Shipvane · 4 AE roles
Marco E. · joined Cargolio
Fleetora · first roles in DENumPy VS Plotly_
As of 4 November 2026, Plotly is named by 290 companies and NumPy by 2,424; NumPy skews to companies under 200 people (44% vs 40%), Plotly to companies over 1,000 (32% vs 31%).
As of 4 November 2026 · refreshed daily · counts move as websites, DNS and career sites are re-read.
The website-and-DNS footprint is not comparable between a marketing suite and a CRM: NumPy's script and mail records show on hundreds of thousands of small sites, Plotly rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- NumPy: 2–200 employees
- 44%
- Plotly: 2–200 employees
- 40%
- NumPy: 1,000+ employees
- 31%
- Plotly: 1,000+ employees
- 32%
- Postings per company, 90 days
- 2.1 · 2.3
- Website or DNS footprint
- 0 · 0
Who chooses which
Share of each tool's companies in every segment. "Leans" marks a gap of more than two points.
| Segment | NumPy | share | Plotly | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 105 | 4% | 19 | 7% | Plotly |
| 2-10 employees | 225 | 9% | 17 | 6% | NumPy |
| 11-50 employees | 385 | 16% | 37 | 13% | NumPy |
| 51-200 employees | 445 | 18% | 61 | 21% | Plotly |
| 201-500 employees | 315 | 13% | 37 | 13% | even |
| 501-1000 employees | 195 | 8% | 27 | 9% | even |
| 1001-5000 employees | 315 | 13% | 41 | 14% | even |
| 5001-10000 employees | 91 | 4% | 15 | 5% | even |
| 10,001+ employees | 348 | 14% | 36 | 12% | even |
| Segment | NumPy | share | Plotly | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 972 | 40% | 101 | 35% | NumPy |
| Business & finance services | 547 | 23% | 59 | 20% | NumPy |
| Manufacturing & industry | 343 | 14% | 47 | 16% | Plotly |
| Consumer services & leisure | 110 | 5% | 13 | 4% | even |
| Public, community & associations | 98 | 4% | 24 | 8% | Plotly |
| Media & content | 85 | 4% | 10 | 3% | even |
| Utilities & infrastructure | 83 | 3% | 12 | 4% | even |
| Commerce & trade | 54 | 2% | 6 | 2% | even |
| Automotive | 40 | 2% | 7 | 2% | even |
| Health care | 30 | 1% | 2 | 1% | even |
| Transport, logistics & rental | 26 | 1% | 6 | 2% | even |
| Property & construction | 21 | 1% | 3 | 1% | even |
| Segment | NumPy | share | Plotly | share | Leans |
|---|---|---|---|---|---|
| United States | 1,399 | 58% | 182 | 63% | Plotly |
| United Kingdom | 169 | 7% | 15 | 5% | even |
| India | 132 | 5% | 5 | 2% | NumPy |
| Germany | 99 | 4% | 8 | 3% | even |
| France | 75 | 3% | 11 | 4% | even |
| Canada | 49 | 2% | 11 | 4% | even |
| Spain | 35 | 1% | – | – | outside top 12 |
| Brazil | 30 | 1% | 6 | 2% | even |
| Italy | 24 | 1% | – | – | outside top 12 |
| Singapore | 24 | 1% | 5 | 2% | even |
| Poland | 22 | 1% | – | – | outside top 12 |
| Netherlands | 21 | 1% | – | – | outside top 12 |
| United Arab Emirates | – | – | 4 | 1% | outside top 12 |
| Portugal | – | – | 4 | 1% | outside top 12 |
| Austria | – | – | 3 | 1% | outside top 12 |
| Czechia | – | – | 3 | 1% | outside top 12 |
| Segment | NumPy | share | Plotly | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 4,240 | 60% | 572 | 67% | Plotly |
| Software engineering | 1,002 | 14% | 134 | 16% | even |
| Engineering (non-software) | 316 | 5% | 28 | 3% | even |
| Finance & accounting | 193 | 3% | 11 | 1% | even |
| research and science | 100 | 1% | 6 | 1% | even |
| IT operations & business systems | 82 | 1% | 2 | 0% | even |
| Legal, compliance & risk | 58 | 1% | 1 | 0% | even |
| Education & training | 42 | 1% | 2 | 0% | even |
| Unclassified | 33 | 0% | 3 | 0% | even |
| Marketing & communications | 22 | 0% | – | – | outside top 12 |
| General management & consulting | 19 | 0% | 2 | 0% | even |
| Product, program & project management | 19 | 0% | 3 | 0% | even |
| logistics warehouse and transport | 12 | 0% | – | – | outside top 12 |
| Quality, safety & environment | 10 | 0% | – | – | outside top 12 |
| Customer service & success | 8 | 0% | 2 | 0% | even |
| Sales | 8 | 0% | 3 | 0% | even |
| construction and civil | 6 | 0% | – | – | outside top 12 |
| Business development & strategy | 4 | 0% | – | – | outside top 12 |
| Design & UX | 3 | 0% | 5 | 1% | even |
| Human resources | 3 | 0% | – | – | outside top 12 |
| arts media and entertainment | 2 | 0% | 2 | 0% | even |
| public safety and protective services | 2 | 0% | – | – | outside top 12 |
| skilled trades and field service | 2 | 0% | – | – | outside top 12 |
| Administration & office | 1 | 0% | – | – | outside top 12 |
| agriculture and environment | 1 | 0% | – | – | outside top 12 |
| manufacturing and production | – | – | 1 | 0% | outside top 12 |
The companies behind each column
Companies using NumPy →
Companies using Plotly →
data science libraries ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
Plotly is named by 290 companies in job postings and NumPy by 2,424; 162 name both. (Breaknorm, 4 November 2026, https://breaknorm.co/compare/numpy-vs-plotly)
Read from the source, not self-reported
Every number on this page can be traced to a page we crawled or a posting we read. Full methodology →
- Job postingsRead hourly from career sites. A tool counts when the employer's own text names it as the team's system; both tools can count for one company.
- Website and DNSScripts and embeds on the company's pages, plus SPF, DKIM, MX and CNAME records of its domain that point at the vendor.
- SegmentsCountry, size and industry from the company profile built from its website.
- Not a reviewNo ratings, prices or feature claims. For those, read the vendors.
NumPy vs Plotly: questions
Which is more used, NumPy or Plotly?
By companies naming it in their own job postings, NumPy (2,424) over Plotly (290). By website-and-DNS footprint, Plotly (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses NumPy?
44% of NumPy companies have 2 to 200 employees, against 40% for Plotly. 31% of NumPy companies have over 1,000 employees, against 32% for Plotly.
Do companies run both?
162 companies name both in their postings, usually NumPy in marketing and Plotly in sales, or during a migration.
Where do these numbers come from?
From the employer's own text in job postings read hourly from career sites, and from scripts found on company websites in our crawl. No vendor data, no surveys.
Get either list your way
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with the person who owns it
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