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id int64 1 200 | session int64 1 44 | behavior_persistence float64 0.07 0.99 | incentive_decay float64 0.11 0.97 | switching_friction float64 0.11 0.86 | cue_dependence float64 0.15 0.83 | reinforcement_memory float64 0.15 0.78 | default_exposure float64 0.11 0.94 | deliberative_override float64 0.06 0.93 | habitlock_index float64 0.27 0.79 |
|---|---|---|---|---|---|---|---|---|---|
1 | 43 | 0.812552 | 0.323522 | 0.453333 | 0.495754 | 0.623122 | 0.918489 | 0.408967 | 0.594402 |
2 | 10 | 0.903517 | 0.644257 | 0.607268 | 0.359264 | 0.341637 | 0.650372 | 0.619594 | 0.582151 |
3 | 41 | 0.43874 | 0.440154 | 0.472485 | 0.426892 | 0.364718 | 0.73758 | 0.315614 | 0.486792 |
4 | 37 | 0.554093 | 0.106256 | 0.362338 | 0.420027 | 0.520668 | 0.616753 | 0.53722 | 0.425444 |
5 | 6 | 0.719304 | 0.823476 | 0.645306 | 0.580493 | 0.602288 | 0.478752 | 0.565528 | 0.635777 |
6 | 27 | 0.643383 | 0.831185 | 0.535742 | 0.540181 | 0.40318 | 0.44148 | 0.575261 | 0.566077 |
7 | 8 | 0.481296 | 0.243192 | 0.500673 | 0.432597 | 0.432627 | 0.628428 | 0.643951 | 0.434857 |
8 | 29 | 0.64134 | 0.45782 | 0.458192 | 0.30036 | 0.282615 | 0.495977 | 0.632548 | 0.442789 |
9 | 41 | 0.664438 | 0.238028 | 0.406737 | 0.385089 | 0.368213 | 0.483981 | 0.167539 | 0.473157 |
10 | 29 | 0.931321 | 0.73531 | 0.645752 | 0.554468 | 0.690914 | 0.310099 | 0.366889 | 0.675909 |
11 | 28 | 0.775811 | 0.719945 | 0.662606 | 0.42132 | 0.536629 | 0.38101 | 0.341281 | 0.614456 |
12 | 36 | 0.59953 | 0.271314 | 0.417694 | 0.534369 | 0.36337 | 0.854696 | 0.353359 | 0.505964 |
13 | 20 | 0.906966 | 0.762566 | 0.755175 | 0.62227 | 0.610827 | 0.418952 | 0.604728 | 0.678288 |
14 | 17 | 0.595163 | 0.457609 | 0.672598 | 0.461655 | 0.327047 | 0.542098 | 0.37913 | 0.526581 |
15 | 38 | 0.593272 | 0.880148 | 0.466469 | 0.461601 | 0.357395 | 0.340315 | 0.102836 | 0.572521 |
16 | 16 | 0.38511 | 0.493007 | 0.31112 | 0.465614 | 0.423829 | 0.600454 | 0.931709 | 0.397079 |
17 | 36 | 0.538282 | 0.703574 | 0.43009 | 0.560516 | 0.310171 | 0.23398 | 0.159903 | 0.518346 |
18 | 31 | 0.465729 | 0.304286 | 0.406298 | 0.49715 | 0.492325 | 0.608704 | 0.126302 | 0.493606 |
19 | 2 | 0.861633 | 0.842138 | 0.721677 | 0.832095 | 0.665765 | 0.334 | 0.396724 | 0.725965 |
20 | 4 | 0.766209 | 0.316256 | 0.478317 | 0.346448 | 0.22457 | 0.54464 | 0.503861 | 0.464394 |
21 | 4 | 0.911846 | 0.341994 | 0.590969 | 0.642594 | 0.709896 | 0.802579 | 0.601589 | 0.641091 |
22 | 2 | 0.3733 | 0.171087 | 0.456858 | 0.149008 | 0.396295 | 0.392569 | 0.378115 | 0.352919 |
23 | 41 | 0.947141 | 0.536527 | 0.641075 | 0.553907 | 0.54826 | 0.33849 | 0.834246 | 0.582572 |
24 | 7 | 0.884663 | 0.472555 | 0.589375 | 0.498975 | 0.48232 | 0.342641 | 0.257378 | 0.592749 |
25 | 14 | 0.764329 | 0.612667 | 0.437937 | 0.447528 | 0.565732 | 0.446898 | 0.388932 | 0.568615 |
26 | 11 | 0.817631 | 0.779906 | 0.560254 | 0.548737 | 0.532565 | 0.610353 | 0.641982 | 0.626171 |
