players
About:
This table contains a basic informational table about the current players in Minor League Esports
Parquet Usage
Examples assume you have run the view alias first.- Alias a View
-
CREATE VIEW v_players AS ( SELECT * FROM read_parquet( 'https://f004.backblazeb2.com/file/sprocket-artifacts/test/data/players.parquet' ) ); - Select Everything
-
SELECT * FROM v_players; - Select players on a given team
-
SELECT * FROM v_players WHERE franchise = 'team_name';
CSV Usage
To link a CSV to your Google sheet
=importData("https://f004.backblazeb2.com/file/sprocket-artifacts/test/data/players.csv")
JSON Usage
- Javascript
-
const players = await fetch("https://f004.backblazeb2.com/file/sprocket-artifacts/test/data/players.json").then(r => r.json()) - Python
-
import requests players = requests.get("https://f004.backblazeb2.com/file/sprocket-artifacts/test/data/players.json").json() - C#
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using (var client = new HttpClient()) { var json = await client.GetStringAsync("https://f004.backblazeb2.com/file/sprocket-artifacts/test/data/players.json"); var players = JObject.Parse(json); } - Ruby
-
require 'net/http' require 'json' uri = URI.parse("https://f004.backblazeb2.com/file/sprocket-artifacts/test/data/players.json") response = Net::HTTP.get_response(uri) players = JSON.parse(response.body) - R
-
library(jsonlite) players <- fromJSON("https://f004.backblazeb2.com/file/sprocket-artifacts/test/data/players.json") - curl
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curl https://f004.backblazeb2.com/file/sprocket-artifacts/test/data/players.json | jq
At a glance:
Table Schema:
| column_name | column_type | null | key | default | extra |
|---|---|---|---|---|---|
| as_of | TIMESTAMP WITH TIME ZONE | YES | None | None | None |
| name | VARCHAR | YES | None | None | None |
| salary | DOUBLE | YES | None | None | None |
| sprocket_player_id | BIGINT | YES | None | None | None |
| member_id | BIGINT | YES | None | None | None |
| skill_group | VARCHAR | YES | None | None | None |
| franchise | VARCHAR | YES | None | None | None |
| slot | VARCHAR | YES | None | None | None |
| current_scrim_points | BIGINT | YES | None | None | None |
Sample Data:
| as_of | name | salary | sprocket_player_id | member_id | skill_group | franchise | slot | current_scrim_points |
|---|---|---|---|---|---|---|---|---|
| 2024-06-09 17:11:53.186189-05:00 | !Chino-096 | 12.5 | 2 | 3 | Academy League | FP | NONE | 0 |
| 2024-06-09 17:11:53.186189-05:00 | BuffaloDave | 10.5 | 4 | 5 | Academy League | FP | NONE | 0 |
| 2024-06-09 17:11:53.186189-05:00 | AcePocket | 17.0 | 5 | 6 | Premier League | FP | NONE | 0 |
| 2024-06-09 17:11:53.186189-05:00 | Achieves | 15.5 | 6 | 7 | Master League | FP | NONE | 0 |
| 2024-06-09 17:11:53.186189-05:00 | AD Slaps | 9.5 | 8 | 9 | Foundation League | FP | NONE | 0 |
Table Summary:
| column_name | column_type | min | max | approx_unique | avg | std | q25 | q50 | q75 | count | null_percentage |
|---|---|---|---|---|---|---|---|---|---|---|---|
| as_of | TIMESTAMP WITH TIME ZONE | 2024-06-09 17:11:53.186189-05 | 2024-06-09 17:11:53.186189-05 | 1 | None | None | None | None | None | 5265 | 0.0% |
| name | VARCHAR | !Chino-096 | Érid | 5227 | None | None | None | None | None | 5265 | 0.0% |
| salary | DOUBLE | 4.0 | 20.0 | 33 | 13.490978157644824 | 3.32464322258247 | 11.5 | 13.5 | 16.0 | 5265 | 0.0% |
| sprocket_player_id | BIGINT | 1 | 5374 | 5377 | 2648.0759734093067 | 1541.4194593860757 | 1319 | 2635 | 3953 | 5265 | 0.0% |
| member_id | BIGINT | 2 | 5432 | 5406 | 2690.8400759734095 | 1559.3700614277532 | 1342 | 2692 | 4008 | 5265 | 0.0% |
| skill_group | VARCHAR | Academy League | Premier League | 5 | None | None | None | None | None | 5265 | 0.0% |
| franchise | VARCHAR | Aviators | Wolves | 37 | None | None | None | None | None | 5265 | 0.0% |
| slot | VARCHAR | PLAYERH | 11 | None | None | None | None | None | 5265 | 0.0% | |
| current_scrim_points | BIGINT | 0 | 405 | 36 | 2.388414055080722 | 15.833844069587604 | 0 | 0 | 0 | 5265 | 0.0% |