Let me first parse the data and compute the correct numbers.
Rows: Let me enumerate them.
1001, 2025-01-06, Texas, widget, 1240.00 → Q1 Texas
1002, 1/9/2025, CA→California, gadget, 980 → Q1 California
1003, 2025-01-14, TX→Texas, gizmo, 312.50 → Q1 Texas
1004, Jan 21 2025, california→California, widget, 1764.00 → Q1 California
1005, 2025-01-27, Ohio, gadget, 455 → Q1 Ohio
1006, 2/3/2025, texas, widget, N/A → Q1 Texas, excluded amount
1007, 2025-02-10, OH→Ohio, gizmo, 1102.25 → Q1 Ohio
1008, Feb 14 2025, California, widget, 2310.00 → Q1 California
1009, 2025-02-18, TX→Texas, gadget, -450.00 → Q1 Texas refund
1010, 2025-02-24, Texas, gizmo, 870.10 → Q1 Texas
1011, 3/3/2025, Ohio, widget, 1999.99 → Q1 Ohio
1012, 2025-03-08, CA→California, gizmo, 640.00 → Q1 California
1008 duplicate → removed
1013, Mar 12 2025, tx→Texas, gadget, 1580.00 → Q1 Texas
1014, 2025-03-19, ohio→Ohio, gizmo, 225.75 → Q1 Ohio
1015, 2025-03-27, California, gadget, 3050.00 → Q1 California
1016, 4/2/2025, TX→Texas, widget, 990.00 → Q2 Texas
1017, 2025-04-07, Ohio, gadget, unknown → Q2 Ohio, excluded amount
1018, Apr 11 2025, CA→California, widget, 1420.50 → Q2 California
1019, 2025-04-16, Texas, gizmo, 2075.00 → Q2 Texas
1020, 2025-04-22, OH→Ohio, widget, 760.25 → Q2 Ohio
1021, 5/1/2025, California, gizmo, 1111.11 → Q2 California
1022, 2025-05-06, TX→Texas, gadget, 845.00 → Q2 Texas
1023, May 13 2025, Ohio, gizmo, -220.00 → Q2 Ohio refund
1024, 2025-05-19, texas→Texas, widget, 1300.00 → Q2 Texas
1025, 2025-05-28, CA→California, gadget, 2940.40 → Q2 California
1026, 6/4/2025, Ohio, widget, 515.00 → Q2 Ohio
1027, 2025-06-10, California, widget, 1875.25 → Q2 California
1028, Jun 17 2025, TX→Texas, gizmo, N/A → Q2 Texas, excluded
1029, 2025-06-23, OH→Ohio, gadget, 1660.00 → Q2 Ohio
1030, 2025-06-30, Texas, gadget, 730.90 → Q2 Texas
Rows received: count the data rows = let me count: 1001..1030 = 30 unique ids + 1 duplicate row (1008) = 31 rows total received. Duplicates removed = 1.
Rows after deduplication: 30. Excluded rows (invalid amount): 1006 N/A, 1017 unknown, 1028 N/A = 3 rows excluded from revenue. Rows counted = 27.
Now compute the pivot:
Q1:
Texas: 1001 1240.00 + 1003 312.50 + 1009 -450.00 + 1010 870.10 + 1013 1580.00 = 1240+312.50=1552.50; +(-450)=1102.50; +870.10=1972.60; +1580=3552.60
California: 1002 980 + 1004 1764 + 1008 2310 + 1012 640 + 1015 3050 = 980+1764=2744; +2310=5054; +640=5694; +3050=8744.00
Ohio: 1005 455 + 1007 1102.25 + 1011 1999.99 + 1014 225.75 = 455+1102.25=1557.25; +1999.99=3557.24; +225.75=3782.99
Q1 total: 3552.60 + 8744.00 + 3782.99 = 16079.59
Q2:
Texas: 1016 990 + 1019 2075 + 1022 845 + 1024 1300 + 1030 730.90 = 990+2075=3065; +845=3910; +1300=5210; +730.90=5940.90
California: 1018 1420.50 + 1021 1111.11 + 1025 2940.40 + 1027 1875.25 = 1420.50+1111.11=2531.61; +2940.40=5472.01; +1875.25=7347.26
Ohio: 1020 760.25 + 1023 -220 + 1026 515 + 1029 1660 = 760.25-220=540.25; +515=1055.25; +1660=2715.25
Q2 total: 5940.90 + 7347.26 + 2715.25 = 16003.41
Region totals:
Texas: 3552.60 + 5940.90 = 9493.50
California: 8744.00 + 7347.26 = 16091.26
Ohio: 3782.99 + 2715.25 = 6498.24
Grand total: 16079.59 + 16003.41 = 32083.00. Confirm via regions: 9493.50+16091.26+6498.24 = 9493.50+16091.26=25584.76; +6498.24=32083.00. ✓
Top region: California $16,091.26.
