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Update app.py
Browse files
app.py
CHANGED
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@@ -1003,333 +1003,333 @@ pipe_knock.fit(pipe_X,pipe_y)
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joblib.dump(pipe_knock,"./knockout_stage_prediction.pkl")
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pred_set.append({'Team1': row['country1'], 'Team2': row['country2']})
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elif row['potential2'] > row['potential1'] and abs(row['potential2'] - row['potential1']) > 2:
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pred_set.append({'Team1': row['country2'], 'Team2': row['country1']})
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else:
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if row['rank1'] > row['rank2']:
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pred_set.append({'Team1': row['country1'], 'Team2': row['country2']})
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else:
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pred_set.append({'Team1': row['country2'], 'Team2': row['country1']})
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pred_set = pd.DataFrame(pred_set)
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pred_set.insert(2, 'Team1_FIFA_RANK', pred_set['Team1'].map(last_team_scores.set_index('team')['rank']))
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pred_set.insert(3, 'Team2_FIFA_RANK', pred_set['Team2'].map(last_team_scores.set_index('team')['rank']))
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pred_set.insert(4, 'Team1_Goalkeeper_Score',
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pred_set['Team1'].map(last_team_scores.set_index('team')['goalkeeper_score']))
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pred_set.insert(5, 'Team2_Goalkeeper_Score',
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pred_set['Team2'].map(last_team_scores.set_index('team')['goalkeeper_score']))
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pred_set.insert(6, 'Team1_Defense', pred_set['Team1'].map(last_team_scores.set_index('team')['defense_score']))
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pred_set.insert(7, 'Team1_Offense', pred_set['Team1'].map(last_team_scores.set_index('team')['offense_score']))
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pred_set.insert(8, 'Team1_Midfield',
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pred_set['Team1'].map(last_team_scores.set_index('team')['midfield_score']))
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pred_set.insert(9, 'Team2_Defense', pred_set['Team2'].map(last_team_scores.set_index('team')['defense_score']))
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pred_set.insert(10, 'Team2_Offense', pred_set['Team2'].map(last_team_scores.set_index('team')['offense_score']))
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pred_set.insert(11, 'Team2_Midfield',
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pred_set['Team2'].map(last_team_scores.set_index('team')['midfield_score']))
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return pred_set
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def print_results(dataset, y_pred, matches, proba):
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results = []
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for i in range(dataset.shape[0]):
