Delete api_scraper.py
Browse files- api_scraper.py +0 -927
api_scraper.py
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import requests
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import polars as pl
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import numpy as np
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from datetime import datetime
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from tqdm import tqdm
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from pytz import timezone
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import re
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from concurrent.futures import ThreadPoolExecutor, as_completed
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import time
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class MLB_Scrape:
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def __init__(self):
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# Initialize your class here if needed
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pass
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def get_sport_id(self):
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"""
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Retrieves the list of sports from the MLB API and processes it into a Polars DataFrame.
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Returns:
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- df (pl.DataFrame): A DataFrame containing the sports information.
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"""
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# Make API call to retrieve sports information
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response = requests.get(url='https://statsapi.mlb.com/api/v1/sports').json()
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# Convert the JSON response into a Polars DataFrame
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df = pl.DataFrame(response['sports'])
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return df
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def get_sport_id_check(self, sport_id: int = 1):
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"""
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Checks if the provided sport ID exists in the list of sports retrieved from the MLB API.
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Parameters:
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- sport_id (int): The sport ID to check. Default is 1.
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Returns:
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- bool: True if the sport ID exists, False otherwise. If False, prints the available sport IDs.
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"""
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# Retrieve the list of sports from the MLB API
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sport_id_df = self.get_sport_id()
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# Check if the provided sport ID exists in the DataFrame
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if sport_id not in sport_id_df['id']:
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print('Please Select a New Sport ID from the following')
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print(sport_id_df)
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return False
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return True
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def get_game_types(self):
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"""
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Retrieves the different types of MLB games from the MLB API and processes them into a Polars DataFrame.
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Returns:
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- df (pl.DataFrame): A DataFrame containing the game types information.
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"""
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# Make API call to retrieve game types information
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response = requests.get(url='https://statsapi.mlb.com/api/v1/gameTypes').json()
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# Convert the JSON response into a Polars DataFrame
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df = pl.DataFrame(response)
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return df
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def get_schedule(self,
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year_input: list = [2024],
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sport_id: list = [1],
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game_type: list = ['R']):
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"""
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Retrieves the schedule of baseball games based on the specified parameters.
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Parameters:
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- year_input (list): A list of years to filter the schedule. Default is [2024].
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- sport_id (list): A list of sport IDs to filter the schedule. Default is [1].
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- game_type (list): A list of game types to filter the schedule. Default is ['R'].
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Returns:
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- game_df (pandas.DataFrame): A DataFrame containing the game schedule information, including game ID, date, time, away team, home team, game state, venue ID, and venue name. If the schedule length is 0, it returns a message indicating that different parameters should be selected.
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"""
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# Type checks
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if not isinstance(year_input, list) or not all(isinstance(year, int) for year in year_input):
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raise ValueError("year_input must be a list of integers.")
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if not isinstance(sport_id, list) or not all(isinstance(sid, int) for sid in sport_id):
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raise ValueError("sport_id must be a list of integers.")
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if not isinstance(game_type, list) or not all(isinstance(gt, str) for gt in game_type):
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raise ValueError("game_type must be a list of strings.")
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eastern = timezone('US/Eastern')
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# Convert input lists to comma-separated strings
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year_input_str = ','.join([str(x) for x in year_input])
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sport_id_str = ','.join([str(x) for x in sport_id])
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game_type_str = ','.join([str(x) for x in game_type])
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# Make API call to retrieve game schedule
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game_call = requests.get(url=f'https://statsapi.mlb.com/api/v1/schedule/?sportId={sport_id_str}&gameTypes={game_type_str}&season={year_input_str}&hydrate=lineup,players').json()
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# Extract relevant data from the API response
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game_list = [item for sublist in [[y['gamePk'] for y in x['games']] for x in game_call['dates']] for item in sublist]
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time_list = [item for sublist in [[y['gameDate'] for y in x['games']] for x in game_call['dates']] for item in sublist]
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date_list = [item for sublist in [[y['officialDate'] for y in x['games']] for x in game_call['dates']] for item in sublist]
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away_team_list = [item for sublist in [[y['teams']['away']['team']['name'] for y in x['games']] for x in game_call['dates']] for item in sublist]
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home_team_list = [item for sublist in [[y['teams']['home']['team']['name'] for y in x['games']] for x in game_call['dates']] for item in sublist]
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state_list = [item for sublist in [[y['status']['codedGameState'] for y in x['games']] for x in game_call['dates']] for item in sublist]
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venue_id = [item for sublist in [[y['venue']['id'] for y in x['games']] for x in game_call['dates']] for item in sublist]
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venue_name = [item for sublist in [[y['venue']['name'] for y in x['games']] for x in game_call['dates']] for item in sublist]
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# Create a Polars DataFrame with the extracted data
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game_df = pl.DataFrame(data={'game_id': game_list,
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'time': time_list,
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'date': date_list,
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'away': away_team_list,
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'home': home_team_list,
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'state': state_list,
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'venue_id': venue_id,
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'venue_name': venue_name})
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# Check if the DataFrame is empty
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if len(game_df) == 0:
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return 'Schedule Length of 0, please select different parameters.'
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# Convert date and time columns to appropriate formats
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game_df = game_df.with_columns(
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game_df['date'].str.to_date(),
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game_df['time'].str.to_datetime().dt.convert_time_zone(eastern.zone).dt.strftime("%I:%M %p"))
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# Remove duplicate games and sort by date
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game_df = game_df.unique(subset='game_id').sort('date')
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# Check again if the DataFrame is empty after processing
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if len(game_df) == 0:
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return 'Schedule Length of 0, please select different parameters.'
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return game_df
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def get_data(self, game_list_input: list):
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"""
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Retrieves live game data for a list of game IDs.
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Parameters:
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- game_list_input (list): A list of game IDs for which to retrieve live data.
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Returns:
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- data_total (list): A list of JSON responses containing live game data for each game ID.
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"""
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data_total = []
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print('This May Take a While. Progress Bar shows Completion of Data Retrieval.')
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# Iterate over the list of game IDs with a progress bar
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for i in tqdm(range(len(game_list_input)), desc="Processing", unit="iteration"):
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# Make a GET request to the MLB API for each game ID
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r = requests.get(f'https://statsapi.mlb.com/api/v1.1/game/{game_list_input[i]}/feed/live')
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# Append the JSON response to the data_total list
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data_total.append(r.json())
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return data_total
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return data_total
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def get_data_df(self, data_list):
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"""
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Converts a list of game data JSON objects into a Polars DataFrame.