27 | 35 | 0.810972 | 0.563301 | 0.497152 | 0.61776 | 0.528952 | 0.68134 | 0.718249 | 0.588716 |
28 | 24 | 0.378573 | 0.470721 | 0.309702 | 0.346558 | 0.538248 | 0.240738 | 0.340979 | 0.414431 |
29 | 5 | 0.768195 | 0.529302 | 0.518786 | 0.439901 | 0.525215 | 0.910459 | 0.644593 | 0.583036 |
30 | 17 | 0.92118 | 0.67544 | 0.641253 | 0.668694 | 0.444397 | 0.470881 | 0.460743 | 0.651753 |
31 | 3 | 0.502738 | 0.508994 | 0.363117 | 0.514524 | 0.379299 | 0.443181 | 0.849759 | 0.424563 |
32 | 30 | 0.532129 | 0.71522 | 0.474552 | 0.481241 | 0.289371 | 0.645897 | 0.407432 | 0.528521 |
33 | 24 | 0.805427 | 0.90144 | 0.539418 | 0.536283 | 0.492175 | 0.440112 | 0.627222 | 0.616896 |
34 | 39 | 0.32157 | 0.557037 | 0.545931 | 0.266478 | 0.381764 | 0.699308 | 0.656459 | 0.435828 |
35 | 38 | 0.540321 | 0.196486 | 0.352165 | 0.501176 | 0.346844 | 0.276111 | 0.114045 | 0.430778 |
36 | 34 | 0.626939 | 0.400682 | 0.634307 | 0.601657 | 0.512764 | 0.772631 | 0.448789 | 0.579389 |
37 | 41 | 0.559566 | 0.459403 | 0.347442 | 0.371198 | 0.54644 | 0.500147 | 0.473923 | 0.4721 |
38 | 29 | 0.548651 | 0.367098 | 0.446996 | 0.413062 | 0.351703 | 0.941332 | 0.199882 | 0.521197 |
39 | 23 | 0.988253 | 0.93935 | 0.774238 | 0.699594 | 0.706268 | 0.638889 | 0.518851 | 0.780649 |
40 | 12 | 0.307129 | 0.132377 | 0.345122 | 0.268295 | 0.46744 | 0.561938 | 0.146447 | 0.382377 |
41 | 9 | 0.689548 | 0.662894 | 0.38525 | 0.647329 | 0.54931 | 0.219174 | 0.474085 | 0.547651 |
42 | 16 | 0.692722 | 0.802921 | 0.690067 | 0.59921 | 0.652386 | 0.439204 | 0.508914 | 0.645675 |
43 | 43 | 0.643556 | 0.502868 | 0.62616 | 0.546184 | 0.286723 | 0.516475 | 0.217977 | 0.555812 |
44 | 15 | 0.649984 | 0.511932 | 0.401768 | 0.439421 | 0.549476 | 0.340678 | 0.669863 | 0.481716 |
45 | 24 | 0.567728 | 0.281594 | 0.485799 | 0.461261 | 0.629094 | 0.623487 | 0.182139 | 0.533113 |
46 | 22 | 0.754529 | 0.30675 | 0.650314 | 0.52409 | 0.513023 | 0.433519 | 0.616687 | 0.530915 |
47 | 7 | 0.518656 | 0.581902 | 0.417858 | 0.550481 | 0.371988 | 0.26209 | 0.676553 | 0.451392 |
48 | 17 | 0.674752 | 0.535649 | 0.456482 | 0.575751 | 0.373735 | 0.658644 | 0.287359 | 0.563748 |
49 | 34 | 0.732816 | 0.387019 | 0.460027 | 0.515541 | 0.457099 | 0.380328 | 0.282046 | 0.528088 |
50 | 20 | 0.464001 | 0.464571 | 0.207806 | 0.459167 | 0.53678 | 0.162315 | 0.324174 | 0.423627 |
51 | 25 | 0.776383 | 0.397505 | 0.352337 | 0.502571 | 0.538678 | 0.868 | 0.585817 | 0.549245 |
52 | 24 | 0.483648 | 0.305382 | 0.387747 | 0.376148 | 0.289392 | 0.511442 | 0.398524 | 0.412098 |
53 | 26 | 0.361932 | 0.451044 | 0.476111 | 0.385532 | 0.403117 | 0.555519 | 0.145546 | 0.472139 |
54 | 12 | 0.704915 | 0.450652 | 0.611247 | 0.348045 | 0.570488 | 0.826739 | 0.22813 | 0.599342 |
55 | 22 | 0.629531 | 0.31709 | 0.462038 | 0.478928 | 0.549022 | 0.811805 | 0.335022 | 0.542158 |
56 | 10 | 0.521849 | 0.653122 | 0.107234 | 0.396467 | 0.531293 | 0.45932 | 0.264892 | 0.475356 |
