Problem With Friends Of Tracking Code Noob [python]

I am learning with python code and I have some issues: https://github.com/Slothfulwave612/Football-Analytics-Using-Python/blob/master/03.%20Analyzing%20Event%20Data/pass_map.py My

Solution 1:

So it's combining all the matches onto 1 because the figure is "drawing" on top of the previous one. There's a few other things you need to change too.

1. The away team will not always be Real Madrid, so make that dynamic
2. Adjust that in the figure text text so it's not always "vs. Real Madrid"
3. Save the file as something dynamic so they don't overwrite
4. Instead of doing plt.text to put in the titles (which is fine if you want to annotate at a specific x,y coordinates), use plt.title() and plt.suptitle(). It'll center and just make it a nicer layout of the text
5. You us i for you match id variable when iterating, but then you don't change/include that in the loop
6. This is the main issue: (fig,ax) = createPitch(pitch_length_X, pitch_width_Y,'yards','gray') is what is creating your "blank canvas" to plot on. So this needs to be called before each plot. It's like grabbing a new blank sheet of paper to draw on. If you just use the first initial sheet, then everything will go on that 1 sheet. So move that into your for loop

Code

import matplotlib.pyplot as plt
import json
from pandas.io.json import json_normalize
from FCPython import createPitch

## Note Statsbomb data uses yards for their pitch dimensions
pitch_length_X = 120
pitch_width_Y = 80## match id for our El Clasico
match_list = [16205, 16131, 16265]
teamA = 'Barcelona'#<--- adjusted herefor match_id in match_list:
    ## calling the function to create a pitch map## yards is the unit for measurement and## gray will be the line color of the pitch map
    (fig,ax) = createPitch(pitch_length_X, pitch_width_Y,'yards','gray') #< moved into for loop

    player_name = 'Lionel Andrés Messi Cuccittini'## this is the name of our event data file for## our required El Clasico
    file_name = str(match_id) + '.json'## loading the required event data file
    my_data = json.load(open('Statsbomb/data/events/' + file_name, 'r', encoding='utf-8'))


    ## get the nested structure into a dataframe ## store the dataframe in a dictionary with the match id as key
    df = json_normalize(my_data, sep='_').assign(match_id = file_name[:-5])
    teamB = [x for x inlist(df['team_name'].unique()) if x != teamA ][0] #<--- get other team name## making the list of all column names
    column = list(df.columns)

    ## all the type names we have in our dataframe
    all_type_name = list(df['type_name'].unique())

    ## creating a data frame for pass## and then removing the null values## only listing the player_name in the dataframe
    pass_df = df.loc[df['type_name'] == 'Pass', :].copy()
    pass_df.dropna(inplace=True, axis=1)
    pass_df = pass_df.loc[pass_df['player_name'] == player_name, :]

    ## creating a data frame for ball receipt## removing all the null values## and only listing Barcelona players in the dataframe
    breceipt_df = df.loc[df['type_name'] == 'Ball Receipt*', :].copy()
    breceipt_df.dropna(inplace=True, axis=1)
    breceipt_df = breceipt_df.loc[breceipt_df['team_name'] == 'Barcelona', :]

    pass_comp, pass_no = 0, 0## pass_comp: completed pass## pass_no: unsuccessful pass## iterating through the pass dataframefor row_num, passed in pass_df.iterrows():   

        if passed['player_name'] == player_name:
            ## for away side
            x_loc = passed['location'][0]
            y_loc = passed['location'][1]

            pass_id = passed['id']
            summed_result = sum(breceipt_df.iloc[:, 14].apply(lambda x: pass_id in x))

            if summed_result > 0:
                ## if pass made was successful
                color = 'blue'
                label = 'Successful'
                pass_comp += 1else:
                ## if pass made was unsuccessful
                color = 'red'
                label = 'Unsuccessful'
                pass_no += 1## plotting circle at the player's position
            shot_circle = plt.Circle((pitch_length_X - x_loc, y_loc), radius=2, color=color, label=label)
            shot_circle.set_alpha(alpha=0.2)
            ax.add_patch(shot_circle)

            ## parameters for making the arrow
            pass_x = 120 - passed['pass_end_location'][0]
            pass_y = passed['pass_end_location'][1] 
            dx = ((pitch_length_X - x_loc) - pass_x)
            dy = y_loc - pass_y

            ## making an arrow to display the pass
            pass_arrow = plt.Arrow(pitch_length_X - x_loc, y_loc, -dx, -dy, width=1, color=color)

            ## adding arrow to the plot
            ax.add_patch(pass_arrow)

    ## computing pass accuracy
    pass_acc = (pass_comp / (pass_comp + pass_no)) * 100
    pass_acc = str(round(pass_acc, 2))

    ## adding text to the plot
    plt.suptitle('{} pass map vs {}'.format(player_name, teamB), fontsize=15) #<-- make dynamic and change to suptitle
    plt.title('Pass Accuracy: {}'.format(pass_acc), fontsize=15) #<-- change to title## handling labels
    handles, labels = plt.gca().get_legend_handles_labels()
    by_label = dict(zip(labels, handles))
    plt.legend(by_label.values(), by_label.keys(), loc='best', bbox_to_anchor=(0.9, 1, 0, 0), fontsize=12)

    ## editing the figure size and saving it
    fig.set_size_inches(12, 8)
    fig.savefig('{} passmap.png'.format(match_id), dpi=200)  #<-- dynamic file name## showing the plot
    plt.show()