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Parameters:
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- data_list (list): A list of JSON objects containing game data.
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Returns:
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- data_df (pl.DataFrame): A DataFrame containing the structured game data.
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"""
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swing_list = ['X','F','S','D','E','T','W']
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whiff_list = ['S','T','W']
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print('Converting Data to Dataframe.')
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game_id = []
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game_date = []
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batter_id = []
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batter_name = []
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batter_hand = []
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batter_team = []
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batter_team_id = []
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pitcher_id = []
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pitcher_name = []
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pitcher_hand = []
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pitcher_team = []
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pitcher_team_id = []
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play_description = []
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play_code = []
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in_play = []
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is_strike = []
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is_swing = []
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is_whiff = []
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is_out = []
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is_ball = []
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is_review = []
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pitch_type = []
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pitch_description = []
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strikes = []
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balls = []
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outs = []
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strikes_after = []
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balls_after = []
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outs_after = []
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start_speed = []
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end_speed = []
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sz_top = []
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sz_bot = []
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x = []
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y = []
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ax = []
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ay = []
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az = []
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pfxx = []
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pfxz = []
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px = []
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pz = []
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vx0 = []
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vy0 = []
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vz0 = []
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x0 = []
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y0 = []
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z0 = []
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zone = []
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type_confidence = []
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plate_time = []
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extension = []
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spin_rate = []
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spin_direction = []
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vb = []
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ivb = []
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hb = []
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launch_speed = []
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launch_angle = []
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launch_distance = []
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launch_location = []
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trajectory = []
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hardness = []
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hit_x = []
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hit_y = []
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index_play = []
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play_id = []
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start_time = []
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end_time = []
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is_pitch = []
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type_type = []
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type_ab = []
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ab_number = []
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event = []
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event_type = []
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rbi = []
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away_score = []
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home_score = []
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for data in data_list:
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for ab_id in range(len(data['liveData']['plays']['allPlays'])):
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ab_list = data['liveData']['plays']['allPlays'][ab_id]
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for n in range(len(ab_list['playEvents'])):
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if ab_list['playEvents'][n]['isPitch'] == True or 'call' in ab_list['playEvents'][n]['details']:
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ab_number.append(ab_list['atBatIndex'] if 'atBatIndex' in ab_list else None)
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game_id.append(data['gamePk'])
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game_date.append(data['gameData']['datetime']['officialDate'])