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print()
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if y_pred[i] == 2:
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print(matches.iloc[i, 0] + " vs. " + matches.iloc[i, 1] + " => Draw")
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results.append({'result': 'Draw'})
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elif y_pred[i] == 1:
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print(matches.iloc[i, 0] + " vs. " + matches.iloc[i, 1] + " => Winner: " + dataset.iloc[i, 0])
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results.append({'result': dataset.iloc[i, 0]})
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else:
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# proba_round = rf_ks_model.predict_proba(dataset_round)
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results_round = print_results(dataset_round, prediction_round, round, proba_round)
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return results_round
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def center_str(round):
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spaces = ['', ' ', ' ', ' ', ' ', ' ', ]
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for j in range(2):
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for i in range(round.shape[0]):
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if (13 - len(round.iloc[i, j])) % 2 == 0:
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round.iloc[i, j] = spaces[int((13 - len(round.iloc[i, j])) / 2)] + round.iloc[i, j] + spaces[
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int((13 - len(round.iloc[i, j])) / 2)]
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else:
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round.iloc[i, j] = spaces[int(((13 - len(round.iloc[i, j])) / 2) - 0.5)] + round.iloc[i, j] + \
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spaces[int(((13 - len(round.iloc[i, j])) / 2) + 0.5)]
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return round
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def center2(a):
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spaces = ['', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ',
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' ', ' ', ' ', ' ', ' ',
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' ', ' ', ' ', ' ',
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' ']
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if (29 - len(a)) % 2 == 0:
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a = spaces[int((29 - len(a)) / 2)] + a + spaces[int((29 - len(a)) / 2)]
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joblib.dump(pipe_knock,"./knockout_stage_prediction.pkl")
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st.title("FIFA winner predication")
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st.write('This app predict 2022 FIFA winner')
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if st.button("Predict FIFA Winner"):
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last_team_scores = pd.read_csv('./data/last_team_scores.csv')
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last_team_scores.tail()
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squad_stats = pd.read_csv('./data/squad_stats.csv')