Now to write the HTML. The dashboard must compute from raw CSV embedded inside the JS. The raw CSV should be embedded as a string (preserving exact rows including the duplicate 1008). Note: the CSV contains quoted fields including commas inside quotes — need a proper CSV parser inside JS. E.g.: `"1,240.00"` and `"Jan 21, 2025"`.
Approach: embed the CSV as a template literal or a script tag with type="text/plain". Quoted fields contain commas; parse with a simple state machine.
Parsing amounts: strip $ , and whitespace; try parseFloat; if NaN → exclude. E.g., "N/A", "unknown". Actually strip $ and commas then Number() — but "N/A" contains a comma? "N/A" has no comma. Strip $ and commas then parseFloat, verify it's not NaN. Use regex: clean = amount.replace(/[$,]/g,'').trim(); then check /^-?\d+(\.\d+)?$/ then Number. That way N/A and unknown are excluded.
Date parsing: format ISO YYYY-MM-DD, M/D/YYYY, "Mon DD, YYYY". Parse to month. Quarter = ceil(month/3).
Region normalization: map lowercase and trimmed: {tx/texas→Texas, ca/california→California, oh/ohio→Ohio}.
Build the HTML with pivot table, SVG bar chart, data quality panel, headline. Compute everything in JS at load time.
Bar chart: grouped bars per region or totals per region. Spec: "Bar chart of revenue by region" — total revenue per region (or possibly grouped by quarter). Grouped bars with legend for quarter per region, plus totals? Keep it simple: grouped bars per region (Q1, Q2) — or just totals per region. Grouped is nicer and consistent. Actually simple: totals per region. Make it a canvas or inline SVG built in JS. Use SVG.
Write a CSV parser: state machine handling quotes.
Amount parsing: strip $ and commas, whitespace; try parseFloat; if NaN → exclude.
Date parsing: function parseDate(s): s = s.trim(); if match /^\d{4}-\d{2}-\d{2}$/ → month = parseInt(parts[1]); if match /^\d{1,2}\/\d{1,2}\/\d{4}$/ → month = parts[0]; else split by comma and month name from first token. Use Date parse fallback. Implement:
```
function monthOf(s){
s=s.trim();
let m;
if(m=/^\d{4}-\d{2}-/.exec(s)) return +s.slice(5,7);
if(m=/^(\d{1,2})\/\d{1,2}\/\d{4}$/.exec(s)) return +m[1];
// Month name
m=/^([A-Za-z]{3,})/.exec(s);
const names={jan:0,feb:2,mar:3,apr:4,may:5,jun:6,...};
return names[m[1].slice(0,3).toLowerCase()]+1;
}
```
Quarter = Math.ceil(month/3), only Q1 and Q2 in the data. Include a quarters array dynamically, but the spec says Q1=Jan-Mar, Q2=Apr-Jun, and the data only covers H1 2025. For completeness render columns from sorted quarters found.
Embedding CSV: use ``; the CSV doesn't contain it so it's fine. Use script type="text/plain".
CSV parse function:
```
function parseCSV(text){
const rows=[]; let row=[],field='',inQ=false,c;
for(let i=0;i1||row[0]!=='') rows.push(row); row=[]; }
else if(c==='\r'){}
else field+=c;
}
}
if(field!==''||row.length){ row.push(field); if(row.length>1||row[0]!=='') rows.push(row);}
return rows;
}
```
Amount parsing: strip $ and commas, whitespace; try parseFloat; if NaN → exclude.
Data quality: rows received = total data rows = 31. Duplicates removed = 1. Rows excluded = 3. Rows counted = 27.
Headline: "Top region: California — $16,091.26 total revenue".
Chart: SVG grouped bars per region per quarter, plus labels. Add axis line. Max value scale: max cell value = Q1 California 8744. Scale from that.
SVG design: width 520, height 260, chart area x from 60 to 500, y from 20 to 220. 3 regions × 2 bars. Group width = 440/3 ≈ 146. Bar width 40, gap 10. Max value scale based on max cell value.
Amount formatting: use Intl.NumberFormat('en-US',{style:'currency',currency:'USD'}).
Add negative-value styling to the table too. Also compute in JS so numbers are "computed correctly" — since they're computed from data at runtime, correct.
Sanity checks to display in the quality panel: rows received = rowsParsed (31), duplicates dropped, rows excluded, rows counted.
Now write the final HTML. Keep it reasonably styled.