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if 'matchup' in ab_list:
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batter_id.append(ab_list['matchup']['batter']['id'] if 'batter' in ab_list['matchup'] else None)
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if 'batter' in ab_list['matchup']:
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batter_name.append(ab_list['matchup']['batter']['fullName'] if 'fullName' in ab_list['matchup']['batter'] else None)
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else:
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batter_name.append(None)
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batter_hand.append(ab_list['matchup']['batSide']['code'] if 'batSide' in ab_list['matchup'] else None)
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pitcher_id.append(ab_list['matchup']['pitcher']['id'] if 'pitcher' in ab_list['matchup'] else None)
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if 'pitcher' in ab_list['matchup']:
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pitcher_name.append(ab_list['matchup']['pitcher']['fullName'] if 'fullName' in ab_list['matchup']['pitcher'] else None)
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else:
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pitcher_name.append(None)
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pitcher_hand.append(ab_list['matchup']['pitchHand']['code'] if 'pitchHand' in ab_list['matchup'] else None)
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if ab_list['about']['isTopInning']:
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batter_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else None)
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batter_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else None)
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pitcher_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else None)
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pitcher_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else None)
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else:
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batter_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else None)
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batter_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else None)
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pitcher_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else None)
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pitcher_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else None)
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play_description.append(ab_list['playEvents'][n]['details']['description'] if 'description' in ab_list['playEvents'][n]['details'] else None)
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play_code.append(ab_list['playEvents'][n]['details']['code'] if 'code' in ab_list['playEvents'][n]['details'] else None)
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in_play.append(ab_list['playEvents'][n]['details']['isInPlay'] if 'isInPlay' in ab_list['playEvents'][n]['details'] else None)
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is_strike.append(ab_list['playEvents'][n]['details']['isStrike'] if 'isStrike' in ab_list['playEvents'][n]['details'] else None)
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if 'details' in ab_list['playEvents'][n]:
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is_swing.append(True if ab_list['playEvents'][n]['details']['code'] in swing_list else None)
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is_whiff.append(True if ab_list['playEvents'][n]['details']['code'] in whiff_list else None)
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else:
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is_swing.append(None)
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is_whiff.append(None)
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is_ball.append(ab_list['playEvents'][n]['details']['isOut'] if 'isOut' in ab_list['playEvents'][n]['details'] else None)
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is_review.append(ab_list['playEvents'][n]['details']['hasReview'] if 'hasReview' in ab_list['playEvents'][n]['details'] else None)
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pitch_type.append(ab_list['playEvents'][n]['details']['type']['code'] if 'type' in ab_list['playEvents'][n]['details'] else None)
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pitch_description.append(ab_list['playEvents'][n]['details']['type']['description'] if 'type' in ab_list['playEvents'][n]['details'] else None)
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if ab_list['playEvents'][n]['pitchNumber'] == 1:
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strikes.append(0)
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balls.append(0)
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strikes_after.append(ab_list['playEvents'][n]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n]['count'] else None)
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balls_after.append(ab_list['playEvents'][n]['count']['balls'] if 'balls' in ab_list['playEvents'][n]['count'] else None)
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outs.append(ab_list['playEvents'][n]['count']['outs'] if 'outs' in ab_list['playEvents'][n]['count'] else None)
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outs_after.append(ab_list['playEvents'][n]['count']['outs'] if 'outs' in ab_list['playEvents'][n]['count'] else None)
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else:
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strikes.append(ab_list['playEvents'][n-1]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n-1]['count'] else None)
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balls.append(ab_list['playEvents'][n-1]['count']['balls'] if 'balls' in ab_list['playEvents'][n-1]['count'] else None)
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outs.append(ab_list['playEvents'][n-1]['count']['outs'] if 'outs' in ab_list['playEvents'][n-1]['count'] else None)
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strikes_after.append(ab_list['playEvents'][n]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n]['count'] else None)
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balls_after.append(ab_list['playEvents'][n]['count']['balls'] if 'balls' in ab_list['playEvents'][n]['count'] else None)
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outs_after.append(ab_list['playEvents'][n]['count']['outs'] if 'outs' in ab_list['playEvents'][n]['count'] else None)
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if 'pitchData' in ab_list['playEvents'][n]:
