| import streamlit as st |
| import numpy as np |
| import pandas as pd |
| import time |
| from database import db |
|
|
| st.set_page_config(layout="wide") |
|
|
| st.markdown(""" |
| <style> |
| /* Tab styling */ |
| .stTabs [data-baseweb="tab-list"] { |
| gap: 8px; |
| padding: 4px; |
| } |
| .stTabs [data-baseweb="tab"] { |
| height: 50px; |
| white-space: pre-wrap; |
| background-color: #DAA520; |
| color: white; |
| border-radius: 10px; |
| gap: 1px; |
| padding: 10px 20px; |
| font-weight: bold; |
| transition: all 0.3s ease; |
| } |
| .stTabs [aria-selected="true"] { |
| background-color: #DAA520; |
| border: 3px solid #FFD700; |
| color: white; |
| } |
| .stTabs [data-baseweb="tab"]:hover { |
| background-color: #FFD700; |
| cursor: pointer; |
| } |
| div[data-baseweb="select"] > div { |
| background-color: #DAA520; |
| color: white; |
| } |
| </style>""", unsafe_allow_html=True) |
|
|
| def paginate_dataframe(df, page_size): |
| total_rows = len(df) |
| total_pages = (total_rows + page_size -1) // page_size |
|
|
| if 'current_page' not in st.session_state: |
| st.session_state['current_page'] = 0 |
| |
| start_idx = st.session_state['current_page'] * page_size |
| end_idx = start_idx + page_size |
|
|
| current_page_data = df.iloc[start_idx:end_idx] |
|
|
| return current_page_data, total_pages, total_rows |
|
|
| def display_paginated_table(df, page_size): |
| current_page_data, total_pages, total_rows = paginate_dataframe(df, page_size) |
|
|
| st.dataframe(current_page_data.style.background_gradient(axis=0).background_gradient(cmap='RdYlGn_r').format(precision=2), height = 500, use_container_width = True, hide_index = True) |
|
|
| col1, col2, col3, col4 = st.columns([1, 2, 2, 1]) |
| with col1: |
| if st.button('⏮️ First', disabled=st.session_state.current_page == 0): |
| st.session_state.current_page = 0 |
| st.rerun() |
| with col2: |
| if st.button('⬅️ Previous', disabled=st.session_state.current_page == 0): |
| st.session_state.current_page -= 1 |
| st.rerun() |
| with col3: |
| if st.button('Next ➡️', disabled=st.session_state.current_page >= total_pages - 1): |
| st.session_state.current_page += 1 |
| st.rerun() |
| with col4: |
| if st.button('Last ⏭️', disabled=st.session_state.current_page >= total_pages - 1): |
| st.session_state.current_page = total_pages - 1 |
| st.rerun() |
|
|
| @st.cache_resource(ttl = 61) |
| def init_baselines(): |
|
|
| db_pulls = ['Bullpen_Data', 'Hitter_Agg_Merge', 'Hitter_Long_Merge', 'Hitter_Short_Merge', 'Pitcher_Agg_Merge', 'Pitcher_Long_Merge', 'Pitcher_Short_Merge', |
| 'Slate_Hitters_Merge', 'Slate_Teams_Merge', 'Starting_Pitchers', 'True_AVG_Split', 'Pitcher_Info', 'Hitter_Info'] |
|
|
| for table in db_pulls: |
| collection = db[table] |
| cursor = collection.find() |
| df = pd.DataFrame(cursor) |
|
|
| if table == 'Bullpen_Data': |
| try: |
| bp_data = df.drop(columns = ['_id']) |
| except: |
| bp_data = df |
| elif table == 'Hitter_Agg_Merge': |
| try: |
| hitter_agg = df.drop(columns = ['_id']) |
| except: |
| hitter_agg = df |
| elif table == 'Hitter_Long_Merge': |
| try: |
| hitter_long = df.drop(columns = ['_id']) |
| except: |
| hitter_long = df |
| elif table == 'Hitter_Short_Merge': |
| try: |
| hitter_short = df.drop(columns = ['_id']) |
| except: |
| hitter_short = df |
| elif table == 'Pitcher_Agg_Merge': |
| try: |
| pitcher_agg = df.drop(columns = ['_id']) |
| except: |
| pitcher_agg = df |
| elif table == 'Pitcher_Long_Merge': |
| try: |
| pitcher_long = df.drop(columns = ['_id']) |
| except: |
| pitcher_long = df |
| elif table == 'Pitcher_Short_Merge': |
| try: |
| pitcher_short = df.drop(columns = ['_id']) |
| except: |
| pitcher_short = df |
| elif table == 'Slate_Hitters_Merge': |
| try: |
| slate_hitters = df.drop(columns = ['_id']) |
| except: |
| slate_hitters = df |
| elif table == 'Slate_Teams_Merge': |
| try: |
| slate_team = df.drop(columns = ['_id']) |
| except: |
| slate_team = df |
| elif table == 'Starting_Pitchers': |
| try: |
| starting_pitchers = df.drop(columns = ['_id']) |
| except: |
| starting_pitchers = df |
| elif table == 'True_AVG_Split': |
