Chess Performance

ChessPerf.py

import requests
import pandas as pd
from tabulate import tabulate
import sys

pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
pd.set_option('display.width', 600)

playerurl = "https://www.ecfrating.org.uk/v2/new/api.php?v2/players/name/"

playerfname = input("Enter Player's (approx.) First Name (e.g Joh for John): ")
playerlname = input("Enter Player's (approx.) Last Name (e.g Smi for Smith): ")

URL2 = playerurl+playerfname+"%20"+playerlname

response2 = requests.get(URL2)
data2 = response2.json()
try:
    mydata2 = pd.DataFrame.from_dict(data2['players'])
    mydata2.index += 1
    mydata2 = mydata2.drop(['member_no', 'gender', 'FIDE_no', 'due_date','club_code','nation','nation2','flag','category'], axis=1)
    mydata2.rename(columns = {'full_name':'Full_Name', 'club_name':'Club','gender':'Gender','date_last_game':'LastGame'}, inplace = True)
    mydata2.index.name = "Row"
    print(tabulate(mydata2, headers='keys', tablefmt='psql'))
except:
    print("Player not found!")
    sys.exit(1)

try:
    chooseplayer = input("Choose Row Number: ")
    playerID = mydata2.at[int(chooseplayer),'ECF_code']
    baseurl = "https://www.ecfrating.org.uk/v2/new/api.php?v2/games/Standard"
    howmanygames = input("Enter how many past games you want to see: ")
    URL = baseurl+"/player/"+playerID+"/limit/"+howmanygames
    response = requests.get(URL)
    data = response.json()

    mydata = pd.DataFrame.from_dict(data['games'])
    mydata.loc[mydata.score==5,'score']='0.5'
    mydata.loc[mydata.colour=="w",'colour']='White'
    mydata.loc[mydata.colour=="b",'colour']='Black'
    mydata.loc[mydata.colour=="W",'colour']='White'
    mydata.loc[mydata.colour=="B",'colour']='Black'
    mydata = mydata[mydata.opponent_no != 0]
    mydata['score'] = pd.to_numeric(mydata['score'],errors='coerce')
    mydata['increment'] = pd.to_numeric(mydata['increment'],errors='coerce')
    mydata['opponent_rating'] = pd.to_numeric(mydata['opponent_rating'], errors='ignore')
    mydata['player_rating'] = pd.to_numeric(mydata['player_rating'], errors='ignore')
    mydata['diff_rating'] = mydata['opponent_rating']-mydata['player_rating']
    mydata = mydata[mydata.score >= 0]

    avgopprating = mydata['opponent_rating'].mean()
    totalpercent = mydata['score'].sum()
    averageopponent = mydata['diff_rating'].mean()
    myrating = mydata['player_rating'].iloc[0]
    player_rating_list = mydata['player_rating'].tolist()
    player_rating_filter = [value for value in player_rating_list if value > 0]
    ratingdiff = myrating - player_rating_filter[-1]

    mydata.rename(columns = {'player_rating':'NewRating', 'game_date':'Date','colour':'Colour','score':'Score'}, inplace = True)
    mydata.round(0)
    mydata.index.name = "Row"
    mydata['Versus'] = mydata['opponent_name'].map(str) + ' (' + mydata['opponent_rating'].map(str) + ')'
    mydata.reset_index()
    mydata.index += 1

    wins = mydata.loc[mydata['Score'] == 1, 'Score'].count()
    draws = mydata.loc[mydata['Score'] == 0.5, 'Score'].count()
    losses = mydata.loc[mydata['Score'] == 0, 'Score'].count()
    winswithW = mydata.loc[(mydata['Score']==1) & (mydata['Colour'] == 'White'), 'Score'].count()
    winswithB = mydata.loc[(mydata['Score']==1) & (mydata['Colour'] == 'Black'), 'Score'].count()

    print(f"Statistics:")
    print(f"WDL: {wins} Wins, {draws} Draws and {losses} Losses")
    print(f"Wins with White: {winswithW}")
    print(f"Wins with Black: {winswithB}")
    print(f"Percentage Score: {(100*int(totalpercent)/int(howmanygames)):.0f} %")
    print(f"Current Rating: {myrating:.0f}")
    print(f"Rating change: {ratingdiff:.0f}")
    print(f"Average Opponent Rating: {avgopprating:.0f}")

    mydata = mydata.drop(
            ['event_code', 'opponent_name', 'NewRating', 'opponent_rating', 'event_name', 'club_code', 'org_name', 'section_title', 'opponent_no', 'increment',
             'diff_rating'], axis=1)

    print(tabulate(mydata, headers='keys', tablefmt='psql'))

except:
    print("No games in database!")
    sys.exit(1)