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start_speed.append(ab_list['playEvents'][n]['pitchData']['startSpeed'] if 'startSpeed' in ab_list['playEvents'][n]['pitchData'] else None)
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end_speed.append(ab_list['playEvents'][n]['pitchData']['endSpeed'] if 'endSpeed' in ab_list['playEvents'][n]['pitchData'] else None)
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sz_top.append(ab_list['playEvents'][n]['pitchData']['strikeZoneTop'] if 'strikeZoneTop' in ab_list['playEvents'][n]['pitchData'] else None)
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sz_bot.append(ab_list['playEvents'][n]['pitchData']['strikeZoneBottom'] if 'strikeZoneBottom' in ab_list['playEvents'][n]['pitchData'] else None)
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347 |
-
x.append(ab_list['playEvents'][n]['pitchData']['coordinates']['x'] if 'x' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
348 |
-
y.append(ab_list['playEvents'][n]['pitchData']['coordinates']['y'] if 'y' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
349 |
-
|
350 |
-
ax.append(ab_list['playEvents'][n]['pitchData']['coordinates']['aX'] if 'aX' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
351 |
-
ay.append(ab_list['playEvents'][n]['pitchData']['coordinates']['aY'] if 'aY' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
352 |
-
az.append(ab_list['playEvents'][n]['pitchData']['coordinates']['aZ'] if 'aZ' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
353 |
-
pfxx.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pfxX'] if 'pfxX' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
354 |
-
pfxz.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pfxZ'] if 'pfxZ' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
355 |
-
px.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pX'] if 'pX' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
356 |
-
pz.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pZ'] if 'pZ' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
357 |
-
vx0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['vX0'] if 'vX0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
358 |
-
vy0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['vY0'] if 'vY0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
359 |
-
vz0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['vZ0'] if 'vZ0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
360 |
-
x0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['x0'] if 'x0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
361 |
-
y0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['y0'] if 'y0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
362 |
-
z0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['z0'] if 'z0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
|
363 |
-
|
364 |
-
zone.append(ab_list['playEvents'][n]['pitchData']['zone'] if 'zone' in ab_list['playEvents'][n]['pitchData'] else None)
|
365 |
-
type_confidence.append(ab_list['playEvents'][n]['pitchData']['typeConfidence'] if 'typeConfidence' in ab_list['playEvents'][n]['pitchData'] else None)
|
366 |
-
plate_time.append(ab_list['playEvents'][n]['pitchData']['plateTime'] if 'plateTime' in ab_list['playEvents'][n]['pitchData'] else None)
|
367 |
-
extension.append(ab_list['playEvents'][n]['pitchData']['extension'] if 'extension' in ab_list['playEvents'][n]['pitchData'] else None)
|
368 |
-
|
369 |
-
if 'breaks' in ab_list['playEvents'][n]['pitchData']:
|
370 |
-
spin_rate.append(ab_list['playEvents'][n]['pitchData']['breaks']['spinRate'] if 'spinRate' in ab_list['playEvents'][n]['pitchData']['breaks'] else None)
|
371 |
-
spin_direction.append(ab_list['playEvents'][n]['pitchData']['breaks']['spinDirection'] if 'spinDirection' in ab_list['playEvents'][n]['pitchData']['breaks'] else None)
|
372 |
-
vb.append(ab_list['playEvents'][n]['pitchData']['breaks']['breakVertical'] if 'breakVertical' in ab_list['playEvents'][n]['pitchData']['breaks'] else None)
|
373 |
-
ivb.append(ab_list['playEvents'][n]['pitchData']['breaks']['breakVerticalInduced'] if 'breakVerticalInduced' in ab_list['playEvents'][n]['pitchData']['breaks'] else None)
|
374 |
-
hb.append(ab_list['playEvents'][n]['pitchData']['breaks']['breakHorizontal'] if 'breakHorizontal' in ab_list['playEvents'][n]['pitchData']['breaks'] else None)
|
375 |
-
|
376 |
-
else:
|
377 |
-
start_speed.append(None)
|
378 |
-
end_speed.append(None)
|
379 |
-
|
380 |
-
sz_top.append(None)
|
381 |
-
sz_bot.append(None)
|
382 |
-
x.append(None)
|
383 |
-
y.append(None)
|
384 |
-
|
385 |
-
ax.append(None)
|
386 |
-
ay.append(None)
|
387 |
-
az.append(None)
|
388 |
-
pfxx.append(None)
|
389 |
-
pfxz.append(None)
|
390 |
-
px.append(None)
|
391 |
-
pz.append(None)
|
392 |
-
vx0.append(None)
|
393 |
-
vy0.append(None)
|
394 |
-
vz0.append(None)
|
395 |
-
x0.append(None)
|
396 |
-
y0.append(None)
|
397 |
-
z0.append(None)
|
398 |
-
|
399 |
-
zone.append(None)
|
400 |
-
type_confidence.append(None)
|
401 |
-
plate_time.append(None)
|
402 |
-
extension.append(None)
|
403 |
-
spin_rate.append(None)
|
404 |
-
spin_direction.append(None)
|
405 |
-
vb.append(None)
|
406 |
-
ivb.append(None)
|
407 |
-
hb.append(None)
|
408 |
-
|
409 |
-
if 'hitData' in ab_list['playEvents'][n]:
|
410 |
-
launch_speed.append(ab_list['playEvents'][n]['hitData']['launchSpeed'] if 'launchSpeed' in ab_list['playEvents'][n]['hitData'] else None)
|
411 |
-
launch_angle.append(ab_list['playEvents'][n]['hitData']['launchAngle'] if 'launchAngle' in ab_list['playEvents'][n]['hitData'] else None)
|
412 |
-
launch_distance.append(ab_list['playEvents'][n]['hitData']['totalDistance'] if 'totalDistance' in ab_list['playEvents'][n]['hitData'] else None)
|
413 |
-
launch_location.append(ab_list['playEvents'][n]['hitData']['location'] if 'location' in ab_list['playEvents'][n]['hitData'] else None)
|
414 |
-
|
415 |
-
trajectory.append(ab_list['playEvents'][n]['hitData']['trajectory'] if 'trajectory' in ab_list['playEvents'][n]['hitData'] else None)
|
416 |
-
hardness.append(ab_list['playEvents'][n]['hitData']['hardness'] if 'hardness' in ab_list['playEvents'][n]['hitData'] else None)
|
417 |
-
hit_x.append(ab_list['playEvents'][n]['hitData']['coordinates']['coordX'] if 'coordX' in ab_list['playEvents'][n]['hitData']['coordinates'] else None)
|
418 |
-
hit_y.append(ab_list['playEvents'][n]['hitData']['coordinates']['coordY'] if 'coordY' in ab_list['playEvents'][n]['hitData']['coordinates'] else None)
|
419 |
-
else:
|
420 |
-
launch_speed.append(None)
|
421 |
-
launch_angle.append(None)
|
422 |
-
launch_distance.append(None)
|
423 |
-
launch_location.append(None)
|
424 |
-
trajectory.append(None)
|
425 |
-
hardness.append(None)
|
426 |
-
hit_x.append(None)
|
427 |
-
