Data tiles

Data tiles: patterns generated from real data

Every Gomes Code project gets a tile generated from its own data. The function is deterministic: the same numbers always draw the same pattern. Each value becomes a petal, the bars along the edge repeat the values to scale, and the module is mirrored and rotated as in traditional azulejo work.

Gomes Code

Six presidential runoffs, 2002–2022

National share of valid votes for the PT candidate in every presidential runoff since 2002. It is the brand pattern, used on pages without their own case.

Data (6)

Six presidential runoffs, 2002–2022
Data	% of valid votes
2002 · Lula	61.3
2006 · Lula	60.8
2010 · Dilma	56.1
2014 · Dilma	51.7
2018 · Haddad	44.9
2022 · Lula	50.9

Source: TSE municipal results, processed by Urna, retrieved 2026-10-13

RK Barbearia

RK's price list

The 13 services on the shop's public price list, grouped into haircut, beard and other. Each value is the service price.

Data (13)

RK's price list
Data	BRL
Combo (corte e barba c/ lavagem)	125
Combo (corte e barba s/ lavagem)	120
Corte c/ lavagem	65
Corte sem lavagem	60
Corte 1 máquina	50
Raspagem	70
Acabamento	25
Barboterapia	80
Barba completa	60
Barba express	50
Sobrancelha	25
Depilação nariz	25
Depilação orelha	25

Source: RK Barbearia's public website, retrieved 2026-10-13

Gomes Code product

InkFlow lines of code by language

Non-blank source lines by language, counted in the repository (src and wasm folders).

Data (3)

InkFlow lines of code by language
Data	lines
TSX (interface)	3,555
TypeScript (logic)	2,437
C++ (drawing engine)	74

Source: InkFlow repository, retrieved 2026-10-13

Gomes Code original project

2022 runoff by region

Lula's share of valid votes in each region in the 2022 presidential runoff.

Data (5)

2022 runoff by region
Data	% of valid votes
North	49
Northeast	69.3
Center-West	39.8
Southeast	45.7
South	38.2

Source: TSE municipal results, processed by Urna, retrieved 2026-10-13

Gomes Code product

Tutor lines of code by module

Non-blank Python lines in each Tutor module.

Data (7)

Tutor lines of code by module
Data	lines
Pedagogy	1,473
Research	1,060
Workspace	1,013
Learning	630
Models (LLM)	449
Evals	237
Adaptive profile	211

Source: Tutor repository, retrieved 2026-10-13

Gomes Code product

Automated tests per chapter

Number of tests grading the exercises of each of the 9 Python track chapters.

Data (9)

Automated tests per chapter
Data	tests
Foundations	34
Functions and iteration	38
Classes and objects	43
Data structures	30
Files, data and tests	40
Advanced Python	48
Traps	42
Under the hood	46
Programming with AI	40

Source: Code Forge content, retrieved 2026-10-13

Gomes Code product

Clipcutter lines of code by layer

Non-blank lines of code in each project layer.

Data (5)

Clipcutter lines of code by layer
Data	lines
Interface (JS, CSS, HTML)	1,329
HTTP routes	394
Services (vision and video)	303
Tests	151
Data models	82

Source: Clipcutter repository, retrieved 2026-10-13

2002 runoff

Lula vs Serra, 2002

Lula's share of valid votes in each region in the 2002 runoff.

Data (5)

Lula vs Serra, 2002
Data	% of valid votes
North	58.2
Northeast	61.5
Center-West	57.3
Southeast	63
South	58.8

Source: TSE municipal results, processed by Urna, retrieved 2026-10-13

2006 runoff

Lula vs Alckmin, 2006

Lula's share of valid votes in each region in the 2006 runoff.

Data (5)

Lula vs Alckmin, 2006
Data	% of valid votes
North	65.6
Northeast	77.1
Center-West	52.4
Southeast	56.9
South	46.5

Source: TSE municipal results, processed by Urna, retrieved 2026-10-13

2010 runoff

Dilma vs Serra, 2010

Dilma's share of valid votes in each region in the 2010 runoff.

Data (5)

Dilma vs Serra, 2010
Data	% of valid votes
North	57.4
Northeast	70.6
Center-West	49.1
Southeast	51.9
South	46.1

Source: TSE municipal results, processed by Urna, retrieved 2026-10-13

2014 runoff

Dilma vs Aécio, 2014

Dilma's share of valid votes in each region in the 2014 runoff.

Data (5)

Dilma vs Aécio, 2014
Data	% of valid votes
North	56.5
Northeast	71.7
Center-West	42.6
Southeast	43.8
South	41.1

Source: TSE municipal results, processed by Urna, retrieved 2026-10-13

2018 runoff

Haddad vs Bolsonaro, 2018

Haddad's share of valid votes in each region in the 2018 runoff.

Data (5)

Haddad vs Bolsonaro, 2018
Data	% of valid votes
North	48.1
Northeast	69.7
Center-West	33.4
Southeast	34.6
South	31.7

Source: TSE municipal results, processed by Urna, retrieved 2026-10-13

2022 runoff

Lula vs Bolsonaro, 2022

Lula's share of valid votes in each region in the 2022 runoff.

Data (5)

Lula vs Bolsonaro, 2022
Data	% of valid votes
North	49
Northeast	69.3
Center-West	39.8
Southeast	45.7
South	38.2

Source: TSE municipal results, processed by Urna, retrieved 2026-10-13