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import pandas as pd
In [31]:
doosan_pb_df = pd.read_csv("basic/doosan_pb_15.csv")
hanhwa_pb_df = pd.read_csv("basic/hanhwa_pb_15.csv")
KIA_pb_df = pd.read_csv("basic/KIA_pb_15.csv")
KT_pb_df = pd.read_csv("basic/KT_pb_15.csv")
LG_pb_df = pd.read_csv("basic/LG_pb_15.csv")
lotte_pb_df = pd.read_csv("basic/lotte_pb_15.csv")
NC_pb_df = pd.read_csv("basic/NC_pb_15.csv")
nexen_pb_df = pd.read_csv("basic/nexen_pb_15.csv")
samsung_pb_df = pd.read_csv("basic/samsung_pb_15.csv")
SK_pb_df = pd.read_csv("basic/SK_pb_15.csv")
In [32]:
doosan_pd_df = pd.read_csv("detail/doosan_pd_15.csv")
hanhwa_pd_df = pd.read_csv("detail/hanhwa_pd_15.csv")
KIA_pd_df = pd.read_csv("detail/KIA_pd_15.csv")
KT_pd_df = pd.read_csv("detail/KT_pd_15.csv")
LG_pd_df = pd.read_csv("detail/LG_pd_15.csv")
lotte_pd_df = pd.read_csv("detail/lotte_pd_15.csv")
NC_pd_df = pd.read_csv("detail/NC_pd_15.csv")
nexen_pd_df = pd.read_csv("detail/nexen_pd_15.csv")
samsung_pd_df = pd.read_csv("detail/samsung_pd_15.csv")
SK_pd_df = pd.read_csv("detail/SK_pd_15.csv")
In [33]:
doosan_df = doosan_pb_df.merge(doosan_pd_df, left_on="name",right_on="name")[["name", "team_x", "ERA_x", "G", "W", "L", "SV", "HLD", "WPCT", "IP", "H", "HR", "BB", "HBP", "SO", "R", "ER", "WHIP", "GS", "Wgs", "Wgr", "GF", "SVO", "TS", "GDP", "GO", "AO", "GO/AO"]]
hanhwa_df = hanhwa_pb_df.merge(hanhwa_pd_df, left_on="name",right_on="name")[["name", "team_x", "ERA_x", "G", "W", "L", "SV", "HLD", "WPCT", "IP", "H", "HR", "BB", "HBP", "SO", "R", "ER", "WHIP", "GS", "Wgs", "Wgr", "GF", "SVO", "TS", "GDP", "GO", "AO", "GO/AO"]]
KIA_df = KIA_pb_df.merge(KIA_pd_df, left_on="name",right_on="name")[["name", "team_x", "ERA_x", "G", "W", "L", "SV", "HLD", "WPCT", "IP", "H", "HR", "BB", "HBP", "SO", "R", "ER", "WHIP", "GS", "Wgs", "Wgr", "GF", "SVO", "TS", "GDP", "GO", "AO", "GO/AO"]]
KT_df = KT_pb_df.merge(KT_pd_df, left_on="name",right_on="name")[["name", "team_x", "ERA_x", "G", "W", "L", "SV", "HLD", "WPCT", "IP", "H", "HR", "BB", "HBP", "SO", "R", "ER", "WHIP", "GS", "Wgs", "Wgr", "GF", "SVO", "TS", "GDP", "GO", "AO", "GO/AO"]]
LG_df = LG_pb_df.merge(LG_pd_df, left_on="name",right_on="name")[["name", "team_x", "ERA_x", "G", "W", "L", "SV", "HLD", "WPCT", "IP", "H", "HR", "BB", "HBP", "SO", "R", "ER", "WHIP", "GS", "Wgs", "Wgr", "GF", "SVO", "TS", "GDP", "GO", "AO", "GO/AO"]]
lotte_df = lotte_pb_df.merge(lotte_pd_df, left_on="name",right_on="name")[["name", "team_x", "ERA_x", "G", "W", "L", "SV", "HLD", "WPCT", "IP", "H", "HR", "BB", "HBP", "SO", "R", "ER", "WHIP", "GS", "Wgs", "Wgr", "GF", "SVO", "TS", "GDP", "GO", "AO", "GO/AO"]]
NC_df = NC_pb_df.merge(NC_pd_df, left_on="name",right_on="name")[["name", "team_x", "ERA_x", "G", "W", "L", "SV", "HLD", "WPCT", "IP", "H", "HR", "BB", "HBP", "SO", "R", "ER", "WHIP", "GS", "Wgs", "Wgr", "GF", "SVO", "TS", "GDP", "GO", "AO", "GO/AO"]]
