BlueSCar

class PermutationImportance():
  def __init__(self, learn:Learner, df=None, bs=None):
    "Initialize with a test dataframe, a learner, and a metric"
    self.learn = learn
    self.df = df
    bs = bs if bs is not None else learn.dls.bs
    if self.df is not None:
      self.dl = learn.dls.test_dl(self.df, bs=bs)
    else:
      self.dl = learn.dls[1]

BlueSCar

import cfbd
import matplotlib.pyplot as plt
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
import pandas as pd

# Grab some stats from the CFBD API
stats = cfbd.StatsApi().get_advanced_team_season_stats(year=2020)
df = pd.DataFrame.from_records([dict(team=s.team, o_line_yards=s.offense.line_yards, d_line_yards=s.defense.line_yards) for s in stats])

# Need to grab team ids

BlueSCar

import cfbd
import pandas as pd

games = cfbd.GamesApi().get_team_game_stats(year=2020, week=1)

stats = []
for g in games:
    for t in g.teams:
        for s in t.stats:
            stats.append(dict(game_id=g.id, team=t.school, conference=t.conference, category=s.category, stat=s.stat))

BlueSCar

import numpy as np
import pandas as pd
import requests

pd.set_option('display.float_format', lambda x: '%.8f' % x)

season = 2
day = 3

response = requests.get('https://collegefootballrisk.com/api/territories', params={'season': season, 'day': day})

BlueSCar

import pandas as pd
import requests

response = requests.get(
    "https://api.collegefootballdata.com/games/players",
    params={"year": 2019, "week": "1"}
)

records = pd.io.json.json_normalize(
    response.json(),

BlueSCar

[{
    typeId: 3,
    regex: /(?:Fumble by [^,]+, )?(?:([A-Z][^,\s]+(?: [A-Z][^,\s]+)+)|(?:N\/A))(?:(?: pass incomplete(?: to )*)([A-Z][^,\s]+(?: [A-Z'][^,\s]*)+)*)*(?:(?:, broken up by )([A-Z][^,\s]+(?: [A-Z][^,\s]+)+))*/g,
    types: [{
        id: 1,
        isOffense: true,
        yardageStat: false
    }, {
        id: 2,
        isOffense: true,