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squad_stats.tail()
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group_matches = pd.read_csv('./data/Qatar_group_stage.csv')
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round_16 = group_matches.iloc[48:56, :]
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quarter_finals = group_matches.iloc[56:60, :]
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semi_finals = group_matches.iloc[60:62, :]
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final = group_matches.iloc[62:63, :]
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second_final = group_matches.iloc[63:64, :]
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group_matches = group_matches.iloc[:48, :]
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group_matches.tail()
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xgb_gs_model = joblib.load("./groups_stage_prediction.pkl")
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xgb_ks_model = joblib.load("./knockout_stage_prediction.pkl")
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team_group = group_matches.drop(['country2'], axis=1)
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team_group = team_group.drop_duplicates().reset_index(drop=True)
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team_group = team_group.rename(columns={"country1": "team"})
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team_group.head(5)
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def matches(g_matches):
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g_matches.insert(2, 'potential1',
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g_matches['country1'].map(squad_stats.set_index('nationality_name')['potential']))
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g_matches.insert(3, 'potential2',
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g_matches['country2'].map(squad_stats.set_index('nationality_name')['potential']))
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g_matches.insert(4, 'rank1', g_matches['country1'].map(last_team_scores.set_index('team')['rank']))
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g_matches.insert(5, 'rank2', g_matches['country2'].map(last_team_scores.set_index('team')['rank']))
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pred_set = []
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for index, row in g_matches.iterrows():
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if row['potential1'] > row['potential2'] and abs(row['potential1'] - row['potential2']) > 2:
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pred_set.append({'Team1': row['country1'], 'Team2': row['country2']})
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elif row['potential2'] > row['potential1'] and abs(row['potential2'] - row['potential1']) > 2:
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pred_set.append({'Team1': row['country2'], 'Team2': row['country1']})
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else:
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if row['rank1'] > row['rank2']:
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pred_set.append({'Team1': row['country1'], 'Team2': row['country2']})
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else:
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pred_set.append({'Team1': row['country2'], 'Team2': row['country1']})