hit_y.append(None)
|
428 |
-
|
429 |
-
index_play.append(ab_list['playEvents'][n]['index'] if 'index' in ab_list['playEvents'][n] else None)
|
430 |
-
play_id.append(ab_list['playEvents'][n]['playId'] if 'playId' in ab_list['playEvents'][n] else None)
|
431 |
-
start_time.append(ab_list['playEvents'][n]['startTime'] if 'startTime' in ab_list['playEvents'][n] else None)
|
432 |
-
end_time.append(ab_list['playEvents'][n]['endTime'] if 'endTime' in ab_list['playEvents'][n] else None)
|
433 |
-
is_pitch.append(ab_list['playEvents'][n]['isPitch'] if 'isPitch' in ab_list['playEvents'][n] else None)
|
434 |
-
type_type.append(ab_list['playEvents'][n]['type'] if 'type' in ab_list['playEvents'][n] else None)
|
435 |
-
|
436 |
-
|
437 |
-
|
438 |
-
if n == len(ab_list['playEvents']) - 1 :
|
439 |
-
|
440 |
-
type_ab.append(data['liveData']['plays']['allPlays'][ab_id]['result']['type'] if 'type' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
|
441 |
-
event.append(data['liveData']['plays']['allPlays'][ab_id]['result']['event'] if 'event' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
|
442 |
-
event_type.append(data['liveData']['plays']['allPlays'][ab_id]['result']['eventType'] if 'eventType' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
|
443 |
-
rbi.append(data['liveData']['plays']['allPlays'][ab_id]['result']['rbi'] if 'rbi' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
|
444 |
-
away_score.append(data['liveData']['plays']['allPlays'][ab_id]['result']['awayScore'] if 'awayScore' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
|
445 |
-
home_score.append(data['liveData']['plays']['allPlays'][ab_id]['result']['homeScore'] if 'homeScore' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
|
446 |
-
is_out.append(data['liveData']['plays']['allPlays'][ab_id]['result']['isOut'] if 'isOut' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
|
447 |
-
|
448 |
-
else:
|
449 |
-
|
450 |
-
type_ab.append(None)
|
451 |
-
event.append(None)
|
452 |
-
event_type.append(None)
|
453 |
-
rbi.append(None)
|
454 |
-
away_score.append(None)
|
455 |
-
home_score.append(None)
|
456 |
-
is_out.append(None)
|
457 |
-
|
458 |
-
elif ab_list['playEvents'][n]['count']['balls'] == 4:
|
459 |
-
|
460 |
-
event.append(data['liveData']['plays']['allPlays'][ab_id]['result']['event'])
|
461 |
-
event_type.append(data['liveData']['plays']['allPlays'][ab_id]['result']['eventType'])
|
462 |
-
|
463 |
-
|
464 |
-
game_id.append(data['gamePk'])
|
465 |
-
game_date.append(data['gameData']['datetime']['officialDate'])
|
466 |
-
batter_id.append(ab_list['matchup']['batter']['id'] if 'batter' in ab_list['matchup'] else None)
|
467 |
-
batter_name.append(ab_list['matchup']['batter']['fullName'] if 'batter' in ab_list['matchup'] else None)
|
468 |
-
batter_hand.append(ab_list['matchup']['batSide']['code'] if 'batSide' in ab_list['matchup'] else None)
|
469 |
-
pitcher_id.append(ab_list['matchup']['pitcher']['id'] if 'pitcher' in ab_list['matchup'] else None)
|
470 |
-
pitcher_name.append(ab_list['matchup']['pitcher']['fullName'] if 'pitcher' in ab_list['matchup'] else None)
|
471 |
-
pitcher_hand.append(ab_list['matchup']['pitchHand']['code'] if 'pitchHand' in ab_list['matchup'] else None)
|
472 |
-
if ab_list['about']['isTopInning']:
|
473 |
-
batter_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else None)
|
474 |
-
batter_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else None)
|
475 |
-
pitcher_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else None)
|
476 |
-
pitcher_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else None)
|
477 |
-
else:
|
478 |
-
batter_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else None)
|
479 |
-
batter_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else None)
|
480 |
-
pitcher_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else None)
|
481 |
-
pitcher_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else None)
|
482 |
-
|
483 |
-
play_description.append(None)
|
484 |
-
play_code.append(None)
|
485 |
-
in_play.append(None)
|
486 |
-
is_strike.append(None)
|
487 |
-
is_ball.append(None)
|
488 |
-
is_review.append(None)
|
489 |
-
pitch_type.append(None)
|
490 |
-
pitch_description.append(None)
|
491 |
-
strikes.append(ab_list['playEvents'][n]['count']['balls'] if 'balls' in ab_list['playEvents'][n]['count'] else None)
|
492 |
-
balls.append(ab_list['playEvents'][n]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n]['count'] else None)
|
493 |
-
outs.append(ab_list['playEvents'][n]['count']['outs'] if 'outs' in ab_list['playEvents'][n]['count'] else None)
|
494 |
-
strikes_after.append(ab_list['playEvents'][n]['count']['balls'] if 'balls' in ab_list['playEvents'][n]['count'] else None)
|
495 |
-
balls_after.append(ab_list['playEvents'][n]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n]['count'] else None)
|
496 |
-
outs_after.append(ab_list['playEvents'][n]['count']['outs'] if 'outs' in ab_list['playEvents'][n]['count'] else None)
|
497 |
-
index_play.append(ab_list['playEvents'][n]['index'] if 'index' in ab_list['playEvents'][n] else None)
|
498 |
-
play_id.append(ab_list['playEvents'][n]['playId'] if 'playId' in ab_list['playEvents'][n] else None)
|
499 |
-
start_time.append(ab_list['playEvents'][n]['startTime'] if 'startTime' in ab_list['playEvents'][n] else None)
|
500 |
-
end_time.append(ab_list['playEvents'][n]['endTime'] if 'endTime' in ab_list['playEvents'][n] else None)
|
501 |
-
is_pitch.append(ab_list['playEvents'][n]['isPitch'] if 'isPitch' in ab_list['playEvents'][n] else None)
|
502 |
-
type_type.append(ab_list['playEvents'][n]['type'] if 'type' in ab_list['playEvents'][n] else None)
|
503 |
-
|
504 |
-
|
505 |
-
|
506 |
-
is_swing.append(None)
|
507 |
-
is_whiff.append(None)
|
508 |
-
start_speed.append(None)
|
509 |
-
end_speed.append(None)
|
510 |
-
sz_top.append(None)
|
511 |
-
sz_bot.append(None)
|
512 |
-
x.append(None)
|
513 |
-
y.append(None)
|
514 |
-
ax.append(None)
|
515 |
-
ay.append(None)
|
516 |
-
az.append(None)
|
517 |
-
pfxx.append(None)
|
518 |
-
pfxz.append(None)
|
519 |
-
px.append(None)
|
520 |
-
pz.append(None)
|
521 |
-
vx0.append(None)
|
522 |
-
vy0.append(None)
|
523 |
-
vz0.append(None)
|
524 |
-
x0.append(None)
|
525 |
-
y0.append(None)
|
526 |
-
z0.append(None)
|
527 |
-
zone.append(None)
|
528 |
-
type_confidence.append(None)
|
529 |
-
plate_time.append(None)
|
530 |
-
extension.append(None)
|
531 |
-
spin_rate.append(None)
|
532 |
-
spin_direction.append(None)
|
533 |
-
vb.append(None)
|
534 |
-
ivb.append(None)
|
535 |
-
hb.append(None)
|
536 |
-
launch_speed.append(None)
|
537 |
-
launch_angle.append(None)
|
538 |
-
launch_distance.append(None)
|
539 |
-
launch_location.append(None)
|
540 |
-
trajectory.append(None)
|
541 |
-
hardness.append(None)
|
542 |
