Datasets:
src_ts int64 | station_id int64 | bikes int16 | docks int16 | mechanical int16 | ebike int16 | last_reported int64 | is_installed int8 | is_renting int8 | is_returning int8 |
|---|---|---|---|---|---|---|---|---|---|
1,793,093,646 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,093,707 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,093,768 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,093,831 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,093,891 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,093,951 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,012 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,073 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,134 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,196 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,257 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,318 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,379 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,438 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,499 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,562 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,623 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,684 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,745 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,803 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,864 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,925 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,094,988 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,049 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,110 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,169 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,230 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,291 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,351 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,412 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,476 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,537 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,598 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,656 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,717 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,778 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,842 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,902 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,095,963 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,096,021 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,096,082 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,096,143 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,096,204 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,096,268 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,096,329 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,096,390 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,096,451 | 6,245 | 25 | 0 | 17 | 8 | 1,793,092,863 | 1 | 1 | 1 |
1,793,096,508 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,096,569 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,096,630 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,096,634 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,096,695 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,096,755 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,096,813 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,096,874 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,096,938 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,096,995 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,060 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,121 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,182 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,239 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,300 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,361 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,426 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,487 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,548 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,609 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,666 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,727 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,788 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,853 | 6,245 | 24 | 1 | 17 | 7 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,914 | 6,245 | 24 | 1 | 17 | 7 | 1,793,096,485 | 1 | 1 | 1 |
1,793,097,974 | 6,245 | 24 | 1 | 17 | 7 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,032 | 6,245 | 24 | 1 | 17 | 7 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,093 | 6,245 | 23 | 2 | 17 | 6 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,154 | 6,245 | 23 | 2 | 17 | 6 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,215 | 6,245 | 23 | 2 | 17 | 6 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,279 | 6,245 | 23 | 2 | 17 | 6 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,340 | 6,245 | 23 | 2 | 17 | 6 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,401 | 6,245 | 23 | 2 | 17 | 6 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,462 | 6,245 | 23 | 2 | 17 | 6 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,519 | 6,245 | 23 | 2 | 17 | 6 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,580 | 6,245 | 24 | 1 | 17 | 7 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,645 | 6,245 | 24 | 1 | 17 | 7 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,706 | 6,245 | 24 | 1 | 17 | 7 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,766 | 6,245 | 24 | 1 | 17 | 7 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,827 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,888 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,098,949 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,099,007 | 6,245 | 25 | 0 | 17 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,099,067 | 6,245 | 24 | 1 | 16 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,099,128 | 6,245 | 24 | 1 | 16 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,099,193 | 6,245 | 24 | 1 | 16 | 8 | 1,793,096,485 | 1 | 1 | 1 |
1,793,099,254 | 6,245 | 25 | 0 | 16 | 9 | 1,793,096,485 | 1 | 1 | 1 |
1,793,099,315 | 6,245 | 25 | 0 | 16 | 9 | 1,793,096,485 | 1 | 1 | 1 |
1,793,099,372 | 6,245 | 25 | 0 | 16 | 9 | 1,793,096,485 | 1 | 1 | 1 |
1,793,099,437 | 6,245 | 25 | 0 | 16 | 9 | 1,793,096,485 | 1 | 1 | 1 |
1,793,099,494 | 6,245 | 25 | 0 | 16 | 9 | 1,793,096,485 | 1 | 1 | 1 |
1,793,099,555 | 6,245 | 25 | 0 | 16 | 9 | 1,793,096,485 | 1 | 1 | 1 |
1,793,099,620 | 6,245 | 25 | 0 | 16 | 9 | 1,793,096,485 | 1 | 1 | 1 |
Vélib' Métropole station status, every minute (unofficial)
Bikes (mechanical and electric) and free docks at every Vélib' Métropole station (about 1,520), recorded about once a minute from the operator's open GBFS feed since 2026-10-27. One Parquet file per day (Europe/Paris), plus a station table. Each day is uploaded once complete.