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pred_set = pd.DataFrame(pred_set)
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pred_set.insert(2, 'Team1_FIFA_RANK', pred_set['Team1'].map(last_team_scores.set_index('team')['rank']))
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pred_set.insert(3, 'Team2_FIFA_RANK', pred_set['Team2'].map(last_team_scores.set_index('team')['rank']))
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pred_set.insert(4, 'Team1_Goalkeeper_Score',
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pred_set['Team1'].map(last_team_scores.set_index('team')['goalkeeper_score']))
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pred_set.insert(5, 'Team2_Goalkeeper_Score',
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pred_set['Team2'].map(last_team_scores.set_index('team')['goalkeeper_score']))
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pred_set.insert(6, 'Team1_Defense', pred_set['Team1'].map(last_team_scores.set_index('team')['defense_score']))
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pred_set.insert(7, 'Team1_Offense', pred_set['Team1'].map(last_team_scores.set_index('team')['offense_score']))
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pred_set.insert(8, 'Team1_Midfield',
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pred_set['Team1'].map(last_team_scores.set_index('team')['midfield_score']))
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pred_set.insert(9, 'Team2_Defense', pred_set['Team2'].map(last_team_scores.set_index('team')['defense_score']))
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pred_set.insert(10, 'Team2_Offense', pred_set['Team2'].map(last_team_scores.set_index('team')['offense_score']))
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pred_set.insert(11, 'Team2_Midfield',
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pred_set['Team2'].map(last_team_scores.set_index('team')['midfield_score']))
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return pred_set
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def print_results(dataset, y_pred, matches, proba):
|
| 1073 |
+
results = []
|
| 1074 |
+
for i in range(dataset.shape[0]):
|
| 1075 |
+
print()
|
| 1076 |
+
if y_pred[i] == 2:
|
| 1077 |
+
print(matches.iloc[i, 0] + " vs. " + matches.iloc[i, 1] + " => Draw")
|
| 1078 |
+
results.append({'result': 'Draw'})
|
| 1079 |
+
elif y_pred[i] == 1:
|
| 1080 |
+
print(matches.iloc[i, 0] + " vs. " + matches.iloc[i, 1] + " => Winner: " + dataset.iloc[i, 0])
|
| 1081 |
+
results.append({'result': dataset.iloc[i, 0]})
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1082 |
else:
|
| 1083 |
+
print(matches.iloc[i, 0] + " vs. " + matches.iloc[i, 1] + " => Winner: " + dataset.iloc[i, 1])
|
| 1084 |
+
results.append({'result': dataset.iloc[i, 1]})
|
| 1085 |
+
try:
|
| 1086 |
+
print('Probability of ' + dataset.iloc[i, 0] + ' winning: ', '%.3f' % (proba[i][1]))
|
| 1087 |
+
print('Probability of Draw: ', '%.3f' % (proba[i][2]))
|
| 1088 |
+
print('Probability of ' + dataset.iloc[i, 1] + ' winning: ', '%.3f' % (proba[i][0]))
|
| 1089 |
+
except:
|
| 1090 |
+
print('Probability of ' + dataset.iloc[i, 1] + ' winning: ', '%.3f' % (proba[i][0]))
|
| 1091 |
+
print("")
|
| 1092 |
+
results = pd.DataFrame(results)
|
| 1093 |
+
matches = pd.concat([matches.group, results], axis=1)
|
| 1094 |
+
return matches
|
| 1095 |
+
|
| 1096 |
+
def winner_to_match(round, prev_match):