nexen_df = nexen_pb_df.merge(nexen_pd_df, left_on="name",right_on="name")[["name", "team_x", "ERA_x", "G", "W", "L", "SV", "HLD", "WPCT", "IP", "H", "HR", "BB", "HBP", "SO", "R", "ER", "WHIP", "GS", "Wgs", "Wgr", "GF", "SVO", "TS", "GDP", "GO", "AO", "GO/AO"]]
samsung_df = samsung_pb_df.merge(samsung_pd_df, left_on="name",right_on="name")[["name", "team_x", "ERA_x", "G", "W", "L", "SV", "HLD", "WPCT", "IP", "H", "HR", "BB", "HBP", "SO", "R", "ER", "WHIP", "GS", "Wgs", "Wgr", "GF", "SVO", "TS", "GDP", "GO", "AO", "GO/AO"]]
SK_df = SK_pb_df.merge(SK_pd_df, left_on="name",right_on="name")[["name", "team_x", "ERA_x", "G", "W", "L", "SV", "HLD", "WPCT", "IP", "H", "HR", "BB", "HBP", "SO", "R", "ER", "WHIP", "GS", "Wgs", "Wgr", "GF", "SVO", "TS", "GDP", "GO", "AO", "GO/AO"]]
In [34]:
doosan_df = doosan_df.rename(columns={"team_x":"team"})
hanhwa_df = hanhwa_df.rename(columns={"team_x":"team"})
KIA_df = KIA_df.rename(columns={"team_x":"team"})
KT_df = KT_df.rename(columns={"team_x":"team"})
LG_df = LG_df.rename(columns={"team_x":"team"})
lotte_df = lotte_df.rename(columns={"team_x":"team"})
NC_df = NC_df.rename(columns={"team_x":"team"})
nexen_df = nexen_df.rename(columns={"team_x":"team"})
samsung_df = samsung_df.rename(columns={"team_x":"team"})
SK_df = SK_df.rename(columns={"team_x":"team"})
In [35]:
doosan_df = doosan_df.rename(columns={"ERA_x":"ERA"})
hanhwa_df = hanhwa_df.rename(columns={"ERA_x":"ERA"})
KIA_df = KIA_df.rename(columns={"ERA_x":"ERA"})
KT_df = KT_df.rename(columns={"ERA_x":"ERA"})
LG_df = LG_df.rename(columns={"ERA_x":"ERA"})
lotte_df = lotte_df.rename(columns={"ERA_x":"ERA"})
NC_df = NC_df.rename(columns={"ERA_x":"ERA"})
nexen_df = nexen_df.rename(columns={"ERA_x":"ERA"})
samsung_df = samsung_df.rename(columns={"ERA_x":"ERA"})
SK_df = SK_df.rename(columns={"ERA_x":"ERA"})
In [36]:
doosan_df.to_csv("doosan_pitcher.csv",encoding='utf-8')
hanhwa_df.to_csv("hanhwa_pitcher.csv",encoding='utf-8')
KIA_df.to_csv("KIA_pitcher.csv",encoding='utf-8')
KT_df.to_csv("KT_pitcher.csv",encoding='utf-8')
LG_df.to_csv("LG_pitcher.csv",encoding='utf-8')
lotte_df.to_csv("lotte_pitcher.csv",encoding='utf-8')
NC_df.to_csv("NC_pitcher.csv",encoding='utf-8')
nexen_df.to_csv("nexen_pitcher.csv",encoding='utf-8')
samsung_df.to_csv("samsung_pitcher.csv",encoding='utf-8')
SK_df.to_csv("SK_pitcher.csv",encoding='utf-8')
In [37]:
pitcher_df = pd.concat([doosan_df, hanhwa_df, KIA_df, KT_df, LG_df, lotte_df, NC_df, nexen_df, samsung_df, SK_df]).reset_index(drop=True)
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pitcher_df.to_csv("pitcher_final.csv",encoding="utf-8")
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pitcher_df
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