---
license: other
license_name: per-source
license_link: https://github.com/maxgfr/skycmd/blob/main/DATA_LICENSES.md
pretty_name: skycmd time series (s6-cast training)
task_categories:
- time-series-forecasting
tags:
- skycmd
configs:
- config_name: games
  data_files: data/games.parquet
- config_name: london_smart_meters
  data_files: data/london_smart_meters.parquet
- config_name: pedestrian_counts
  data_files: data/pedestrian_counts.parquet
- config_name: rideshare
  data_files: data/rideshare.parquet
- config_name: ushcn_daily
  data_files: data/ushcn_daily.parquet
- config_name: wiki_daily
  data_files: data/wiki_daily.parquet
- config_name: wind_farms_daily
  data_files: data/wind_farms_daily.parquet
- config_name: wind_farms_hourly
  data_files: data/wind_farms_hourly.parquet
---

# skycmd time series (s6-cast training)

The training series of the s6-cast forecaster: public series absent from GIFT-Eval and Chronos' zero-shot benchmark, and the state variables of the skycmd games.

Part of [skycmd](https://github.com/maxgfr/skycmd), tiny decision models trained from scratch in Rust that run in the
browser. Written by `sky-data fetch-series and sky-train cast-synth --games` at commit [`84c6d854`](https://github.com/maxgfr/skycmd/commit/84c6d854cdc2a9f6d951ebb55780060a01f38ca6).
Licences of every set: [DATA_LICENSES.md](https://github.com/maxgfr/skycmd/blob/main/DATA_LICENSES.md).

Each row is one series: `id` (`<source>:<series>`) and `values` (a list of floats, in time order).
The s6-cast trainer holds out one series in ten, by id, for validation; windows and synthetic
series (`sky-train cast-synth`) are drawn from these at training time.

## Sources and licences

Each config is one source and keeps **its source's licence** (share-alike sources stay share-alike).
Attribution goes to the upstream authors; the conversion is ours.

| config | upstream | licence | how it is used | rows |
|---|---|---|---|---:|
| `games` | ours: state variables of the skycmd games (`sky-train cast-synth --games`) | apache-2.0 | 60 oracle episodes per game | 1,549 |
| `london_smart_meters` | autogluon/chronos_datasets `monash_london_smart_meters` (Monash archive, Godahewa et al. 2021) | cc-by-4.0 | first 2,000 series, last 8,192 points | 2,000 |
| `pedestrian_counts` | autogluon/chronos_datasets `monash_pedestrian_counts` (Monash archive, Godahewa et al. 2021) | cc-by-4.0 | all series | 66 |
| `rideshare` | autogluon/chronos_datasets `monash_rideshare` (Monash archive, Godahewa et al. 2021) | cc-by-4.0 | every numeric column of the first 200 rows | 200 |
| `ushcn_daily` | autogluon/chronos_datasets `ushcn_daily` (NOAA NCEI) | public domain (U.S. Government work) | every numeric column of the first 1,300 rows | 1,300 |
| `wiki_daily` | autogluon/chronos_datasets `wiki_daily_100k` (Wikimedia pageviews) | cc0-1.0 | first 5,000 series | 5,000 |
| `wind_farms_daily` | autogluon/chronos_datasets `wind_farms_daily` (Monash archive, Godahewa et al. 2021) | cc-by-4.0 | all series, last 8,192 points | 337 |
| `wind_farms_hourly` | autogluon/chronos_datasets `wind_farms_hourly` (Monash archive, Godahewa et al. 2021) | cc-by-4.0 | all series, last 8,192 points | 337 |

## Files

| file | rows |
|---|---:|
| `data/games.parquet` | 1,549 |
| `data/london_smart_meters.parquet` | 2,000 |
| `data/pedestrian_counts.parquet` | 66 |
| `data/rideshare.parquet` | 200 |
| `data/ushcn_daily.parquet` | 1,300 |
| `data/wiki_daily.parquet` | 5,000 |
| `data/wind_farms_daily.parquet` | 337 |
| `data/wind_farms_hourly.parquet` | 337 |

```python
from datasets import load_dataset
ds = load_dataset("maxgfr/skycmd-series", "games")
```

skycmd wrote no row with a language model: the targets come from the upstream labels (some upstream
sets carry their own teacher soft labels, see their cards), the games' oracles or our generators.