Numbers 1–100 — Attribute Table

Last Updated: 2026-05-05

1. Introduction

This page provides a structured classification of integers from 1 to 100.

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2. Data Schema

A. Column Definitions

• n: Integer value (1–100)
• prime: 1 if prime
• composite: 1 if composite (n > 1 and not prime)
• semiprime: 1 if product of two primes
• square: 1 if perfect square
• cube: 1 if perfect cube
• pow2: 1 if power of 2
• fib: 1 if Fibonacci number
• triangular: 1 if triangular number
• perfect: 1 if perfect number
• divisor_count: total number of divisors
• digit_sum: sum of decimal digits
• digital_root: repeated digit sum (1–9)
• feature_count: number of active (1) feature flags

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B. Design Policy

• Zero-vector elimination: Every number has at least baseline attributes
• One-hot where appropriate: Binary flags retained for key sets
• Hybrid schema: mix of categorical, numeric, and binary features
• Pipeline-friendly: deterministic and reproducible

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3. Attribute Table (1–100)

n	prime	composite	semiprime	square	cube	pow2	fib	triangular	perfect	divisor_count	digit_sum	digital_root	feature_count
1	0	0	0	1	1	1	1	1	0	1	1	1	5
2	1	0	0	0	0	1	1	0	0	2	2	2	4
3	1	0	0	0	0	0	1	1	0	2	3	3	4
4	0	1	1	1	0	1	0	0	0	3	4	4	4
5	1	0	0	0	0	0	1	0	0	2	5	5	3
6	0	1	1	0	0	0	0	1	1	4	6	6	4
7	1	0	0	0	0	0	0	0	0	2	7	7	2
8	0	1	0	0	1	1	1	0	0	4	8	8	4
9	0	1	1	1	0	0	0	0	0	3	9	9	3
10	0	1	1	0	0	0	0	1	0	4	1	1	3
11	1	0	0	0	0	0	0	0	0	2	2	2	2
12	0	1	0	0	0	0	0	0	0	6	3	3	1
13	1	0	0	0	0	0	1	0	0	2	4	4	3
14	0	1	1	0	0	0	0	0	0	4	5	5	2
15	0	1	1	0	0	0	0	1	0	4	6	6	3
16	0	1	0	1	0	1	0	0	0	5	7	7	3
17	1	0	0	0	0	0	0	0	0	2	8	8	2
18	0	1	0	0	0	0	0	0	0	6	9	9	1
19	1	0	0	0	0	0	0	0	0	2	10	1	2
20	0	1	0	0	0	0	0	0	0	6	2	2	1
21	0	1	1	0	0	0	1	1	0	4	3	3	4
22	0	1	1	0	0	0	0	0	0	4	4	4	2
23	1	0	0	0	0	0	0	0	0	2	5	5	2
24	0	1	0	0	0	0	0	0	0	8	6	6	1
25	0	1	1	1	0	0	0	0	0	3	7	7	3
26	0	1	1	0	0	0	0	0	0	4	8	8	2
27	0	1	0	0	1	0	0	0	0	4	9	9	2
28	0	1	0	0	0	0	0	1	1	6	10	1	3
29	1	0	0	0	0	0	0	0	0	2	11	2	2
30	0	1	0	0	0	0	0	0	0	8	3	3	1
31	1	0	0	0	0	0	0	0	0	2	4	4	2
32	0	1	0	0	0	1	0	0	0	6	5	5	2
33	0	1	1	0	0	0	0	0	0	4	6	6	2
34	0	1	1	0	0	0	1	0	0	4	7	7	3
35	0	1	1	0	0	0	0	0	0	4	8	8	2