|
| 1097 |
+
round.insert(0, 'c1', round['country1'].map(prev_match.set_index('group')['result']))
|
| 1098 |
+
round.insert(1, 'c2', round['country2'].map(prev_match.set_index('group')['result']))
|
| 1099 |
+
round = round.drop(['country1', 'country2'], axis=1)
|
| 1100 |
+
round = round.rename(columns={'c1': 'country1', 'c2': 'country2'}).reset_index(drop=True)
|
| 1101 |
+
return round
|
| 1102 |
+
|
| 1103 |
+
def prediction_knockout(round):
|
| 1104 |
+
dataset_round = matches(round)
|
| 1105 |
+
prediction_round = xgb_ks_model.predict(dataset_round)
|
| 1106 |
+
proba_round = xgb_ks_model.predict_proba(dataset_round)
|
| 1107 |
+
|
| 1108 |
+
# prediction_round = ada_ks_model.predict(dataset_round)
|
| 1109 |
+
# proba_round = ada_ks_model.predict_proba(dataset_round)
|
| 1110 |
+
|
| 1111 |
+
# prediction_round = rf_ks_model.predict(dataset_round)
|
| 1112 |
+
# proba_round = rf_ks_model.predict_proba(dataset_round)
|
| 1113 |
+
|
| 1114 |
+
results_round = print_results(dataset_round, prediction_round, round, proba_round)
|
| 1115 |
+
return results_round
|
| 1116 |
+
|
| 1117 |
+
def center_str(round):
|
| 1118 |
+
spaces = ['', ' ', ' ', ' ', ' ', ' ', ]
|
| 1119 |
+
for j in range(2):
|
| 1120 |
+
for i in range(round.shape[0]):
|
| 1121 |
+
if (13 - len(round.iloc[i, j])) % 2 == 0:
|
| 1122 |
+
round.iloc[i, j] = spaces[int((13 - len(round.iloc[i, j])) / 2)] + round.iloc[i, j] + spaces[
|
| 1123 |
+
int((13 - len(round.iloc[i, j])) / 2)]
|
| 1124 |
+
else:
|
| 1125 |
+
round.iloc[i, j] = spaces[int(((13 - len(round.iloc[i, j])) / 2) - 0.5)] + round.iloc[i, j] + \
|
| 1126 |
+
spaces[int(((13 - len(round.iloc[i, j])) / 2) + 0.5)]
|
| 1127 |
+
return round
|
| 1128 |
+
|
| 1129 |
+
def center2(a):
|
| 1130 |
+
spaces = ['', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ',
|
| 1131 |
+
' ', ' ', ' ', ' ', ' ',
|
| 1132 |
+
' ', ' ', ' ', ' ',
|
| 1133 |
+
' ']
|
| 1134 |
+
if (29 - len(a)) % 2 == 0:
|
| 1135 |
+
a = spaces[int((29 - len(a)) / 2)] + a + spaces[int((29 - len(a)) / 2)]
|
| 1136 |
+
else:
|
| 1137 |
+
a = spaces[int(((29 - len(a)) / 2) - 0.5)] + a + spaces[int(((29 - len(a)) / 2) + 0.5)]
|
| 1138 |
+
return a
|
| 1139 |
+
|
| 1140 |
+
dataset_groups = matches(group_matches)
|
| 1141 |
+
dataset_groups.tail()
|
| 1142 |
+
print(dataset_groups)
|
| 1143 |
+
|
| 1144 |
+
prediction_groups = xgb_gs_model.predict(dataset_groups)
|
| 1145 |
+
proba = xgb_gs_model.predict_proba(dataset_groups)
|
| 1146 |
+
|
| 1147 |
+
# prediction_groups = ada_gs_model.predict(dataset_groups)
|
| 1148 |
+
# proba = ada_gs_model.predict_proba(dataset_groups)
|
| 1149 |
+
|
| 1150 |
+
# prediction_groups = rf_gs_model.predict(dataset_groups)
|
| 1151 |
+
# proba = rf_gs_model.predict_proba(dataset_groups)
|
| 1152 |
+
|
| 1153 |
+
results = print_results(dataset_groups, prediction_groups, group_matches, proba)
|
| 1154 |
+
|
| 1155 |
+
team_group['points'] = 0
|
| 1156 |
+
team_group
|
| 1157 |
+
for i in range(results.shape[0]):
|
| 1158 |
+
for j in range(team_group.shape[0]):
|
| 1159 |
+
if results.iloc[i, 1] == team_group.iloc[j, 0]:
|
| 1160 |
+
team_group.iloc[j, 2] += 3
|
| 1161 |
+
|
| 1162 |
+
print(team_group.groupby(['group', 'team']).mean().astype(int))
|
| 1163 |
+
|
| 1164 |
+
round_of_16 = team_group[team_group['points'] > 5].reset_index(drop=True)
|
| 1165 |
+
round_of_16['group'] = (4 - 1 / 3 * round_of_16.points).astype(int).astype(str) + round_of_16.group
