.
├── airplane_crashes
│ ├── airplane_crashes.json
│ ├── airplane_crashes_drop_unused_cols.csv
│ ├── notebooks
│ │ ├── airplane_crashes_1.ipynb
│ │ ├── airplane_crashes_2.ipynb
│ │ ...
│ ├── raw_json
│ │ ├── airplane_crashes_1.json
│ │ ├── airplane_crashes_2.json
│ │ ...
│ └── type
│ └── types.json
...
The directory structure of this dataset is shown above. For each dataset(e.g., airplane_crashes), it contains the followings:
- The raw dataset file airplane_crashes_drop_unused_cols.csv (omitted due to file size limitation), see here https://stuscueducn-my.sharepoint.com/:f:/g/personal/vengeji_stu_scu_edu_cn/ErusZEUnmI9EpGcaqA1OJ_sBtDny7sJ5ws4JUPXAfxMENw?e=3YMctb
- The collected notebooks containing the interactive analysis logs under the directory /notebooks
- The collected visualization results in JSON format under the directory /raw_json
- The merged visualization results in JSON format in the file airplane_crashes.json
- The schema of attributes (using pandas data types) in the file /type/types.json
A sample dataset kickstarter in the KaggleBench. For each dataset, we collect visualization results in JSON format recorded in files kickstarter_*.json (A)(B). Then we merge results based on the votes to generate an ordered list with 25 visualizations in file kickstarter.json (C). The used attributes are recorded in file types.json.
Summaries of the data sets of KaggleBecnh:
| Name | #-Row | #-Attr | #-Attr-used | #-Viz |
|---|---|---|---|---|
| airplane_crashes | 5268 | 13 | 6 | 22 |
| avito_demand | 1503424 | 18 | 14 | 33 |
| avocados_price | 18249 | 14 | 7 | 20 |
| flight_delay | 5819079 | 32 | 8 | 18 |
| google_play_store | 9659 | 13 | 11 | 33 |
| gun_violence | 239677 | 29 | 6 | 21 |
| h1b_visa | 3002458 | 11 | 7 | 14 |
| home_credit_risk | 307511 | 122 | 20 | 50 |
| kickstarter | 378661 | 15 | 10 | 25 |
| lending_club | 2260668 | 149 | 15 | 29 |
| patient_charge | 1338 | 10 | 9 | 14 |
| sberbank_russian_housing_market | 30471 | 292 | 16 | 29 |
| student_performance | 1000 | 8 | 8 | 34 |
| suicide_rates | 27820 | 12 | 9 | 25 |
| terrorism | 170350 | 136 | 30 | 40 |
| titan | 891 | 12 | 8 | 23 |
| videogame | 16719 | 17 | 15 | 48 |
| zomato | 51717 | 17 | 11 | 49 |