122 lines
3.2 KiB
Python
122 lines
3.2 KiB
Python
from data_filters import *
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import pandas as pd
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def categorize_shots(shots):
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if shots >= 12:
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return 2
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elif shots <= 6:
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return 0
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else:
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return 1
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def categorize_passes(pass_count):
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if pass_count < 400:
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return 0 #słabo
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elif 400 <= pass_count <= 500:
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return 1 #średnio
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else:
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return 2 #dużo
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def categorize_possesion(shots):
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if shots >= 56:
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return 2
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elif shots <= 40:
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return 0
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else:
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return 1
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def categorize_points(data, row, teamHome, matches_type):
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if teamHome:
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data_5 = matches_type(row['season'], row['home_team'], row['date'], data)
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points = calculatePoints(data_5,row['home_team'])
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else:
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data_5 = matches_type(row['season'], row['away_team'], row['date'], data)
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points = calculatePoints(data_5,row['away_team'])
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if points <=1:
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return 0
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elif points >=2:
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return 2
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else:
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return 1
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def get_method(data, home_away, method, matches_type):
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values = []
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for index, row in data.iterrows():
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values.append(method(data, row, home_away, matches_type))
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return values
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def get_points_home(data):
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points = []
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for index, row in data.iterrows():
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points.append(categorize_points(data, row, True))
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return points
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def get_points_away(data):
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points = []
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for index, row in data.iterrows():
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points.append(categorize_points(data, row, False))
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return points
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def categorize_diff(data, row, teamHome, matches_type):
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if teamHome:
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data_5 = matches_type(row['season'], row['home_team'], row['date'], data)
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diff = calculateGoalDifference(data_5,row['home_team'])
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else:
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data_5 = matches_type(row['season'], row['away_team'], row['date'], data)
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diff = calculateGoalDifference(data_5,row['away_team'])
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if diff <=0:
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return 0
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else:
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return 1
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def categorize_aggression(data, row, teamHome, matches_type):
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if teamHome:
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data_5 = matches_type(row['season'], row['home_team'], row['date'], data)
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diff = calculateAggression(data_5,row['home_team'])
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else:
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data_5 = matches_type(row['season'], row['away_team'], row['date'], data)
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diff = calculateAggression(data_5,row['away_team'])
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return diff
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# if diff <=0:
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# return 0
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# else:
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# return 1
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def get_diff_home(data):
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points = []
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for index, row in data.iterrows():
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points.append(categorize_diff(data, row, True))
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return points
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def get_diff_away(data):
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points = []
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for index, row in data.iterrows():
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points.append(categorize_diff(data, row, False))
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return points
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def add_column(data_frame, transform_function, new_column, existing_column=None):
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if existing_column != None:
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new_column_values = data_frame[existing_column].apply(transform_function)
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data_frame[new_column] = new_column_values
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else:
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new_column_values = transform_function
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data_frame[new_column] = new_column_values
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return data_frame
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def get_result_list(df, home_team):
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results = []
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for score in df['result_full']:
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results.append(getResult(score,home_team))
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return results
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