bar_interact

def barit(week, measure):
    """
    Filters and plot the dataframe as a bar plot of teams' defence performance
    Args:
    -----
        * week (str): the period to filter on, or "Overall" to display the entire season
        * measure (str): the option of measurement
    Returns:
    --------
        A matplotlib bar plot
    """
    plot = df.copy()
    if week != 'Overall':
        week_num = int(week.split(' ')[1])
        plot = plot[plot.week == week_num]
        
    if measure == 'playResult':
        defence = plot.groupby('defensiveTeam').agg({'playResult': 'mean'})
        defence.rename(columns = {'playResult': 'mean'}, inplace=True)
    elif measure == 'offensePlayResult':
        defence = plot.groupby('defensiveTeam').agg({'offensePlayResult': 'mean'})
        defence.rename(columns = {'offensePlayResult': 'mean'}, inplace=True)
    elif measure == 'epa':
        defence = plot.groupby('defensiveTeam').agg({'epa': 'mean'})
        defence.rename(columns = {'epa': 'mean'}, inplace=True)
        
    # Plot it (only if there's data to plot)
    if len(plot) > 0:
        fig, ax = plt.subplots(figsize=(15, 15))
        ax.barh([i+1 for i in range(defence.shape[0])], defence['mean'].tolist())
        ax.set_xlabel('Opponent\'s Average Gain', size=15)
        ax.set_yticklabels([])
        ax.set_title('Team Defence Performance', size=15)
        for x0, y0, path in zip([i+1 for i in range(defence.shape[0])], defence['mean'].tolist(), 
                               ['../input/nfl-team-logos/' + file for file in sorted(os.listdir('../input/nfl-team-logos'))]):
            ab = AnnotationBbox(getImage(path), (y0, x0), xybox=(-25, 0), frameon=False, 
                                xycoords='data', boxcoords="offset points", pad=0)
            ax.add_artist(ab)
    else:
        print("No data to show for current selection")