57 | 39 | 0.425794 | 0.623953 | 0.404858 | 0.42333 | 0.502191 | 0.73224 | 0.441554 | 0.50841 |
58 | 37 | 0.360728 | 0.348196 | 0.572655 | 0.446717 | 0.151575 | 0.602971 | 0.6046 | 0.40308 |
59 | 39 | 0.466083 | 0.332364 | 0.540257 | 0.390779 | 0.344326 | 0.702623 | 0.597998 | 0.446213 |
60 | 19 | 0.729864 | 0.627521 | 0.664001 | 0.699013 | 0.634853 | 0.581518 | 0.244763 | 0.673033 |
61 | 5 | 0.142254 | 0.633253 | 0.351014 | 0.38675 | 0.342093 | 0.404105 | 0.264414 | 0.401941 |
62 | 41 | 0.585949 | 0.809685 | 0.409856 | 0.664467 | 0.388279 | 0.834302 | 0.670859 | 0.576045 |
63 | 21 | 0.799243 | 0.415418 | 0.469526 | 0.410434 | 0.416851 | 0.783321 | 0.552522 | 0.540339 |
64 | 29 | 0.451824 | 0.698199 | 0.38275 | 0.509314 | 0.475404 | 0.524426 | 0.626533 | 0.490967 |
65 | 7 | 0.774468 | 0.561046 | 0.328366 | 0.493026 | 0.625406 | 0.76171 | 0.632112 | 0.56674 |
66 | 8 | 0.645531 | 0.677465 | 0.415468 | 0.41791 | 0.483168 | 0.670094 | 0.373074 | 0.559828 |
67 | 7 | 0.55246 | 0.576039 | 0.387676 | 0.527924 | 0.373235 | 0.533175 | 0.750633 | 0.469103 |
68 | 36 | 0.852272 | 0.287875 | 0.646791 | 0.483819 | 0.529504 | 0.389733 | 0.717074 | 0.529132 |
69 | 36 | 0.900439 | 0.722188 | 0.606357 | 0.756449 | 0.734409 | 0.421264 | 0.267928 | 0.716708 |
70 | 11 | 0.428546 | 0.66733 | 0.393121 | 0.597008 | 0.399722 | 0.556896 | 0.552498 | 0.495363 |
71 | 23 | 0.488424 | 0.516744 | 0.442942 | 0.331801 | 0.435921 | 0.333032 | 0.609776 | 0.431041 |
72 | 7 | 0.403637 | 0.36158 | 0.408405 | 0.365073 | 0.309238 | 0.467456 | 0.605468 | 0.384528 |
73 | 33 | 0.900113 | 0.96274 | 0.651479 | 0.527564 | 0.700634 | 0.652858 | 0.361065 | 0.739425 |
74 | 1 | 0.409105 | 0.549436 | 0.371723 | 0.63501 | 0.546607 | 0.548606 | 0.417973 | 0.507696 |
75 | 3 | 0.532272 | 0.543827 | 0.527301 | 0.379572 | 0.419326 | 0.304748 | 0.774976 | 0.442658 |
76 | 35 | 0.518546 | 0.70081 | 0.481475 | 0.346752 | 0.456543 | 0.6107 | 0.724578 | 0.493948 |
77 | 42 | 0.745284 | 0.611662 | 0.481983 | 0.638016 | 0.579356 | 0.254943 | 0.655919 | 0.554374 |
78 | 25 | 0.928403 | 0.92951 | 0.571978 | 0.740216 | 0.507324 | 0.662746 | 0.697699 | 0.697079 |
79 | 6 | 0.715739 | 0.689421 | 0.474643 | 0.687802 | 0.568395 | 0.763577 | 0.467426 | 0.634881 |
80 | 2 | 0.640589 | 0.460046 | 0.457937 | 0.533673 | 0.541844 | 0.342804 | 0.79953 | 0.479895 |
81 | 38 | 0.934771 | 0.636613 | 0.681377 | 0.69893 | 0.713633 | 0.68128 | 0.325726 | 0.731147 |
82 | 12 | 0.813753 | 0.21158 | 0.537245 | 0.464479 | 0.587385 | 0.327583 | 0.61251 | 0.501331 |
83 | 10 | 0.566175 | 0.492879 | 0.435619 | 0.514277 | 0.55739 | 0.349542 | 0.302126 | 0.51657 |
84 | 25 | 0.989268 | 0.830582 | 0.526556 | 0.747607 | 0.655279 | 0.502436 | 0.811921 | 0.680451 |
85 | 1 | 0.27507 | 0.643849 | 0.280799 | 0.513053 | 0.286831 | 0.503348 | 0.518758 | 0.4134 |
86 | 10 | 0.638644 | 0.606484 | 0.304362 | 0.637951 | 0.679191 | 0.694385 | 0.534959 | 0.573807 |
