Jesse Moore jes-moore
jes-moore
/ convert_to_hdfs.sh
Created
January 9, 2019 18:59
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| #!/bin/bash | |
| #Variables | |
| csv_files='ls /path/to/csv/files/*.csv' | |
| out_file='/path/to/output/folder' | |
| file_locs=$out_file/files.txt | |
| fits_out=$out_file/merged.fits | |
| hdf5_out=$out_file/merged.hdf5 | |
| # Create Txt File of Locations |
jes-moore
/ compare_wins_shots.py
Created
December 22, 2018 19:30
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| # Generate linear fit and chart 1 | |
| slope, intercept, r_value, p_value, std_err = stats.linregress( | |
| seasonal_df['rebound_ratio'], seasonal_df['win']) | |
| line = slope * seasonal_df['rebound_ratio'].values + intercept | |
| ch1_data = go.Scatter( | |
| x=seasonal_df['rebound_ratio'].values, | |
| y=seasonal_df['win'].values, | |
| mode='markers', | |
| marker=go.Marker(color='rgb(255, 127, 14)'), |
jes-moore
/ seasonal_df.py
Created
December 22, 2018 19:29
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| def get_seasonal_reb_df(): | |
| shot_to_reb = load_rebounds_df() | |
| ## Use only regular season | |
| shot_to_reb = shot_to_reb[shot_to_reb.type == 'R'] | |
| rebound_df = shot_to_reb.groupby(['for_name', 'season', 'lead_to_reb']).agg({ | |
| 'counter': | |
| 'count' | |
| }).reset_index() |
jes-moore
/ prop_goals_shots.py
Created
December 22, 2018 19:28
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| reb_goals = shot_df_agg2.loc[shot_df_agg2.shotTimeDiff <= 3, 'numGoals'].sum() | |
| reb_shots = shot_df_agg2.loc[shot_df_agg2.shotTimeDiff <= 3, 'numShots'].sum() | |
| norm_goals = shot_df_agg2.loc[shot_df_agg2.shotTimeDiff > 3, 'numGoals'].sum() | |
| norm_shots = shot_df_agg2.loc[shot_df_agg2.shotTimeDiff > 3, 'numShots'].sum() | |
| ## Data | |
| data = go.Bar( | |
| x=['Shots', 'Goals'], | |
| y=[reb_shots / norm_shots, reb_goals / norm_goals], |
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| def agg_rebounds_df2(): | |
| ## Aggregate shots and goals | |
| shot_df = load_rebounds_df() | |
| shot_df_agg2 = shot_df.groupby(['shotTimeDiff', 'nextShotResult']).agg({ | |
| 'counter': | |
| 'sum' | |
| }).reset_index() | |
| ## Create pivot table | |
| shot_df_agg2 = shot_df_agg2.pivot_table( |
jes-moore
/ num_shots_goals.py
Created
December 22, 2018 19:27
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| ## Scoring Ratio Chart | |
| shotTimeData = go.Scatter( | |
| x=shot_df_agg.loc[0:20, 'shotTimeDiff'], | |
| y=shot_df_agg.loc[0:20, 'goalRatio'], | |
| mode='markers+lines', | |
| text=shot_df_agg.loc[0:20, 'goalRatioText'], | |
| hoverinfo='text') | |
| data = [shotTimeData] | |
| ## Layout |
jes-moore
/ agg_rebounds_df.py
Last active
December 22, 2018 19:23
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| def agg_rebounds_df(): | |
| shot_df = load_rebounds_df() | |
| # Aggregate by Time Differential | |
| shot_df = shot_df[shot_df.shotTimeDiff > 0] | |
| shot_df_agg = shot_df.groupby('shotTimeDiff').agg({'counter':'sum'}) | |
| # Aggregate shots and goals | |
| shot_df_agg = shot_df.groupby(['shotTimeDiff','nextShotResult'])\ | |
| .agg({'counter':'sum'}).reset_index() |
jes-moore
/ rebounds_df.py
Created
December 22, 2018 19:22
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| def load_rebounds_df(): | |
| shot_df, unique_games = load_expanded_shooting_df() | |
| shot_df['shotTimeDiff'] = 0 | |
| shot_df['nextShotResult'] = 'None' | |
| shot_df['nextShotX'] = 0 | |
| shot_df['nextShotY'] = 0 | |
| for gameid in tqdm(unique_games): | |
| game_shot_df =\ | |
| shot_df.loc[shot_df.game_id == gameid, :].sort_values('play_num') |
jes-moore
/ load_expanded_shooting_df.py
Created
December 22, 2018 19:22
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| def load_expanded_shooting_df(): | |
| shot_df = load_shooting_df() | |
| # Load Team Info | |
| team_info = pd.read_csv('data/team_info.csv') | |
| team_info['combined_name'] = team_info.shortName + ' ' + team_info.teamName | |
| team_info.drop( | |
| ['franchiseId', 'shortName', 'teamName', 'abbreviation', 'link'], | |
| axis=1, | |
| inplace=True) |
jes-moore
/ shooting_df.py
Created
December 22, 2018 19:20
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| import pandas as pd | |
| from tqdm import tqdm | |
| import time | |
| def load_shooting_df(): | |
| # Get Shot on and Against | |
| plays_df = pd.read_csv('data/game_plays.csv') | |
| shooting_df = plays_df.loc[plays_df.event.isin(['Goal', 'Shot']), :] | |
| # Format Shot by and Goalie |
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