agg_rebounds_df.py

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()

    # Create pivot table
    shot_df_agg = shot_df_agg.pivot_table(aggfunc='sum',
                                          columns=['nextShotResult'],
                                          fill_value=0,
                                          index=['shotTimeDiff']).reset_index()

    # Drop multilevel and add ratio
    shot_df_agg.columns = shot_df_agg.columns.droplevel()
    shot_df_agg.columns = ['shotTimeDiff','numGoals','numShots']
    shot_df_agg['goalRatio'] = shot_df_agg['numGoals'] /\
    (shot_df_agg['numGoals'] + shot_df_agg['numShots'])

    #Set Minimum Shots for Differential
    shot_df_agg = shot_df_agg[shot_df_agg.numShots > 1500]
    shot_df_agg['goalRatioText'] ='Time b/w Rebound = ' \
        + shot_df_agg['shotTimeDiff'].apply(lambda x: str(x))\
        + ' <br>Scoring Ratio = ' + shot_df_agg['goalRatio'].apply(lambda x:"{0:.2f}%".format(x * 100))\
        + ' <br>Number of Shots = ' + shot_df_agg['numShots'].apply(lambda x: str(x))\
        + ' <br>Number of Goals = ' + shot_df_agg['numGoals'].apply(lambda x: str(x))
    return shot_df_agg