import pandas as pd import streamlit as st import gspread scope = ['https://www.googleapis.com/auth/spreadsheets', "https://www.googleapis.com/auth/drive"] credentials = { "type": "service_account", "project_id": "sheets-api-connect-378620", "private_key_id": "1005124050c80d085e2c5b344345715978dd9cc9", "private_key": "-----BEGIN PRIVATE KEY-----\nMIIEvQIBADANBgkqhkiG9w0BAQEFAASCBKcwggSjAgEAAoIBAQCtKa01beXwc88R\nnPZVQTNPVQuBnbwoOfc66gW3547ja/UEyIGAF112dt/VqHprRafkKGmlg55jqJNt\na4zceLKV+wTm7vBu7lDISTJfGzCf2TrxQYNqwMKE2LOjI69dBM8u4Dcb4k0wcp9v\ntW1ZzLVVuwTvmrg7JBHjiSaB+x5wxm/r3FOiJDXdlAgFlytzqgcyeZMJVKKBQHyJ\njEGg/1720A0numuOCt71w/2G0bDmijuj1e6tH32MwRWcvRNZ19K9ssyDz2S9p68s\nYDhIxX69OWxwScTIHLY6J2t8txf/XMivL/636fPlDADvBEVTdlT606n8CcKUVQeq\npUVdG+lfAgMBAAECggEAP38SUA7B69eTfRpo658ycOs3Amr0JW4H/bb1rNeAul0K\nZhwd/HnU4E07y81xQmey5kN5ZeNrD5EvqkZvSyMJHV0EEahZStwhjCfnDB/cxyix\nZ+kFhv4y9eK+kFpUAhBy5nX6T0O+2T6WvzAwbmbVsZ+X8kJyPuF9m8ldcPlD0sce\ntj8NwVq1ys52eosqs7zi2vjt+eMcaY393l4ls+vNq8Yf27cfyFw45W45CH/97/Nu\n5AmuzlCOAfFF+z4OC5g4rei4E/Qgpxa7/uom+BVfv9G0DIGW/tU6Sne0+37uoGKt\nW6DzhgtebUtoYkG7ZJ05BTXGp2lwgVcNRoPwnKJDxQKBgQDT5wYPUBDW+FHbvZSp\nd1m1UQuXyerqOTA9smFaM8sr/UraeH85DJPEIEk8qsntMBVMhvD3Pw8uIUeFNMYj\naLmZFObsL+WctepXrVo5NB6RtLB/jZYxiKMatMLUJIYtcKIp+2z/YtKiWcLnwotB\nWdCjVnPTxpkurmF2fWP/eewZ+wKBgQDRMtJg7etjvKyjYNQ5fARnCc+XsI3gkBe1\nX9oeXfhyfZFeBXWnZzN1ITgFHplDznmBdxAyYGiQdbbkdKQSghviUQ0igBvoDMYy\n1rWcy+a17Mj98uyNEfmb3X2cC6WpvOZaGHwg9+GY67BThwI3FqHIbyk6Ko09WlTX\nQpRQjMzU7QKBgAfi1iflu+q0LR+3a3vvFCiaToskmZiD7latd9AKk2ocsBd3Woy9\n+hXXecJHPOKV4oUJlJgvAZqe5HGBqEoTEK0wyPNLSQlO/9ypd+0fEnArwFHO7CMF\nycQprAKHJXM1eOOFFuZeQCaInqdPZy1UcV5Szla4UmUZWkk1m24blHzXAoGBAMcA\nyH4qdbxX9AYrC1dvsSRvgcnzytMvX05LU0uF6tzGtG0zVlub4ahvpEHCfNuy44UT\nxRWW/oFFaWjjyFxO5sWggpUqNuHEnRopg3QXx22SRRTGbN45li/+QAocTkgsiRh1\nqEcYZsO4mPCsQqAy6E2p6RcK+Xa+omxvSnVhq0x1AoGAKr8GdkCl4CF6rieLMAQ7\nLNBuuoYGaHoh8l5E2uOQpzwxVy/nMBcAv+2+KqHEzHryUv1owOi6pMLv7A9mTFoS\n18B0QRLuz5fSOsVnmldfC9fpUc6H8cH1SINZpzajqQA74bPwELJjnzrCnH79TnHG\nJuElxA33rFEjbgbzdyrE768=\n-----END PRIVATE KEY-----\n", "client_email": "gspread-connection@sheets-api-connect-378620.iam.gserviceaccount.com", "client_id": "106625872877651920064", "auth_uri": "https://accounts.google.com/o/oauth2/auth", "token_uri": "https://oauth2.googleapis.com/token", "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs", "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/gspread-connection%40sheets-api-connect-378620.iam.gserviceaccount.com" } gc = gspread.service_account_from_dict(credentials) st.set_page_config(layout="wide") @st.cache_data def init_baselines(): sh = gc.open_by_url('https://docs.google.com/spreadsheets/d/10MVGsAHJPUAdK9SJ28ZqjgBgV2xBJSXEka-s2pIxHHE/edit#gid=1858245367') worksheet = sh.worksheet('ROO') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Player'] != 'Welp'] raw_display = raw_display.loc[raw_display['Salary'] > 0] raw_display = raw_display.loc[raw_display['Median'] > 0] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') roo_table = raw_display.sort_values(by='Median', ascending=False) # worksheet = sh.worksheet('Positional_Boosts') # raw_display = pd.DataFrame(worksheet.get_all_records()) # raw_display.replace("", 'Welp', inplace=True) # raw_display = raw_display.loc[raw_display['teamname'] != 'Welp'] # raw_display = raw_display.apply(pd.to_numeric, errors='ignore') # positional_boosts = raw_display.sort_values(by='Avg_Allowed', ascending=False) worksheet = sh.worksheet('Overall_Stacks') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Team'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lck_overall_stacks = raw_display.sort_values(by='Stack+', ascending=False) worksheet = sh.worksheet('Win_Stacks') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Team'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lck_win_stacks = raw_display.sort_values(by='Stack+', ascending=False) worksheet = sh.worksheet('Loss_Stacks') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Team'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lck_loss_stacks = raw_display.sort_values(by='Stack+', ascending=False) worksheet = sh.worksheet('Overall_BO1_Stats') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Player'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lck_bo1 = raw_display worksheet = sh.worksheet('Overall_BO3_Stats') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Player'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lck_bo3 = raw_display worksheet = sh.worksheet('Overall_BO5_Stats') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Player'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lck_bo5 = raw_display sh = gc.open_by_url('https://docs.google.com/spreadsheets/d/10MVGsAHJPUAdK9SJ28ZqjgBgV2xBJSXEka-s2pIxHHE/edit#gid=1858245367') worksheet = sh.worksheet('Overall_Stacks') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Team'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lcs_overall_stacks = raw_display.sort_values(by='Stack+', ascending=False) worksheet = sh.worksheet('Win_Stacks') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Team'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lcs_win_stacks = raw_display.sort_values(by='Stack+', ascending=False) worksheet = sh.worksheet('Loss_Stacks') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Team'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lcs_loss_stacks = raw_display.sort_values(by='Stack+', ascending=False) worksheet = sh.worksheet('Overall_BO1_Stats') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Player'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lcs_bo1 = raw_display worksheet = sh.worksheet('Overall_BO3_Stats') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Player'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lcs_bo3 = raw_display worksheet = sh.worksheet('Overall_BO5_Stats') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Player'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lcs_bo5 = raw_display sh = gc.open_by_url('https://docs.google.com/spreadsheets/d/1oOJD_QcBeDJ1f7e9FfgUHOQEPT6kvU0Sa9hQ_4B8gqc/edit?gid=1288836099#gid=1288836099') worksheet = sh.worksheet('Overall_Stacks') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Team'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lec_overall_stacks = raw_display.sort_values(by='Stack+', ascending=False) worksheet = sh.worksheet('Win_Stacks') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Team'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lec_win_stacks = raw_display.sort_values(by='Stack+', ascending=False) worksheet = sh.worksheet('Loss_Stacks') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Team'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lec_loss_stacks = raw_display.sort_values(by='Stack+', ascending=False) worksheet = sh.worksheet('Overall_BO1_Stats') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Player'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lec_bo1 = raw_display worksheet = sh.worksheet('Overall_BO3_Stats') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Player'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lec_bo3 = raw_display worksheet = sh.worksheet('Overall_BO5_Stats') raw_display = pd.DataFrame(worksheet.get_all_records()) raw_display.rename(columns={"Name": "Player", "Nickname": "Player", "Fantasy": "Median"}, inplace = True) raw_display.replace("", 'Welp', inplace=True) raw_display = raw_display.loc[raw_display['Player'] != 'Welp'] raw_display = raw_display.apply(pd.to_numeric, errors='ignore') lec_bo5 = raw_display return roo_table, lck_overall_stacks, lck_win_stacks, lck_loss_stacks, lcs_overall_stacks, lcs_win_stacks, lcs_loss_stacks, lec_overall_stacks, lec_win_stacks, lec_loss_stacks, lck_bo1, lck_bo3, lck_bo5, lcs_bo1, lcs_bo3, lcs_bo5, lec_bo1, lec_bo3, lec_bo5 roo_table, lck_overall_stacks, lck_win_stacks, lck_loss_stacks, lcs_overall_stacks, lcs_win_stacks, lcs_loss_stacks, lec_overall_stacks, lec_win_stacks, lec_loss_stacks, lck_bo1, lck_bo3, lck_bo5, lcs_bo1, lcs_bo3, lcs_bo5, lec_bo1, lec_bo3, lec_bo5 = init_baselines() tab1, tab2, tab3 = st.tabs(["LOL Stacks Table", "LOL Range of Outcomes", "LOL Player Base Stats"]) def convert_df_to_csv(df): return df.to_csv().encode('utf-8') with tab1: if st.button("Reset Data", key='reset1'): # Clear values from *all* all in-memory and on-disk data caches: # i.e. clear values from both square and cube st.cache_data.clear() roo_table, lck_overall_stacks, lck_win_stacks, lck_loss_stacks, lcs_overall_stacks, lcs_win_stacks, lcs_loss_stacks, lec_overall_stacks, lec_win_stacks, lec_loss_stacks, lck_bo1, lck_bo3, lck_bo5, lcs_bo1, lcs_bo3, lcs_bo5, lec_bo1, lec_bo3, lec_bo5 = init_baselines() league_choice1 = st.radio("What table would you like to display?", ('LCK/LPL', 'LCS', 'LEC'), key='league_var1') if league_choice1 == 'LCK/LPL': league_hold = lck_overall_stacks elif league_choice1 == 'LCS': league_hold = lcs_overall_stacks elif league_choice1 == 'LEC': league_hold = lec_overall_stacks display = league_hold.set_index('Team') st.dataframe(display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), use_container_width = True) st.download_button( label="Export Stacks", data=convert_df_to_csv(display), file_name='LOL_Stacks_export.csv', mime='text/csv', ) with tab2: if st.button("Reset Data", key='reset2'): # Clear values from *all* all in-memory and on-disk data caches: # i.e. clear values from both square and cube st.cache_data.clear() roo_table, lck_overall_stacks, lck_win_stacks, lck_loss_stacks, lcs_overall_stacks, lcs_win_stacks, lcs_loss_stacks, lec_overall_stacks, lec_win_stacks, lec_loss_stacks, lck_bo1, lck_bo3, lck_bo5, lcs_bo1, lcs_bo3, lcs_bo5, lec_bo1, lec_bo3, lec_bo5 = init_baselines() with st.container(): col1, col2, col3, col4 = st.columns([4, 2, 2, 2]) with col1: league_choice2 = st.radio("What table would you like to display?", ('LCK/LPL', 'LCS', 'LEC'), key='league_var2') if league_choice2 == 'LCK/LPL': league_hold = roo_table[roo_table['league'] == 'LCK'] elif league_choice2 == 'LCS': league_hold = roo_table[roo_table['league'] == 'LCS'] elif league_choice2 == 'LEC': league_hold = roo_table[roo_table['league'] == 'LEC'] with col2: model_choice = st.radio("What table would you like to display?", ('Overall', 'Wins', 'Losses'), key='roo_table') if model_choice == 'Overall': hold_display = league_hold[league_hold['type'] == 'Overall'] elif model_choice == 'Wins': hold_display = league_hold[league_hold['type'] == 'Wins'] elif model_choice == 'Losses': hold_display = league_hold[league_hold['type'] == 'Losses'] with col3: pos_var1 = st.selectbox('View specific position?', options = ['All', 'TOP', 'JNG', 'MID', 'ADC', 'SUP'], key = 'roo_posvar') with col4: team_var1 = st.multiselect('View specific team?', options = hold_display['Team'].unique(), key = 'roo_teamvar') display = hold_display.set_index('Player') if team_var1: display = display[display['Team'].isin(team_var1)] if pos_var1 == 'All': display = display elif pos_var1 != 'All': display = display[display['Position'].str.contains(pos_var1)] display = display.drop(columns=['type', 'league', 'Timestamp']) display['Cpt_Own'] = ((display['Own']) * ((100 - (100-display['Own'])))) / 300 scale_var = display['Cpt_Own'].sum() display['Cpt_Own'] = display['Cpt_Own'] * (100 / scale_var) st.dataframe(display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height=750, use_container_width = True) st.download_button( label="Export Range of Outcomes", data=convert_df_to_csv(display), file_name='LOL_ROO_export.csv', mime='text/csv', ) with tab3: if st.button("Reset Data", key='reset3'): # Clear values from *all* all in-memory and on-disk data caches: # i.e. clear values from both square and cube st.cache_data.clear() roo_table, lck_overall_stacks, lck_win_stacks, lck_loss_stacks, lcs_overall_stacks, lcs_win_stacks, lcs_loss_stacks, lec_overall_stacks, lec_win_stacks, lec_loss_stacks, lck_bo1, lck_bo3, lck_bo5, lcs_bo1, lcs_bo3, lcs_bo5, lec_bo1, lec_bo3, lec_bo5 = init_baselines() with st.container(): col1, col2, col3, col4 = st.columns([4, 2, 2, 2]) with col1: league_choice3 = st.radio("What table would you like to display?", ('LCK/LPL', 'LCS', 'LEC'), key='league_var3') with col2: gametype_choice = st.radio("What format are the games being played?", ('Best of 1', 'Best of 3', 'Best of 5'), key='player_stats') with col3: pos_var2 = st.selectbox('View specific position?', options = ['All', 'TOP', 'JNG', 'MID', 'ADC', 'SUP'], key = 'proj_posvar') with col4: team_var2 = st.multiselect('View specific team?', options = hold_display['Team'].unique(), key = 'proj_teamvar') if league_choice3 == 'LCK/LPL': if gametype_choice == 'Best of 1': hold_display = lck_bo1 elif gametype_choice == 'Best of 3': hold_display = lck_bo3 elif gametype_choice == 'Best of 5': hold_display = lck_bo5 display = hold_display.set_index('Player') elif league_choice3 == 'LCS': if gametype_choice == 'Best of 1': hold_display = lcs_bo1 elif gametype_choice == 'Best of 3': hold_display = lcs_bo3 elif gametype_choice == 'Best of 5': hold_display = lcs_bo5 display = hold_display.set_index('Player') elif league_choice3 == 'LEC': if gametype_choice == 'Best of 1': hold_display = lec_bo1 elif gametype_choice == 'Best of 3': hold_display = lec_bo3 elif gametype_choice == 'Best of 5': hold_display = lec_bo5 display = hold_display.set_index('Player') if team_var2: display = display[display['Team'].isin(team_var2)] if pos_var2 == 'All': display = display elif pos_var2 != 'All': display = display[display['Position'].str.contains(pos_var2)] st.dataframe(display.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height=750, use_container_width = True) st.download_button( label="Export Baselines", data=convert_df_to_csv(display), file_name='LOL_Baselines_export.csv', mime='text/csv', )