Let me parse the data carefully.

Rows (in order of appearance), with deduplication: keep the first occurrence of an order_id. 1008 appears twice → drop the second one (the row after 1012).

Rows after deduplication: total received rows = 31 data rows. Duplicates removed = 1. Remaining = 30 rows.

Excluded (non-numeric amounts): 1006 N/A, 1017 unknown, 1028 N/A → 3 excluded. Tally = 27.

Normalize regions: Texas, tx, TX, texas, california, CA, California → California, Ohio/OH/ohio → Ohio.

Next, compute revenue by region × quarter. All dates are in Q1 or Q2 of 2025.

Q1 rows (Jan–Mar):
1001 Texas 1240.00
1002 CA 980
1003 TX 312.50
1004 california 1764.00
1005 Ohio 455
1007 OH 1102.25
1008 California 2310.00
1009 TX -450.00
1010 Texas 870.10
1011 Ohio 1999.99
1012 CA 640.00
1013 tx 1580.00
1014 ohio 225.75
1015 California 3050.00

Q2 rows:
1016 TX 990.00
1018 CA 1420.50
1019 Texas 2075.00
1020 OH 760.25
1021 California 1111.11
1022 TX 845.00
1023 Ohio -220.00
1024 texas 1300.00
1025 CA 2940.40
1026 Ohio 515.00
1027 California 1875.25
1029 OH 1660.00
1030 Texas 730.90

Compute Texas Q1: 1240 + 312.50 + (-450) + 870.10 + 1580 = 1240+312.50=1552.50; -450 → 1102.50; +870.10=1972.60; +1580=3552.60.
Texas Q2: 990 + 2075 + 845 + 1300 + 730.90 = 990+2075=3065; +845=3910; +1300=5210; +730.90=5940.90.
Texas total: 3552.60+5940.90 = 9493.50.

California Q1: 980+1764+2310+640+3050 = 980+1764=2744; +2310=5054; +640=5694; +3050=8744.
California Q2: 1420.50+1111.11+2940.40+1875.25 = 1420.50+1111.11=2531.61; +2940.40=5472.01; +1875.25=7347.26.
California total: 8744+7347.26=16091.26.

Ohio Q1: 455+1102.25+1999.99+225.75 = 455+1102.25=1557.25; +1999.99=3557.24; +225.75=3782.99.
Ohio Q2: 760.25 + (-220) + 515 + 1660 = 760.25-220=540.25; +515=1055.25; +1660=2715.25.
Ohio total: 3782.99+2715.25=6498.24.

Q1 total: 3552.60+8744+3782.99 = 3552.60+8744=12296.60; +3782.99=16079.59.
Q2 total: 5940.90+7347.26+2715.25 = 5940.90+7347.26=13288.16; +2715.25=16003.41.
Grand total: 16079.59+16003.41=32083.00.

Sanity check: sum of all amounts: 9493.50+16091.26+6498.24 = 32083.00. Good.

Top region: California, $16,091.26.

The dashboard should compute these with JS from the embedded CSV. Write a single HTML file with an embedded CSV, a parser (handling quoted fields containing commas — dates like "Jan 21, 2025" and amounts like "1,240.00"), cleaning logic, and rendering.

Parsing dates: formats YYYY-MM-DD, M/D/YYYY, "Mon D, YYYY". Write a parser.

Parsing amounts: strip $, commas, spaces; parseFloat; if NaN → exclude.

CSV parser: handle double quotes.

Bar chart: SVG, one bar per region, using the revenue totals.

Alright, let me write the file. Keep it clean, with a bit of styling.

Code plan:

- Embed the CSV as a raw string in a <script type="text/plain" id="raw"> tag or a template.
- parseCSV(text): standard state machine handling quotes.
- Normalize regions: map lowercase and trimmed: tx/texas → Texas; ca/california → California; oh/ohio → Ohio.
- Parse dates: patterns.
- Aggregate.

Draw the pivot table, headline, quality panel, SVG bar chart.

Amount formatting: "$" + value.toLocaleString('en-US',{minimumFractionDigits:2,maximumFractionDigits:2}). Handle negative numbers like -$450.00 — a plain format is fine.

Bar chart: compute scale with max = max(regionTotals). Draw bars with labels and values. Use viewBox.

Write the final HTML.