|
| 1166 |
+
round_of_16 = round_of_16.rename(columns={"team": "result"})
|
| 1167 |
+
|
| 1168 |
+
round_16 = winner_to_match(round_16, round_of_16)
|
| 1169 |
+
results_round_16 = prediction_knockout(round_16)
|
| 1170 |
+
|
| 1171 |
+
quarter_finals = winner_to_match(quarter_finals, results_round_16)
|
| 1172 |
+
results_quarter_finals = prediction_knockout(quarter_finals)
|
| 1173 |
+
|
| 1174 |
+
semi_finals = winner_to_match(semi_finals, results_quarter_finals)
|
| 1175 |
+
results_finals = prediction_knockout(semi_finals)
|
| 1176 |
+
|
| 1177 |
+
final = winner_to_match(final, results_finals)
|
| 1178 |
+
winner = prediction_knockout(final)
|
| 1179 |
+
|
| 1180 |
+
second = results_finals[~results_finals.result.isin(winner.result)]
|
| 1181 |
+
results_finals_3 = results_quarter_finals[~results_quarter_finals.result.isin(results_finals.result)]
|
| 1182 |
+
results_finals_3.iloc[0, 0] = 'z1'
|
| 1183 |
+
results_finals_3.iloc[1, 0] = 'z2'
|
| 1184 |
+
second_final = winner_to_match(second_final, results_finals_3)
|
| 1185 |
+
third = prediction_knockout(second_final)
|
| 1186 |
+
|
| 1187 |
+
round_16 = center_str(round_16)
|
| 1188 |
+
quarter_finals = center_str(quarter_finals)
|
| 1189 |
+
semi_finals = center_str(semi_finals)
|
| 1190 |
+
final = center_str(final)
|
| 1191 |
+
group_matches = center_str(group_matches)
|
| 1192 |
+
|
| 1193 |
+
# Function to center align text
|
| 1194 |
+
def center(text):
|
| 1195 |
+
return f"<div style='text-align: center;'>{text}</div>"
|
| 1196 |
+
|
| 1197 |
+
# Function to generate the formatted text
|
| 1198 |
+
def generate_text(round_16, quarter_finals, semi_finals, final):
|
| 1199 |
+
formatted_text = (
|
| 1200 |
+
round_16.iloc[
|
| 1201 |
+
0, 0] + '━━━━┓ ┏━━━━' +
|
| 1202 |
+
round_16.iloc[4, 0] + '\n' +
|
| 1203 |
+
' ┃ ┃\n' +
|
| 1204 |
+
' ┃━━━━' + quarter_finals.iloc[
|
| 1205 |
+
0, 0] + '━━━━┓ ┏━━━━' +
|
| 1206 |
+
quarter_finals.iloc[2, 0] + '━━━━┃\n' +
|
| 1207 |
+
' ┃ ┃ ┃ ┃\n' +
|
| 1208 |
+
round_16.iloc[
|
| 1209 |
+
0, 1] + '━━━━┛ ┃ ┃ ┗━━━━' +
|
| 1210 |
+
round_16.iloc[4, 1] + '\n' +
|
| 1211 |
+
' ┃━━━━' + semi_finals.iloc[
|
| 1212 |
+
0, 0] + '━━━━┓ ┏━━━━' + semi_finals.iloc[1, 0] + '━━━━┃\n' +
|
| 1213 |
+
round_16.iloc[
|
| 1214 |
+
1, 0] + '━━━━┓ ┃ ┃ ┃ ┃ ┏━━━━' +
|
| 1215 |
+
round_16.iloc[5, 0] + '\n' +
|
| 1216 |
+
' ┃ ┃ ┃ ┃ ┃ ┃\n' +
|
| 1217 |
+
' ┃━━━━' + quarter_finals.iloc[
|
| 1218 |
+
0, 1] + '━━━━┛ ┃ ┃ ┗━━━━' +
|
| 1219 |
+
quarter_finals.iloc[2, 1] + '━━━━┃\n' +
|
| 1220 |
+
' ┃ ┃ ┃ ┃\n' +
|
| 1221 |
+
round_16.iloc[
|
| 1222 |
+
1, 1] + '━━━━┛ ┃ ┃ ┗━━━━' +
|
| 1223 |
+
round_16.iloc[5, 1] + '\n' +
|
| 1224 |
+
' ┃━━━━' + final.iloc[0, 0] + 'vs.' +
|
| 1225 |
+
final.iloc[0, 1] + '━━━━┃\n' +
|
| 1226 |
+
round_16.iloc[
|
| 1227 |
+
2, 0] + '━━━━┓ ┃ ┃ ┏━━━━' +
|
| 1228 |
+
round_16.iloc[6, 0] + '\n' +
|
| 1229 |
+
' ┃ ┃ ┃ ┃\n' +
|
| 1230 |
+
' ┃━━━━' + quarter_finals.iloc[
|
| 1231 |
+
1, 0] + '━━━━┓ ┃ ┃ ┏━━━━' +
|
| 1232 |
+
quarter_finals.iloc[3, 0] + '━━━━┃\n' +
|
| 1233 |
+
' ┃ ┃ ┃ ┃ ┃ ┃\n' +
|
| 1234 |
+
round_16.iloc[
|
| 1235 |
+
2, 1] + '━━━━┛ ┃ ┃ ┃ ┃ ┗━━━━' +
|
| 1236 |
+
round_16.iloc[6, 1] + '\n' +
|
| 1237 |
+
' ┃━━━━' + semi_finals.iloc[
|
| 1238 |
+
0, 1] + '━━━━┛ ┗━━━━' + semi_finals.iloc[1, 1] + '━━━━┃\n' +
|
| 1239 |
+
round_16.iloc[
|
| 1240 |
+
3, 0] + '━━━━┓ ┃ ┃ ┏━━━━' +
|
| 1241 |
+
round_16.iloc[7, 0] + '\n' +
|
| 1242 |
+
