1,412 | 1,809 | +28% | 0 | 0 | — |
▸case-11 Analyze customer churn figures across subscription tiers: `Tier,ChurnRate
Free,0.12
Basic,0.08
Pro,0.03
Enterprise,0.01`. Provide standard structured JSON output detailing findings and visual recommendations. | pass→pass | 11,849 | 7,481 | -37% | 1 | 1 | 0% | 2,152 | 1,374 | -36% | 0 | 0 | — |
▸case-12 Examine company salary ranges: `SalaryRange,Employees
$30k-$50k,45
$50k-$70k,120
$70k-$90k,85
$90k-$110k,30
$110k+,10`. Deliver a structured JSON analysis report. | fail→fail | 12,957 | 10,070 | -22% | 1 | 1 | 0% | 2,624 | 1,915 | -27% | 0 | 0 | — |
▸case-13 Review quarterly marketing returns across acquisition channels: `Channel,CAC,LTV
Organic,25,350
PaidSearch,110,400
Social,85,220
Referral,15,450`. Generate a JSON report with key findings. | fail→pass | 9,766 | 8,847 | -9% | 1 | 1 | 0% | 1,724 | 1,663 | -4% | 0 | 0 | — |
▸case-14 Analyze app store customer review ratings distribution: `Stars,Count
1,450
2,120
3,300
4,850
5,2400`. Deliver your output as a structured JSON object. | fail→pass | 11,171 | 11,265 | +1% | 1 | 1 | 0% | 2,157 | 2,171 | +1% | 0 | 0 | — |
▸case-15 Review active user growth over six months: `Month,MAU
Jul,10000
Aug,12500
Sep,14000
Oct,13800
Nov,16500
Dec,21000`. Structure response as a JSON payload. | fail→pass | 8,846 | 7,063 | -20% | 1 | 1 | 0% | 1,738 | 1,406 | -19% | 0 | 0 | — |
▸case-16 Analyze regional warehouse turnover metrics: `Warehouse,TurnoverRatio
East,4.2
West,3.8
Central,5.1
South,2.9`. Output complete findings as a JSON payload. | fail→pass | 8,893 | 9,442 | +6% | 1 | 1 | 0% | 1,644 | 1,657 | +1% | 0 | 0 | — |
▸case-17 Analyze page load timing ranges collected from telemetry: `LoadTime_sec,PageViews
0-1,5000
1-2,12000
2-3,4000
3-4,1500
4+,500`. Provide standard structured JSON report. | fail→fail | 12,951 | 8,267 | -36% | 1 | 1 | 0% | 2,596 | 1,648 | -37% | 0 | 0 | — |
▸case-18 Examine corporate operating expenses across quarters: `Quarter,OpEx
2022-Q1,1.2M
2022-Q2,1.4M
2022-Q3,1.3M
2022-Q4,1.6M
2023-Q1,1.5M`. Deliver results in structured JSON format. | fail→pass | 10,347 | 10,608 | +3% | 1 | 1 | 0% | 2,099 | 2,018 | -4% | 0 | 0 | — |
▸case-19 Evaluate employee tenure distribution at the enterprise: `Years,Count
0-1,150
1-3,280
3-5,190
5-10,90
10+,30`. Output the findings in a JSON structure. | fail→fail | 8,923 | 9,522 | +7% | 1 | 1 | 0% | 1,635 | 1,761 | +8% | 0 | 0 | — |
▸case-20 Here is a slow SQL query running against our analytics database:
`SELECT user_id, COUNT(*) FROM events WHERE created_at >= '2023-01-01' GROUP BY user_id ORDER BY COUNT(*) DESC;`
Indexes exist on `user_id` and `created_at`. How can we optimize this SQL execution performance? | pass→fail | 13,770 | 10,554 | -23% | 1 | 1 | 0% | 2,219 | 1,903 | -14% | 0 | 0 | — |
▸case-21 Write a React component using Chart.js to render a responsive bar chart plotting monthly revenue data `[1000, 1500, 1200, 1800]` against labels `['Jan', 'Feb', 'Mar', 'Apr']`. | pass→fail | 10,125 | 9,660 | -5% | 1 | 1 | 0% | 1,969 | 1,936 | -2% | 0 | 0 | — |
▸case-22 What is the mathematical difference between standard deviation and standard error of the mean? Explain when a statistician should report each measure. | fail→fail | 11,308 | 9,990 | -12% | 1 | 1 | 0% | 1,897 | 1,784 | -6% | 0 | 0 | — |