-
hit_x.append(None)
|
543 |
-
hit_y.append(None)
|
544 |
-
type_ab.append(None)
|
545 |
-
ab_number.append(None)
|
546 |
-
|
547 |
-
rbi.append(None)
|
548 |
-
away_score.append(None)
|
549 |
-
home_score.append(None)
|
550 |
-
is_out.append(None)
|
551 |
-
|
552 |
-
# print({
|
553 |
-
# 'game_id':len(game_id),
|
554 |
-
# 'game_date':len(game_date),
|
555 |
-
# 'batter_id':len(batter_id),
|
556 |
-
# 'batter_name':len(batter_name),
|
557 |
-
# 'batter_hand':len(batter_hand),
|
558 |
-
# 'batter_team':len(batter_team),
|
559 |
-
# 'batter_team_id':len(batter_team_id),
|
560 |
-
# 'pitcher_id':len(pitcher_id),
|
561 |
-
# 'pitcher_name':len(pitcher_name),
|
562 |
-
# 'pitcher_hand':len(pitcher_hand),
|
563 |
-
# 'pitcher_team':len(pitcher_team),
|
564 |
-
# 'pitcher_team_id':len(pitcher_team_id),
|
565 |
-
|
566 |
-
# 'play_description':len(play_description),
|
567 |
-
# 'play_code':len(play_code),
|
568 |
-
# 'in_play':len(in_play),
|
569 |
-
# 'is_strike':len(is_strike),
|
570 |
-
# 'is_swing':len(is_swing),
|
571 |
-
# 'is_whiff':len(is_whiff),
|
572 |
-
# 'is_out':len(is_out),
|
573 |
-
# 'is_ball':len(is_ball),
|
574 |
-
# 'is_review':len(is_review),
|
575 |
-
# 'pitch_type':len(pitch_type),
|
576 |
-
# 'pitch_description':len(pitch_description),
|
577 |
-
# 'strikes':len(strikes),
|
578 |
-
# 'balls':len(balls),
|
579 |
-
# 'outs':len(outs),
|
580 |
-
# 'strikes_after':len(strikes_after),
|
581 |
-
# 'balls_after':len(balls_after),
|
582 |
-
# 'outs_after':len(outs_after),
|
583 |
-
# 'start_speed':len(start_speed),
|
584 |
-
# 'end_speed':len(end_speed),
|
585 |
-
# 'sz_top':len(sz_top),
|
586 |
-
# 'sz_bot':len(sz_bot),
|
587 |
-
# 'x':len(x),
|
588 |
-
# 'y':len(y),
|
589 |
-
# 'ax':len(ax),
|
590 |
-
# 'ay':len(ay),
|
591 |
-
# 'az':len(az),
|
592 |
-
# 'pfxx':len(pfxx),
|
593 |
-
# 'pfxz':len(pfxz),
|
594 |
-
# 'px':len(px),
|
595 |
-
# 'pz':len(pz),
|
596 |
-
# 'vx0':len(vx0),
|
597 |
-
# 'vy0':len(vy0),
|
598 |
-
# 'vz0':len(vz0),
|
599 |
-
# 'x0':len(x0),
|
600 |
-
# 'y0':len(y0),
|
601 |
-
# 'z0':len(z0),
|
602 |
-
# 'zone':len(zone),
|
603 |
-
# 'type_confidence':len(type_confidence),
|
604 |
-
# 'plate_time':len(plate_time),
|
605 |
-
# 'extension':len(extension),
|
606 |
-
# 'spin_rate':len(spin_rate),
|
607 |
-
# 'spin_direction':len(spin_direction),
|
608 |
-
# 'vb':len(vb),
|
609 |
-
# 'ivb':len(ivb),
|
610 |
-
# 'hb':len(hb),
|
611 |
-
# 'launch_speed':len(launch_speed),
|
612 |
-
# 'launch_angle':len(launch_angle),
|
613 |
-
# 'launch_distance':len(launch_distance),
|
614 |
-
# 'launch_location':len(launch_location),
|
615 |
-
# 'trajectory':len(trajectory),
|
616 |
-
# 'hardness':len(hardness),
|
617 |
-
# 'hit_x':len(hit_x),
|
618 |
-
# 'hit_y':len(hit_y),
|
619 |
-
# 'index_play':len(index_play),
|
620 |
-
# 'play_id':len(play_id),
|
621 |
-
# 'start_time':len(start_time),
|
622 |
-
# 'end_time':len(end_time),
|
623 |
-
# 'is_pitch':len(is_pitch),
|
624 |
-
# 'type_type':len(type_type),
|
625 |
-
# 'type_ab':len(type_ab),
|
626 |
-
# 'event':len(event),
|
627 |
-
# 'event_type':len(event_type),
|
628 |
-
# 'rbi':len(rbi),
|
629 |
-
# 'away_score':len(away_score),
|
630 |
-
# 'home_score':len(home_score),
|
631 |
-
# }
|
632 |
-
|
633 |
-
|
634 |
-
# )
|
635 |
-
df = pl.DataFrame(data={
|
636 |
-
'game_id':game_id,
|
637 |
-
'game_date':game_date,
|
638 |
-
'batter_id':batter_id,
|
639 |
-
'batter_name':batter_name,
|
640 |
-
'batter_hand':batter_hand,
|
641 |
-
'batter_team':batter_team,
|
642 |
-
'batter_team_id':batter_team_id,
|
643 |
-
'pitcher_id':pitcher_id,
|
644 |
-
'pitcher_name':pitcher_name,
|
645 |
-
'pitcher_hand':pitcher_hand,
|
646 |
-
'pitcher_team':pitcher_team,
|
647 |
-
'pitcher_team_id':pitcher_team_id,
|
648 |
-
'ab_number':ab_number,
|
649 |
-
'play_description':play_description,
|
650 |
-
'play_code':play_code,
|
651 |
-
'in_play':in_play,
|
652 |
-
'is_strike':is_strike,
|
653 |
-
'is_swing':is_swing,
|
654 |
-
'is_whiff':is_whiff,
|
655 |
-
'is_out':is_out,
|
656 |
-
'is_ball':is_ball,
|
657 |
-
'is_review':is_review,
|
658 |
-
'pitch_type':pitch_type,
|
659 |
-
'pitch_description':pitch_description,
|
660 |
-
'strikes':strikes,
|
661 |
-
'balls':balls,
|
662 |
-
'outs':outs,
|
663 |
-
'strikes_after':strikes_after,
|
664 |
-
'balls_after':balls_after,
|
665 |
-
'outs_after':outs_after,
|
666 |
-
'start_speed':start_speed,
|
667 |
-
'end_speed':end_speed,
|
668 |
-
'sz_top':sz_top,
|
669 |
-
'sz_bot':sz_bot,
|
670 |
-
'x':x,
|
671 |
-
'y':y,
|
672 |
-
'ax':ax,
|
673 |
-
'ay':ay,
|
674 |
-
'az':az,
|
675 |
-
'pfxx':pfxx,
|
676 |
-
'pfxz':pfxz,
|
677 |
-
'px':px,
|
678 |
-
'pz':pz,
|
679 |
-
'vx0':vx0,
|
680 |
-
'vy0':vy0,
|
681 |
-
'vz0':vz0,
|
682 |
-
'x0':x0,
|
683 |
-
'y0':y0,
|
684 |
-
'z0':z0,
|
685 |
-
'zone':zone,
|
686 |
-
'type_confidence':type_confidence,
|
687 |
-
'plate_time':plate_time,
|
688 |
-
'extension':extension,
|
689 |
-
'spin_rate':spin_rate,
|
690 |
-
'spin_direction':spin_direction,
|
691 |
-
'vb':vb,
|
692 |
-
'ivb':ivb,
|
693 |
-
'hb':hb,
|
694 |
-
'launch_speed':launch_speed,
|
695 |
-
'launch_angle':launch_angle,
|
696 |
-
'launch_distance':launch_distance,
|
697 |
-
'launch_location':launch_location,
|
698 |
-
'trajectory':trajectory,
|
699 |
-
'hardness':hardness,
|
700 |
-
'hit_x':hit_x,
|
701 |
-
'hit_y':hit_y,
|
702 |
-
'index_play':index_play,
|
703 |
-
'play_id':play_id,
|
704 |
-
'start_time':start_time,
|
705 |
-
'end_time':end_time,
|
706 |
-
'is_pitch':is_pitch,
|
707 |
-
'type_type':type_type,
|
708 |
-
'type_ab':type_ab,
|
709 |
-
'event':event,
|
710 |
-
'event_type':event_type,
|
711 |
-
'rbi':rbi,
|
712 |
-
'away_score':away_score,
|
713 |
-
'home_score':home_score,
|
714 |
-
|
715 |
-
},strict=False
|
716 |
-
)
|
717 |
-
|
718 |
-
return df
|
719 |
-
|
720 |
-
# def get_players(self,sport_id:int):
|
721 |
-
# player_data = requests.get(url=f'https://statsapi.mlb.com/api/v1/sports/{sport_id}/players').json()
|
722 |
-
|
723 |
-
# #Select relevant data that will help distinguish players from one another
|
724 |
-
# fullName_list = [x['fullName'] for x in player_data['people']]
|
725 |
-
# id_list = [x['id'] for x in player_data['people']]
|
726 |
-
# position_list = [x['primaryPosition']['abbreviation'] for x in player_data['people']]
|
727 |
-
# team_list = [x['currentTeam']['id']for x in player_data['people']]
|
728 |
-
# age_list = [x['currentAge']for x in player_data['people']]
|
729 |
-
|
730 |
-
# player_df = pl.DataFrame(data={'player_id':id_list,
|
731 |
-
# 'name':fullName_list,
|
732 |
-
# 'position':position_list,
|
733 |
-
# 'team':team_list,
|
734 |
-
# 'age':age_list})
|
735 |
-
# return player_df
|
736 |
-
|
737 |
-
def get_teams(self):
|
738 |
-
"""
|
739 |
-
Retrieves information about MLB teams from the MLB API and processes it into a Polars DataFrame.