' ┃ ┃ ┃ ┃\n' +
|
| 1243 |
+
' ┃━━━━' + quarter_finals.iloc[
|
| 1244 |
+
1, 1] + '━━━━┛ ┗━━━━' +
|
| 1245 |
+
quarter_finals.iloc[3, 1] + '━━━━┃\n' +
|
| 1246 |
+
' ┃ ┃\n' +
|
| 1247 |
+
round_16.iloc[
|
| 1248 |
+
3, 1] + '━━━━┛ ┗━━━━' +
|
| 1249 |
+
round_16.iloc[7, 1] + '\n' +
|
| 1250 |
+
" " + center(
|
| 1251 |
+
"\U0001F947" + winner.iloc[0, 1]) + '\n' +
|
| 1252 |
+
" " + center(
|
| 1253 |
+
"\U0001F948" + second.iloc[0, 1]) + '\n' +
|
| 1254 |
+
" " + center(
|
| 1255 |
+
"\U0001F949" + third.iloc[0, 1])
|
| 1256 |
+
)
|
| 1257 |
+
return formatted_text
|
| 1258 |
+
|
| 1259 |
+
# Generate the formatted text
|
| 1260 |
+
formatted_text = generate_text(round_16, quarter_finals, semi_finals, final)
|
| 1261 |
+
|
| 1262 |
+
# Define the round_16, quarter_finals, semi_finals, final DataFrames
|
| 1263 |
+
# Replace the DataFrame creation with your actual data
|
| 1264 |
+
|
| 1265 |
+
# Display the formatted text
|
| 1266 |
+
st.text(formatted_text)
|
| 1267 |
+
# st.markdown(formatted_text)
|
| 1268 |
+
|
| 1269 |
+
print(round_16.iloc[
|
| 1270 |
+
0, 0] + '━━━━┓ ┏━━━━' +
|
| 1271 |
+
round_16.iloc[4, 0])
|
| 1272 |
+
print(
|
| 1273 |
+
' ┃ ┃')
|
| 1274 |
+
print(' ┃━━━━' + quarter_finals.iloc[
|
| 1275 |
+
0, 0] + '━━━━┓ ┏━━━━' +
|
| 1276 |
+
quarter_finals.iloc[2, 0] + '━━━━┃')
|
| 1277 |
+
print(
|
| 1278 |
+
' ┃ ┃ ┃ ┃')
|
| 1279 |
+
print(round_16.iloc[
|
| 1280 |
+
0, 1] + '━━━━┛ ┃ ┃ ┗━━━━' +
|
| 1281 |
+
round_16.iloc[4, 1])
|
| 1282 |
+
print(' ┃━━━━' + semi_finals.iloc[
|
| 1283 |
+
0, 0] + '━━━━┓ ┏━━━━' + semi_finals.iloc[1, 0] + '━━━━┃')
|
| 1284 |
+
print(round_16.iloc[
|
| 1285 |
+
1, 0] + '━━━━┓ ┃ ┃ ┃ ┃ ┏━━━━' +
|
| 1286 |
+
round_16.iloc[5, 0])
|
| 1287 |
+
print(
|
| 1288 |
+
' ┃ ┃ ┃ ┃ ┃ ┃')
|
| 1289 |
+
print(' ┃━━━━' + quarter_finals.iloc[
|
| 1290 |
+
0, 1] + '━━━━┛ ┃ ┃ ┗━━━━' +
|
| 1291 |
+
quarter_finals.iloc[2, 1] + '━━━━┃')
|
| 1292 |
+
print(
|
| 1293 |
+
' ┃ ┃ ┃ ┃')
|
| 1294 |
+
print(round_16.iloc[
|
| 1295 |
+
1, 1] + '━━━━┛ ┃ ┃ ┗━━━━' +
|
| 1296 |
+
round_16.iloc[5, 1])
|
| 1297 |
+
print(' ┃━━━━' + final.iloc[0, 0] + 'vs.' + final.iloc[
|
| 1298 |
+
0, 1] + '━━━━┃')
|
| 1299 |
+
print(round_16.iloc[
|
| 1300 |
+
2, 0] + '━━━━┓ ┃ ┃ ┏━━━━' +
|
| 1301 |
+
round_16.iloc[6, 0])
|
| 1302 |
+
print(
|
| 1303 |
+
' ┃ ┃ ┃ ┃')
|
| 1304 |
+
print(' ┃━━━━' + quarter_finals.iloc[
|
| 1305 |
+
1, 0] + '━━━━┓ ┃ ┃ ┏━━━━' +
|
| 1306 |
+
quarter_finals.iloc[3, 0] + '━━━━┃')
|
| 1307 |
+
print(
|
| 1308 |
+
' ┃ ┃ ┃ ┃ ┃ ┃')
|
| 1309 |
+
print(round_16.iloc[
|
| 1310 |
+
2, 1] + '━━━━┛ ┃ ┃ ┃ ┃ ┗━━━━' +
|
| 1311 |
+
round_16.iloc[6, 1])
|
| 1312 |
+
print(' ┃━━━━' + semi_finals.iloc[
|
| 1313 |
+
0, 1] + '━━━━┛ ┗━━━━' + semi_finals.iloc[1, 1] + '━━━━┃')
|
| 1314 |
+
print(round_16.iloc[
|
| 1315 |
+
3, 0] + '━━━━┓ ┃ ┃ ┏━━━━' +
|
| 1316 |
+
round_16.iloc[7, 0])
|
| 1317 |
+
print(
|
| 1318 |
+
' ┃ ┃ ┃ ┃')
|
| 1319 |
+
print(' ┃━━━━' + quarter_finals.iloc[
|
| 1320 |
+
1, 1] + '━━━━┛ ┗━━━━' +
|
| 1321 |
+
quarter_finals.iloc[3, 1] + '━━━━┃')
|
| 1322 |
+
print(
|
| 1323 |
+
' ┃ ┃')
|
| 1324 |
+
print(round_16.iloc[
|
| 1325 |
+
3, 1] + '━━━━┛ ┗━━━━' +
|
| 1326 |
+
round_16.iloc[7, 1])
|
| 1327 |
+
print(
|
| 1328 |
+
" " + center2("\U0001F947" + winner.iloc[0, 1]))
|
| 1329 |
+
print(
|
| 1330 |
+
" " + center2("\U0001F948" + second.iloc[0, 1]))
|
| 1331 |
+
print(
|
| 1332 |
+
" " + center2("\U0001F949" + third.iloc[0, 1]))
|
| 1333 |
|
| 1334 |
|
| 1335 |
|