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NumPy VS pandas_

As of 4 November 2026, pandas is named by 2,322 companies and NumPy by 2,424; NumPy skews to companies under 200 people (44% vs 45%), pandas to companies over 1,000 (30% 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, pandas rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.

NumPy: 2–200 employees
44%
pandas: 2–200 employees
45%
NumPy: 1,000+ employees
31%
pandas: 1,000+ employees
30%
Postings per company, 90 days
2.1 · 2.2
Website or DNS footprint
0 · 0
2,424companies name NumPy
2,322companies name pandas
1,982name both
5,193 · 5,187postings in 90 days, NumPy · pandas
02 — Side by side

Who chooses which

Share of each tool's companies in every segment. "Leans" marks a gap of more than two points.

By company size
SegmentNumPysharepandasshareLeans
Self-employed1054%1155%even
2-10 employees2259%26812%pandas
11-50 employees38516%33815%even
51-200 employees44518%42918%even
201-500 employees31513%28412%even
501-1000 employees1958%1978%even
1001-5000 employees31513%29513%even
5001-10000 employees914%924%even
10,001+ employees34814%30413%even
By industry
SegmentNumPysharepandasshareLeans
Technology & software97240%1,03945%pandas
Business & finance services54723%53423%even
Manufacturing & industry34314%23410%NumPy
Consumer services & leisure1105%1135%even
Public, community & associations984%733%even
Media & content854%793%even
Utilities & infrastructure833%653%even
Commerce & trade542%613%even
Automotive402%331%even
Health care301%241%even
Transport, logistics & rental261%311%even
Property & construction211%211%even
By country
SegmentNumPysharepandasshareLeans
United States1,39958%1,32657%even
United Kingdom1697%1697%even
India1325%1225%even
Germany994%994%even
France753%934%even
Canada492%452%even
Spain351%321%even
Brazil301%502%even
Italy241%––outside top 12
Singapore241%201%even
Poland221%221%even
Netherlands211%––outside top 12
Sweden––191%outside top 12
Switzerland––181%outside top 12
Postings by team (share of each tool's postings)
SegmentNumPysharepandasshareLeans
Data & AI4,24060%4,29062%even
Software engineering1,00214%1,02115%even
Engineering (non-software)3165%1682%NumPy
Finance & accounting1933%1622%even
research and science1001%651%even
IT operations & business systems821%1512%even
Legal, compliance & risk581%641%even
Education & training421%180%even
Unclassified330%330%even
Marketing & communications220%220%even
General management & consulting190%441%even
Product, program & project management190%441%even
logistics warehouse and transport120%150%even
Quality, safety & environment100%120%even
Customer service & success80%190%even
Sales80%340%even
construction and civil60%40%even
Business development & strategy40%40%even
Design & UX30%40%even
Human resources30%70%even
arts media and entertainment20%20%even
public safety and protective services20%––outside top 12
skilled trades and field service20%––outside top 12
Administration & office10%40%even
agriculture and environment10%10%even
Go deeper

The companies behind each column

Companies using NumPy →
Companies using pandas →
data science libraries ranked →

Cite this

Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.

pandas is named by 2,322 companies in job postings and NumPy by 2,424; 1,982 name both. (Breaknorm, 4 November 2026, https://breaknorm.co/compare/numpy-vs-pandas)
How we know

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.
FAQ

NumPy vs pandas: questions

Which is more used, NumPy or pandas?

By companies naming it in their own job postings, NumPy (2,424) over pandas (2,322). By website-and-DNS footprint, pandas (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 45% for pandas. 31% of NumPy companies have over 1,000 employees, against 30% for pandas.

Do companies run both?

1,982 companies name both in their postings, usually NumPy in marketing and pandas 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.

Companies and people

Get either list your way

The same data as a search, over MCP and the API, as bulk files, or pushed to you as it changes.

SearchCompany searchFilter on what a company actually does→SearchPeople searchDecision makers, normalized and verified→MCP and APICompanies over MCP and APICount, search and export from your agent→DatasetCompany and People datasetThe whole market in your warehouse→DataCoverage by countryCheck your market before you start→SearchLocal businessesThe same database, by category and city→

Every company on either tool,
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