36	0	1	0	1	0	0	0	1	0	9	9	9	3
37	1	0	0	0	0	0	0	0	0	2	10	1	2
38	0	1	1	0	0	0	0	0	0	4	11	2	2
39	0	1	1	0	0	0	0	0	0	4	12	3	2
40	0	1	0	0	0	0	0	0	0	8	4	4	1
41	1	0	0	0	0	0	0	0	0	2	5	5	2
42	0	1	0	0	0	0	0	0	0	8	6	6	1
43	1	0	0	0	0	0	0	0	0	2	7	7	2
44	0	1	0	0	0	0	0	0	0	6	8	8	1
45	0	1	0	0	0	0	0	1	0	6	9	9	2
46	0	1	1	0	0	0	0	0	0	4	10	1	2
47	1	0	0	0	0	0	0	0	0	2	11	2	2
48	0	1	0	0	0	0	0	0	0	10	12	3	1
49	0	1	1	1	0	0	0	0	0	3	13	4	3
50	0	1	0	0	0	0	0	0	0	6	5	5	1
51	0	1	1	0	0	0	0	0	0	4	6	6	2
52	0	1	0	0	0	0	0	0	0	6	7	7	1
53	1	0	0	0	0	0	0	0	0	2	8	8	2
54	0	1	0	0	0	0	0	0	0	8	9	9	1
55	0	1	1	0	0	0	1	1	0	4	10	1	4
56	0	1	0	0	0	0	0	0	0	8	11	2	1
57	0	1	1	0	0	0	0	0	0	4	12	3	2
58	0	1	1	0	0	0	0	0	0	4	13	4	2
59	1	0	0	0	0	0	0	0	0	2	14	5	2
60	0	1	0	0	0	0	0	0	0	12	6	6	1
61	1	0	0	0	0	0	0	0	0	2	7	7	2
62	0	1	1	0	0	0	0	0	0	4	8	8	2
63	0	1	0	0	0	0	0	0	0	6	9	9	1
64	0	1	0	1	1	1	0	0	0	7	10	1	4
65	0	1	1	0	0	0	0	0	0	4	11	2	2
66	0	1	0	0	0	0	0	1	0	8	12	3	2
67	1	0	0	0	0	0	0	0	0	2	13	4	2
68	0	1	0	0	0	0	0	0	0	6	14	5	1
69	0	1	1	0	0	0	0	0	0	4	15	6	2
70	0	1	0	0	0	0	0	0	0	8	7	7	1
71	1	0	0	0	0	0	0	0	0	2	8	8	2
72	0	1	0	0	0	0	0	0	0	12	9	9	1
73	1	0	0	0	0	0	0	0	0	2	10	1	2
74	0	1	1	0	0	0	0	0	0	4	11	2	2
75	0	1	0	0	0	0	0	0	0	6	12	3	1
76	0	1	0	0	0	0	0	0	0	6	13	4	1
77	0	1	1	0	0	0	0	0	0	4	14	5	2
78	0	1	0	0	0	0	0	1	0	8	15	6	2
79	1	0	0	0	0	0	0	0	0	2	16	7	2
80	0	1	0	0	0	0	0	0	0	10	8	8	1
81	0	1	0	1	0	0	0	0	0	5	9	9	2
82	0	1	1	0	0	0	0	0	0	4	10	1	2
83	1	0	0	0	0	0	0	0	0	2	11	2	2
84	0	1	0	0	0	0	0	0	0	12	12	3	1
85	0	1	1	0	0	0	0	0	0	4	13	4	2
86	0	1	1	0	0	0	0	0	0	4	14	5	2
87	0	1	1	0	0	0	0	0	0	4	15	6	2
88	0	1	0	0	0	0	0	0	0	8	16	7	1
89	1	0	0	0	0	0	1	0	0	2	17	8	3
90	0	1	0	0	0	0	0	0	0	12	9	9	1
91	0	1	1	0	0	0	0	1	0	4	10	1	3
92	0	1	0	0	0	0	0	0	0	6	11	2	1
93	0	1	1	0	0	0	0	0	0	4	12	3	2
94	0	1	1	0	0	0	0	0	0	4	13	4	2
95	0	1	1	0	0	0	0	0	0	4	14	5	2
96	0	1	0	0	0	0	0	0	0	12	15	6	1
97	1	0	0	0	0	0	0	0	0	2	16	7	2
98	0	1	0	0	0	0	0	0	0	6	17	8	1
99	0	1	0	0	0	0	0	0	0	6	18	9	1
100	0	1	1	1	0	0	0	0	0	9	1	1	3

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4. Maintenance Notes

• Extensibility: Future columns may include prime_gap, factor_entropy, or binary_length
• Generation: Recommended via script (avoid manual edits). See: generate_numbers_csv.py
• Interpretation: feature_count is schema-dependent; do not treat as absolute “importance”