|
740 |
-
|
741 |
-
Returns:
|
742 |
-
- mlb_teams_df (pl.DataFrame): A DataFrame containing team information, including team ID, city, name, franchise, abbreviation, parent organization ID, parent organization name, league ID, and league name.
|
743 |
-
"""
|
744 |
-
# Make API call to retrieve team information
|
745 |
-
teams = requests.get(url='https://statsapi.mlb.com/api/v1/teams/').json()
|
746 |
-
|
747 |
-
# Extract relevant data from the API response
|
748 |
-
mlb_teams_city = [x['franchiseName'] if 'franchiseName' in x else None for x in teams['teams']]
|
749 |
-
mlb_teams_name = [x['teamName'] if 'franchiseName' in x else None for x in teams['teams']]
|
750 |
-
mlb_teams_franchise = [x['name'] if 'franchiseName' in x else None for x in teams['teams']]
|
751 |
-
mlb_teams_id = [x['id'] if 'franchiseName' in x else None for x in teams['teams']]
|
752 |
-
mlb_teams_abb = [x['abbreviation'] if 'franchiseName' in x else None for x in teams['teams']]
|
753 |
-
mlb_teams_parent_id = [x['parentOrgId'] if 'parentOrgId' in x else None for x in teams['teams']]
|
754 |
-
mlb_teams_parent = [x['parentOrgName'] if 'parentOrgName' in x else None for x in teams['teams']]
|
755 |
-
mlb_teams_league_id = [x['league']['id'] if 'id' in x['league'] else None for x in teams['teams']]
|
756 |
-
mlb_teams_league_name = [x['league']['name'] if 'name' in x['league'] else None for x in teams['teams']]
|
757 |
-
|
758 |
-
# Create a Polars DataFrame with the extracted data
|
759 |
-
mlb_teams_df = pl.DataFrame(data={'team_id': mlb_teams_id,
|
760 |
-
'city': mlb_teams_franchise,
|
761 |
-
'name': mlb_teams_name,
|
762 |
-
'franchise': mlb_teams_franchise,
|
763 |
-
'abbreviation': mlb_teams_abb,
|
764 |
-
'parent_org_id': mlb_teams_parent_id,
|
765 |
-
'parent_org': mlb_teams_parent,
|
766 |
-
'league_id': mlb_teams_league_id,
|
767 |
-
'league_name': mlb_teams_league_name
|
768 |
-
}).unique().drop_nulls(subset=['team_id']).sort('team_id')
|
769 |
-
|
770 |
-
# Fill missing parent organization IDs with team IDs
|
771 |
-
mlb_teams_df = mlb_teams_df.with_columns(
|
772 |
-
pl.when(pl.col('parent_org_id').is_null())
|
773 |
-
.then(pl.col('team_id'))
|
774 |
-
.otherwise(pl.col('parent_org_id'))
|
775 |
-
.alias('parent_org_id')
|
776 |
-
)
|
777 |
-
|
778 |
-
# Fill missing parent organization names with franchise names
|
779 |
-
mlb_teams_df = mlb_teams_df.with_columns(
|
780 |
-
pl.when(pl.col('parent_org').is_null())
|
781 |
-
.then(pl.col('franchise'))
|
782 |
-
.otherwise(pl.col('parent_org'))
|
783 |
-
.alias('parent_org')
|
784 |
-
)
|
785 |
-
|
786 |
-
# Create a dictionary for mapping team IDs to abbreviations
|
787 |
-
abbreviation_dict = mlb_teams_df.select(['team_id', 'abbreviation']).to_dict(as_series=False)
|
788 |
-
abbreviation_map = {k: v for k, v in zip(abbreviation_dict['team_id'], abbreviation_dict['abbreviation'])}
|
789 |
-
|
790 |
-
# Create a DataFrame for parent organization abbreviations
|
791 |
-
abbreviation_df = mlb_teams_df.select(['team_id', 'abbreviation']).rename({'team_id': 'parent_org_id', 'abbreviation': 'parent_org_abbreviation'})
|
792 |
-
|
793 |
-
# Join the parent organization abbreviations with the main DataFrame
|
794 |
-
mlb_teams_df = mlb_teams_df.join(abbreviation_df, on='parent_org_id', how='left')
|
795 |
-
|
796 |
-
return mlb_teams_df
|
797 |
-
|
798 |
-
def get_leagues(self):
|
799 |
-
"""
|
800 |
-
Retrieves information about MLB leagues from the MLB API and processes it into a Polars DataFrame.
|
801 |
-
|
802 |
-
Returns:
|
803 |
-
- leagues_df (pl.DataFrame): A DataFrame containing league information, including league ID, league name, league abbreviation, and sport ID.
|
804 |
-
"""
|
805 |
-
# Make API call to retrieve league information
|
806 |
-
leagues = requests.get(url='https://statsapi.mlb.com/api/v1/leagues/').json()
|
807 |
-
|
808 |
-
# Extract relevant data from the API response
|
809 |
-
sport_id = [x['sport']['id'] if 'sport' in x else None for x in leagues['leagues']]
|
810 |
-
league_id = [x['id'] if 'id' in x else None for x in leagues['leagues']]
|
811 |
-
league_name = [x['name'] if 'name' in x else None for x in leagues['leagues']]
|
812 |
-
league_abbreviation = [x['abbreviation'] if 'abbreviation' in x else None for x in leagues['leagues']]
|
813 |
-
|
814 |
-
# Create a Polars DataFrame with the extracted data
|
815 |
-
leagues_df = pl.DataFrame(data={
|
816 |
-
'league_id': league_id,
|
817 |
-
'league_name': league_name,
|
818 |
-
'league_abbreviation': league_abbreviation,
|
819 |
-
'sport_id': sport_id,
|
820 |
-
})
|
821 |
-
|
822 |
-
return leagues_df
|
823 |
-
|
824 |
-
def get_player_games_list(self, player_id: int, season: int, start_date: str = None, end_date: str = None, sport_id: int = 1, game_type: list = ['R']):
|
825 |
-
"""
|
826 |
-
Retrieves a list of game IDs for a specific player in a given season.
|
827 |
-
|
828 |
-
Parameters:
|
829 |
-
- player_id (int): The ID of the player.
|
830 |
-
- season (int): The season year for which to retrieve the game list.
|
831 |
-
- start_date (str): The start date (YYYY-MM-DD) of the range (default is January 1st of the specified season).
|
832 |
-
- end_date (str): The end date (YYYY-MM-DD) of the range (default is December 31st of the specified season).