Files and columns
snapshots/YYYY-MM-DD.parquet
One file per Europe/Paris day (DST days hold 23 or 25 hours). One row = one station in one snapshot, sorted by
station_id, then src_ts. About 2.2 million rows and 2–3 MB per day.
| column | type | meaning |
|---|---|---|
src_ts |
int64 | feed timestamp (lastUpdatedOther), Unix seconds, UTC; shared by all rows of a snapshot |
station_id |
int64 | station id; join key with stations.csv |
bikes |
int16 | bikes available (num_bikes_available) |
docks |
int16 | free docks (num_docks_available) |
mechanical |
int16, nullable | mechanical bikes among bikes |
ebike |
int16, nullable | e-bikes among bikes |
last_reported |
int64 | last_reported as published by the feed, Unix seconds, UTC |
is_installed |
int8 (0/1), nullable | feed flag |
is_renting |
int8 (0/1), nullable | feed flag |
is_returning |
int8 (0/1), nullable | feed flag |
stations.csv
One row per station in the latest station_information feed; rebuilt with every upload.
| column | meaning |
|---|---|
station_id |
join key with the snapshots |
station_code |
operator's station code |
name |
station name |
lat, lon |
coordinates (WGS84) |
house_number, street, postal_code, city |
nearest address from reverse geocoding; may be empty or approximate |
capacity_official |
capacity from the feed |
observed_capacity |
max(bikes + docks) seen over all published days |
capacity_gap |
capacity_official − observed_capacity |
geocoded_at |
UTC date the address was fetched |
Notes
Collection started on 2026-10-27 at 10:34 Paris time, so that day is partial. Values are kept as published: nothing is corrected or filled in.
- Snapshots are not evenly spaced. Missing minutes are absent (no placeholder rows), and the feed sometimes
publishes the same counts again a few seconds later under a new
src_ts. Check the spacing ofsrc_tsbefore computing per-minute rates. mechanical/ebikeare null for every station in some snapshots;bikesanddocksare still given.last_reportedcan be stale even for working stations.- Past days can be revised if missing snapshots are recovered; use the commit history to pin a version.
How to load it
import pandas as pd
day = pd.read_parquet("hf://datasets/angelosaadeh/velib/snapshots/2026-10-28.parquet")
day["time"] = pd.to_datetime(day["src_ts"], unit="s", utc=True).dt.tz_convert("Europe/Paris")
stations = pd.read_csv("hf://datasets/angelosaadeh/velib/stations.csv",
dtype={"station_code": str, "postal_code": str})
from datasets import load_dataset
some_days = load_dataset("angelosaadeh/velib", data_files="snapshots/2026-10-2*.parquet", split="train")
stations = load_dataset("csv", data_files="hf://datasets/angelosaadeh/velib/stations.csv", split="train")
Sources and licence
Released under the Licence Ouverte / Open Licence 2.0 (Etalab). You may copy, redistribute, adapt and use it commercially, provided you credit this dataset and the sources below, with their update dates.
Suggested credit: Vélib' Métropole station status, every minute (unofficial), Angelo Saadeh (https://www.angelosaadeh.fr), https://huggingface.co/datasets/angelosaadeh/velib, data from Vélib' Métropole (GBFS) and the Base Adresse Nationale, accessed YYYY-MM-DD (revision [commit hash], if pinned).
- Station data: Vélib' Métropole (Smovengo / Syndicat Autolib' et Vélib' Métropole), GBFS feeds
station_statusandstation_information, from the open data page, under the Etalab Licence Ouverte. Each row'ssrc_tsis the feed's update time. - Addresses: reverse-geocoded with the Géoplateforme geocoding service (IGN), based
on the Base Adresse Nationale (Licence Ouverte 2.0); fetch dates in
geocoded_at. These are the nearest addresses, not addresses published by Vélib' Métropole.
Changes from the source data: reformatted from JSON snapshots to daily Parquet files, duplicate snapshots removed,
columns renamed and bike types flattened (see the tables), unused fields dropped, and capacity and
address columns added to stations.csv.
Disclaimer
Independent dataset, not affiliated with or endorsed by Vélib' Métropole, Smovengo, IGN or any public body. Provided as is, without warranty; it may contain gaps from outages and errors from the upstream data. Questions: www.angelosaadeh.fr.
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