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Tools · Category

data science libraries, ranked by real usage_

As of 4 November 2026, NumPy leads data science libraries with 2,424 companies naming it in job postings, ahead of pandas at 2,322.

As of 4 November 2026 · refreshed daily · counts move as websites, DNS and career sites are re-read.

Leader
NumPy · 2,424
Runner-up
pandas · 2,322
Most hiring, 90 days
NumPy
Highest postings per company
SymPy
Catalogue
T-1.0.1-prov
8,756companies across the category
28%of them on NumPy
18,408postings naming a data science librarie in 90 days
29tools with enough evidence to rank
02 — Ranking

Every data science librarie we can measure

Companies naming the tool, and postings naming it in the last 90 days. Bars are relative to the leader.

#ToolCompaniescompaniesPostings, 90 dayspostingsper company
1
NumPyNumFOCUS
2,424
5,1932.1
2
pandasNumFOCUS
2,322
5,1872.2
3
MatplotlibMatplotlib
686
1,3512.0
4
SciPyNumFOCUS
520
1,0382.0
5
D3.jsD3
466
7651.6
6
PlotlyPlotly
290
6802.3
7
SeabornSeaborn
271
6592.4
8
PolarsPolars
219
4081.9
9
SnowparkSnowflake
172
5913.4
10
ProphetMeta
159
4072.6
11
Apache ArrowApache Software Foundation
149
3602.4
12
GeoPandasGeoPandas
121
1611.3
13
Recharts
109
1361.2
14
Chart.jsChart.js
102
1521.5
15
OR-ToolsGoogle
84
1431.7
16
Apache EChartsApache Software Foundation
65
1131.7
17
PyomoSandia National Laboratories
62
891.4
18
ShapelyShapely
62
741.2
19
ggplot2Posit
61
1702.8
20
HighchartsHighsoft
59
911.5
21
RDKit
57
851.5
22
Open3DOpen3D
54
721.3
23
Apple AccelerateApple
50
1603.2
24
Eigen
46
831.8
25
RasterioMapbox
42
491.2
26
PyArrowApache Software Foundation
34
601.8
27
Statsmodelsstatsmodels
31
581.9
28
xarrayxarray
29
331.1
29
SymPy
10
404.0
03 — Head to head

Compare two tools

Same data, two columns: who chooses which by size, industry and country.

NumPy vs pandas2,424 · 2,322NumPy vs Matplotlib2,424 · 686NumPy vs SciPy2,424 · 520NumPy vs D3.js2,424 · 466NumPy vs Plotly2,424 · 290pandas vs Matplotlib2,322 · 686pandas vs SciPy2,322 · 520pandas vs D3.js2,322 · 466pandas vs Plotly2,322 · 290Matplotlib vs SciPy686 · 520Matplotlib vs D3.js686 · 466Matplotlib vs Plotly686 · 290SciPy vs D3.js520 · 466SciPy vs Plotly520 · 290D3.js vs Plotly466 · 290
Cite this

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

NumPy leads data science libraries with 2,424 companies naming it in job postings, ahead of pandas at 2,322. (Breaknorm, 4 November 2026, https://breaknorm.co/tools/category/data-science-libraries)
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 →

  • CatalogueBreaknorm technology catalogue T-1.0.1-prov: 6,296 tools with vendor and category, editions folded into their parent.
  • CompaniesCompanies whose own postings name the tool as the team's system, any confidence. Candidate wish-lists excluded.
  • 90-day postingsOpen postings first seen or posted in the last 90 days that name the tool.
  • Not countedTools used by teams that do not post jobs, and companies without a career site we can read.
FAQ

data science libraries: questions

How is this ranking made?

By the number of companies whose own job postings name the tool as the team's system, from the Breaknorm technology catalogue (version T-1.0.1-prov). No vendor paid for a position and no editor chose the order.

Why is this different from review-site rankings?

Review sites rank by reviews collected. This ranks by companies hiring people to work in the tool, which is closer to seats in use. It under-counts tools used by teams that rarely post jobs.

What about product editions?

Editions and sub-products () are counted under the parent so no company is counted twice.

Can I get the companies behind a number?

Yes: click a tool, see the first 20, and sign up for the full list with verified e-mails. Counting is free.

Companies and people

Get the companies your way

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