|
833 |
-
- sport_id (int): The ID of the sport for which to retrieve player data.
|
834 |
-
- game_type (list): A list of game types to filter the schedule. Default is ['R'].
|
835 |
-
|
836 |
-
Returns:
|
837 |
-
- player_game_list (list): A list of game IDs in which the player participated during the specified season.
|
838 |
-
"""
|
839 |
-
# Set default start and end dates if not provided
|
840 |
-
|
841 |
-
if not start_date:
|
842 |
-
start_date = f'{season}-01-01'
|
843 |
-
if not end_date:
|
844 |
-
end_date = f'{season}-12-31'
|
845 |
-
|
846 |
-
|
847 |
-
|
848 |
-
# Validate date format
|
849 |
-
date_pattern = re.compile(r'^\d{4}-\d{2}-\d{2}$')
|
850 |
-
if not date_pattern.match(start_date):
|
851 |
-
raise ValueError(f"start_date {start_date} is not in YYYY-MM-DD format")
|
852 |
-
if not date_pattern.match(end_date):
|
853 |
-
raise ValueError(f"end_date {end_date} is not in YYYY-MM-DD format")
|
854 |
-
|
855 |
-
game_type_str = ','.join([str(x) for x in game_type])
|
856 |
-
|
857 |
-
# Make API call to retrieve player game logs
|
858 |
-
response = requests.get(url=f'http://statsapi.mlb.com/api/v1/people/{player_id}?hydrate=stats(type=gameLog,season={season},startDate={start_date},endDate={end_date},sportId={sport_id},gameType=[{game_type_str}]),hydrations').json()
|
859 |
-
print(f'http://statsapi.mlb.com/api/v1/people/{player_id}?hydrate=stats(type=gameLog,season={season},startDate={start_date},endDate={end_date},sportId={sport_id},gameType=[{game_type_str}]),hydrations')
|
860 |
-
# Extract game IDs from the API response
|
861 |
-
player_game_list = [x['game']['gamePk'] for x in response['people'][0]['stats'][0]['splits']]
|
862 |
-
|
863 |
-
return player_game_list
|
864 |
-
|
865 |
-
|
866 |
-
def get_players(self, sport_id: int, season: int, game_type: list = ['R']):
|
867 |
-
"""
|
868 |
-
Retrieves data frame of players in a given league
|
869 |
-
|
870 |
-
Parameters:
|
871 |
-
- sport_id (int): The ID of the sport for which to retrieve player data.
|
872 |
-
- season (int): The season year for which to retrieve player data.
|
873 |
-
|
874 |
-
Returns:
|
875 |
-
- player_df (pl.DataFrame): A DataFrame containing player information, including player ID, name, position, team, and age.
|
876 |
-
"""
|
877 |
-
|
878 |
-
game_type_str = ','.join([str(x) for x in game_type])
|
879 |
-
|
880 |
-
if game_type_str == 'S':
|
881 |
-
player_data = requests.get(f'https://bdfed.stitch.mlbinfra.com/bdfed/stats/player?&env=prod&season={season}&sportId=1&stats=season&group=pitching&gameType=S&limit=1000000&offset=0&sortStat=inningsPitched&order=asc').json()
|
882 |
-
fullName_list = [x['playerFullName'] if 'playerFullName' in x else None for x in player_data['stats']]
|
883 |
-
firstName_list = [x['playerFirstName'] if 'playerFirstName' in x else None for x in player_data['stats']]
|
884 |
-
lastName_list = [x['playerLastName'] if 'playerLastName' in x else None for x in player_data['stats']]
|
885 |
-
id_list = [x['playerId'] if 'playerId' in x else None for x in player_data['stats']]
|
886 |
-
position_list = [x['primaryPositionAbbrev'] if 'primaryPositionAbbrev' in x else None for x in player_data['stats']]
|
887 |
-
team_list = [x['teamId'] if 'teamId' in x else None for x in player_data['stats']]
|
888 |
-
|
889 |
-
df = pl.DataFrame(data={'player_id':id_list,
|
890 |
-
'first_name':firstName_list,
|
891 |
-
'last_name':lastName_list,
|
892 |
-
'name':fullName_list,
|
893 |
-
'position':position_list,
|
894 |
-
'team':team_list})
|
895 |
-
|
896 |
-
else:
|
897 |
-
player_data = requests.get(url=f'https://statsapi.mlb.com/api/v1/sports/{sport_id}/players?season={season}&gameType=[{game_type_str}]').json()['people']
|
898 |
-
|
899 |
-
#Select relevant data that will help distinguish players from one another
|
900 |
-
|
901 |
-
fullName_list = [x['fullName'] if 'fullName' in x else None for x in player_data]
|
902 |
-
firstName_list = [x['firstName'] if 'firstName' in x else None for x in player_data]
|
903 |
-
lastName_list = [x['lastName'] if 'lastName' in x else None for x in player_data]
|
904 |
-
id_list = [x['id'] if 'id' in x else None for x in player_data]
|
905 |
-
position_list = [x['primaryPosition']['abbreviation'] if 'primaryPosition' in x and 'abbreviation' in x['primaryPosition'] else None for x in player_data]
|
906 |
-
team_list = [x['currentTeam']['id'] if 'currentTeam' in x and 'id' in x['currentTeam'] else None for x in player_data]
|
907 |
-
weight_list = [x['weight'] if 'weight' in x else None for x in player_data]
|
908 |
-
height_list = [x['height'] if 'height' in x else None for x in player_data]
|
909 |
-
age_list = [x['currentAge'] if 'currentAge' in x else None for x in player_data]
|
910 |
-
birthDate_list = [x['birthDate'] if 'birthDate' in x else None for x in player_data]
|
911 |
-
|
912 |
-
|
913 |
-
|
914 |
-
df = pl.DataFrame(data={'player_id':id_list,
|
915 |
-
'first_name':firstName_list,
|
916 |
-
'last_name':lastName_list,
|
917 |
-
'name':fullName_list,
|
918 |
-
'position':position_list,
|
919 |
-
'team':team_list,
|
920 |
-
'weight':weight_list,
|
921 |
-
'height':height_list,
|
922 |
-
'age':age_list,
|
923 |
-
'birthDate':birthDate_list})
|
924 |
-
|
925 |
-
return df
|
926 |
-
|
927 |
-
|
|
|
|
|
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