text_plain_output_1.png
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

allteams_2010 = pd.read_csv('../input/ncaa-bpi-ranks-by-year/Ranking csv/ESPN Rank 2009-2010.csv')
allteams_2011 = pd.read_csv('../input/ncaa-bpi-ranks-by-year/Ranking csv/ESPN Rank 2010-2011.csv')
allteams_2012 = pd.read_csv('../input/ncaa-bpi-ranks-by-year/Ranking csv/ESPN Rank 2011-2012.csv')
allteams_2013 = pd.read_csv('../input/ncaa-bpi-ranks-by-year/Ranking csv/ESPN Rank 2012-2013.csv')
allteams_2014 = pd.read_csv('../input/ncaa-bpi-ranks-by-year/Ranking csv/ESPN Rank 2013-2014.csv')
allteams_2015 = pd.read_csv('../input/ncaa-bpi-ranks-by-year/Ranking csv/ESPN Rank 2014-2015.csv')
allteams_2016 = pd.read_csv('../input/ncaa-bpi-ranks-by-year/Ranking csv/ESPN Rank 2015-2016.csv')
allteams_2017 = pd.read_csv('../input/ncaa-bpi-ranks-by-year/Ranking csv/ESPN Rank 2016-2017.csv')
allteams_2018 = pd.read_csv('../input/ncaa-bpi-ranks-by-year/Ranking csv/ESPN Rank 2017-2018.csv')
allteams_2019 = pd.read_csv('../input/ncaa-bpi-ranks-by-year/Ranking csv/ESPN Rank 2018-2019.csv')
allteams_2021 = pd.read_csv('../input/ncaa-bpi-ranks-by-year/Ranking csv/ESPN Rank 2020-2021.csv')

allteams_list = [allteams_2010, allteams_2011, allteams_2012, allteams_2013, allteams_2014, allteams_2015, allteams_2016, allteams_2017, allteams_2018, allteams_2019, allteams_2021]

teamstats_2010 = pd.read_csv('../input/team-stats-csv/Team Stats CSV/2010 Team Stats.csv', skiprows=[0])
teamstats_2011 = pd.read_csv('../input/team-stats-csv/Team Stats CSV/2011 Team Stats.csv', skiprows=[0])
teamstats_2012 = pd.read_csv('../input/team-stats-csv/Team Stats CSV/2012 Team Stats.csv', skiprows=[0])
teamstats_2013 = pd.read_csv('../input/team-stats-csv/Team Stats CSV/2013 Team Stats.csv', skiprows=[0])
teamstats_2014 = pd.read_csv('../input/team-stats-csv/Team Stats CSV/2014 Team Stats.csv', skiprows=[0])
teamstats_2015 = pd.read_csv('../input/team-stats-csv/Team Stats CSV/2015 Team Stats.csv', skiprows=[0])
teamstats_2016 = pd.read_csv('../input/team-stats-csv/Team Stats CSV/2016 Team Stats.csv', skiprows=[0])
teamstats_2017 = pd.read_csv('../input/team-stats-csv/Team Stats CSV/2017 Team Stats.csv', skiprows=[0])
teamstats_2018 = pd.read_csv('../input/team-stats-csv/Team Stats CSV/2018 Team Stats.csv', skiprows=[0])
teamstats_2019 = pd.read_csv('../input/team-stats-csv/Team Stats CSV/2019 Team Stats.csv', skiprows=[0])
teamstats_2021 = pd.read_csv('../input/team-stats-csv/Team Stats CSV/2021 Team Stats.csv', skiprows=[0])

teamstats_list = [teamstats_2010, teamstats_2011, teamstats_2012, teamstats_2013, teamstats_2014, teamstats_2015, teamstats_2016, teamstats_2017, teamstats_2018, teamstats_2019, teamstats_2021]

i = 0
for df in teamstats_list:
    df.School = df.School.str.rstrip()
    year_val = 2010 + i
    years = [year_val] * df.shape[0]
    df['YEAR'] = years
    i += 1

year_val = 2021
years = [year_val] * df.shape[0]
teamstats_2021['YEAR'] = [year_val] * teamstats_2021.shape[0]

teamstats_2010_2021 = pd.concat(teamstats_list)

i = 0
for df in allteams_list:
    df[['W', 'L']] = df['W-L'].str.split('-', expand=True)
    df.drop(['W-L'], inplace=True, axis=1)
    year_val = 2010 + i
    years = [year_val] * df.shape[0]
    df['YEAR'] = years
    i += 1

allteams_2010_2021 = pd.concat(allteams_list)

schoolname_list1 = teamstats_2010_2021.School.unique()
schoolname_list1.sort()

schoolname_list2 = allteams_2010_2021.TEAM.unique()
schoolname_list2.sort()

print(len(schoolname_list2))
print(len(schoolname_list2))
for i in range(len(schoolname_list1)):
    print(schoolname_list1[i], '-', schoolname_list2[i])