87 | 5 | 0.902966 | 0.971301 | 0.617836 | 0.716475 | 0.78043 | 0.648492 | 0.193284 | 0.789943 |
88 | 25 | 0.294868 | 0.674876 | 0.316874 | 0.609149 | 0.346488 | 0.461621 | 0.707083 | 0.426897 |
89 | 21 | 0.526076 | 0.591045 | 0.521215 | 0.286482 | 0.239056 | 0.360571 | 0.435333 | 0.449276 |
90 | 37 | 0.733013 | 0.512853 | 0.794606 | 0.466049 | 0.52395 | 0.617987 | 0.251237 | 0.631071 |
91 | 38 | 0.274828 | 0.303046 | 0.145564 | 0.316368 | 0.233258 | 0.345941 | 0.597938 | 0.278491 |
92 | 29 | 0.254509 | 0.555174 | 0.357252 | 0.449945 | 0.255618 | 0.242324 | 0.446739 | 0.375227 |
93 | 19 | 0.781028 | 0.265429 | 0.478877 | 0.296946 | 0.435441 | 0.822009 | 0.437927 | 0.516237 |
94 | 13 | 0.823484 | 0.580053 | 0.469496 | 0.487354 | 0.502575 | 0.394681 | 0.66893 | 0.54379 |
95 | 44 | 0.485632 | 0.685059 | 0.309215 | 0.461578 | 0.466668 | 0.540955 | 0.267417 | 0.513518 |
96 | 10 | 0.722644 | 0.459818 | 0.491728 | 0.405599 | 0.430556 | 0.185142 | 0.644918 | 0.46786 |
97 | 19 | 0.438406 | 0.587815 | 0.570486 | 0.365677 | 0.272097 | 0.107362 | 0.225983 | 0.450436 |
98 | 17 | 0.459431 | 0.341053 | 0.649486 | 0.45806 | 0.375375 | 0.612703 | 0.266851 | 0.501638 |
99 | 16 | 0.431841 | 0.711044 | 0.275983 | 0.549913 | 0.45539 | 0.772232 | 0.0926 | 0.552998 |
100 | 5 | 0.88705 | 0.498366 | 0.581885 | 0.645841 | 0.68472 | 0.619631 | 0.503375 | 0.648154 |
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Habitlock Economics Dataset
Dataset Description
Summary
Synthetic 200-row dataset for Habitlock measurement and computational experiments.
Supported Tasks
- Economic analysis
- Behavioral Economics research
- Computational economics
Languages
- English (metadata and documentation)
- Python (code examples)
Dataset Structure
Data Fields
id: Unique observation idsession: Synthetic decision sessionbehavior_persistence: Observed persistence in repeated behaviorincentive_decay: Decay of original monetary/non-monetary incentive strengthswitching_friction: Friction associated with changing established behaviorcue_dependence: Dependence on contextual cues and routinesreinforcement_memory: Memory strength of past reinforcementdefault_exposure: Exposure to default-option repetitiondeliberative_override: Capacity for reflective override of habithabitlock_index: Composite term index
Data Splits
- Full dataset: 200 examples
Dataset Creation
Source Data
Synthetic data generated for demonstrating Habitlock applications.
Data Generation
Channels are sampled from controlled distributions with correlated structure. The term index is computed from normalized channels and directional weights.
Considerations
Social Impact
Research-only synthetic data for method development and reproducibility testing.
Additional Information
Licensing
MIT License - free for academic and commercial use.
Citation
@dataset{habitlock2026, title={{Habitlock Economics Dataset}}, author={{Economic Research Collective}}, year={{2026}} }
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