Cross Country - uwaggs/usportspy GitHub Wiki

Cross-Country Module

The usportspy package provides functions to retrieve various data related to Cross-Country, such as team rankings, rosters, meet results, and universities. Note for fields that return a part of a URL that the prefix should be https://www.trackie.com as that is where the reference is to.

Functions

xc_team_rankings

Fetches the rankings of cross-country teams based on gender, seasons, and universities.

Parameters:

  • gender (str): Must be either "m" or "w".
  • seasons (list of int, optional): List of seasons (starting year) to filter by. If nothing is provided, data for all seasons will be returned.
  • universities (list of str, optional): List of universities to filter by. If nothing is provided, data for all universities will be returned.

Returns:

  • pd.DataFrame: A DataFrame containing the filtered cross-country team rankings. The columns of the returned DataFrame are: Season, Gender, Date, Week, Ranking, University, and PTS.

Example:

from usportspy import xc_team_rankings

# Get the team rankings for male teams in the 2023 season
team_rankings = xc_team_rankings("m", seasons=[2023])
print(team_rankings.head())

Expected output:

   Season Gender        Date  Week  Ranking University  PTS
0    2023    MEN  10/30/2023     7        1      Laval   96
1    2023    MEN  10/30/2023     7        2        UBC   86
2    2023    MEN  10/30/2023     7        3     Guelph   80
3    2023    MEN  10/30/2023     7        4    Queen’s   73
4    2023    MEN  10/30/2023     7        5        UNB   54

xc_rosters

Fetches the rosters of cross-country teams based on gender, seasons, and universities.

Parameters:

  • gender (str): Must be either "m" or "w".
  • seasons (list of int, optional): List of seasons (starting year) to filter by. If nothing is provided, data for all seasons will be returned.
  • universities (list of str, optional): List of universities to filter by. If nothing is provided, data for all universities will be returned.

Returns:

  • pd.DataFrame: A DataFrame containing the filtered cross-country team rosters. The columns of the returned DataFrame are: University, Name, Sex, Birthday, Program/Position, Eligibility, Hometown, Type, and Recorded Date.

Example:

from usportspy import xc_rosters

# Get the rosters for female teams in the 2024 season
rosters = xc_rosters("w", seasons=[2024])
print(rosters.head())

Expected output:

          University               Name Sex Birthday                         Program/Position  Eligibility           Hometown     Type        Recorded Date
14  Brock University        Robyn Adamo   F     1999  Teacher Education - Intermediate Senior          NaN    Mississauga, ON  Athlete  08/15/2024-17:59:42
15  Brock University  Anna Ciepielewski   F     2004                              Kinesiology          NaN      Brantford, ON  Athlete  08/15/2024-17:59:42
16  Brock University      Elizabeth Gay   F     2000                                      NaN          NaN                NaN  Athlete  08/15/2024-17:59:42
17  Brock University        Cori Macsai   F     2002                                      NaN          NaN  Port Colborne, ON  Athlete  08/15/2024-17:59:42
18  Brock University      Lauren Macsai   F     2002                              Game Design          NaN  Port Colborne, ON  Athlete  08/15/2024-17:59:42

xc_meet_results

Fetches the meet results of cross-country events based on seasons and universities.

Parameters:

  • seasons (list of int, optional): List of seasons (starting year) to filter by. If nothing is provided, data for all seasons will be returned.
  • universities (list of str, optional): List of universities to filter by. If nothing is provided, data for all universities will be returned.

Returns:

  • pd.DataFrame: A DataFrame containing the filtered cross-country meet results. The columns of the returned DataFrame are: Date, Name, Location, and Results.

Example:

from usportspy import xc_meet_results

# Get the meet results for the 2022 season
meet_results = xc_meet_results([2022])
print(meet_results.head())

Expected output:

           Date                          Name               Location                                      Results
493  11/12/2022  USports Cross Country Champs            Halifax, NS  /results/usports-cross-country-champs/9082/
494  10/29/2022                          RSEQ  Kinadapt - Rawdon, QC                          /results/rseq/9077/
495  10/29/2022         Canada West XC Champs         Abbotsford, BC         /results/canada-west-xc-champs/9078/
496  10/29/2022      OUA Cross Country Champs             London, ON      /results/oua-cross-country-champs/9079/
497  10/29/2022          AUS X-Country Champs          Stratford, PE          /results/aus-x-country-champs/9080/

xc_universities

Fetches the list of universities that have cross-country teams.

Parameters:

  • None

Returns:

  • pd.DataFrame: A DataFrame containing the list of universities with cross-country teams. The columns of the returned DataFrame are: University, Conference, Link, Team Version, and Athlete Version.

Example:

from usportspy import xc_universities

# Get the list of universities
universities = xc_universities()
print(universities.head())

Expected output:

              University                    Conference                                               Link Team Version Athlete Version
0       Brock University  Ontario University Athletics  https://www.trackie.com/usports/tnf/universiti...          NaN            BROC
1    Lakehead University  Ontario University Athletics  https://www.trackie.com/usports/tnf/universiti...          NaN            LAKE
2  Laurentian University  Ontario University Athletics  https://www.trackie.com/usports/tnf/universiti...          NaN            LAUR
3    McMaster University  Ontario University Athletics  https://www.trackie.com/usports/tnf/universiti...          NaN            MCMA
4   Nipissing University  Ontario University Athletics  https://www.trackie.com/usports/tnf/universiti...          NaN             NaN