| try: |
| true_avg_split = df.drop(columns = ['_id']) |
| except: |
| true_avg_split = df |
| elif table == 'Pitcher_Info': |
| try: |
| pitcher_info = df.drop(columns = ['_id']) |
| except: |
| pitcher_info = df |
| elif table == 'Hitter_Info': |
| try: |
| hitter_info = df.drop(columns = ['_id']) |
| except: |
| hitter_info = df |
|
|
| return bp_data, hitter_agg, hitter_long, hitter_short, pitcher_agg, pitcher_long, pitcher_short, slate_hitters, slate_team, starting_pitchers, true_avg_split, pitcher_info, hitter_info |
|
|
| bp_data, hitter_agg, hitter_long, hitter_short, pitcher_agg, pitcher_long, pitcher_short, slate_hitters, slate_team, starting_pitchers, true_avg_split, pitcher_info, hitter_info = init_baselines() |
|
|
| pitcher_tab, hitter_tab, team_tab = st.tabs(['Pitchers', 'Hitters', 'Team']) |
|
|
| with pitcher_tab: |
| with st.container(border = True): |
| st.info('Note: Splits options are available for all baseline tables, they do not apply to True AVG, HWSr, or the Overview tables') |
| col1, col2, col3, col4, col5 = st.columns(5) |
| with col1: |
| site_var_sp = st.selectbox('Site', ['DraftKings', 'FanDuel'], key = 'site_var_sp') |
| with col2: |
| table_var_sp = st.selectbox('Table', ['True AVG Splits', 'HWSr Splits', 'Current Slate Overview', 'Active Baselines', 'League Aggregate Baselines', 'League Short Term Baselines', 'League Long Term Baselines'], key = 'table_var_sp') |
| with col3: |
| splits_var_sp = st.selectbox('Splits', ['RHH', 'LHH', 'Overall'], key = 'splits_var_sp') |
| with col4: |
| team_type_sp = st.selectbox('Do you want to view all teams or Specific ones?', ['All', 'Specific'], key = 'team_type_sp') |
| with col5: |
| if team_type_sp == 'Specific': |
| team_var_sp = st.multiselect('Select Teams', starting_pitchers['Team'].unique(), key = 'team_var_sp') |
| else: |
| team_var_sp = None |
| st.write('All teams selected') |
| |
| if table_var_sp == 'True AVG Splits': |
| disp_raw = true_avg_split |
|
|
| if team_var_sp is not None: |
| disp_raw = disp_raw[disp_raw['Team'].isin(team_var_sp)] |
|
|
| disp_raw = disp_raw[['Player', 'Handedness', 'Team', 'Opp', 'Opp LHH', 'Opp RHH', 'True AVG (LHH)', 'True AVG (RHH)', 'True AVG (Overall)', 'Weighted True AVG']] |
|
|
| elif table_var_sp == 'HWSr Splits': |
| disp_raw = true_avg_split |
|
|
| if team_var_sp is not None: |
| disp_raw = disp_raw[disp_raw['Team'].isin(team_var_sp)] |
|
|
| disp_raw = disp_raw[['Player', 'Handedness', 'Team', 'Opp', 'Opp LHH', 'Opp RHH', 'HWSr (LHH)', 'HWSr (RHH)', 'HWSr (Overall)', 'Weighted HWSr']] |
| |
|
|
| elif table_var_sp == 'Current Slate Overview': |
| disp_raw = starting_pitchers |
|
|
| disp_raw = disp_raw.drop(columns = ['DK Own Adj', 'Perf_Adj', 'Curr']) |
|
|
| if team_var_sp is not None: |
| disp_raw = disp_raw[disp_raw['Team'].isin(team_var_sp)] |
|
|
| elif table_var_sp == 'Active Baselines': |
| disp_raw = pitcher_info |
|
|
| if splits_var_sp != 'Overall': |
| disp_raw = disp_raw[disp_raw['Set'] == splits_var_sp] |
| else: |
| disp_raw = disp_raw[disp_raw['Set'] == 'RHH'] |
| |
| if team_var_sp is not None: |
| disp_raw = disp_raw[disp_raw['Team'].isin(team_var_sp)] |
|
|
| disp_raw = disp_raw[['Names', 'DK_Salary', 'FD_Salary', 'Team', 'Opp', 'Opp_TT', 'Hand', 'K%', 'BB%', 'True AVG', 'xSLG', 'xBA', 'Hits', 'xHRs', 'xHR/PA']] |
| positive_set = ['K%'] |
|
|
| elif table_var_sp == 'League Aggregate Baselines': |
| disp_raw = pitcher_agg |
| disp_raw = disp_raw[disp_raw['Set'] == splits_var_sp] |
| disp_raw = disp_raw[['Player', 'PA', 'Hits', 'Singles', 'Doubles', 'Homeruns', 'Strikeoutper', 'Strikeouts', 'Walkper', 'Walks', 'xBA', 'xSLG', 'xwOBA', 'BABIP', 'AVG', 'FB%', 'True_AVG', 'xHits', 'xHRs', 'xHR/PA', 'HWSr']] |
|
|
| elif table_var_sp == 'League Short Term Baselines': |
| disp_raw = pitcher_short |
| disp_raw = disp_raw[disp_raw['Set'] == splits_var_sp] |
| disp_raw = disp_raw[['Player', 'PA', 'Hits', 'Singles', 'Doubles', 'Homeruns', 'Strikeoutper', 'Strikeouts', 'Walkper', 'Walks', 'xBA', 'xSLG', 'xwOBA', 'BABIP', 'AVG', 'FB%', 'True_AVG', 'xHits', 'xHRs', 'xHR/PA', 'HWSr']] |
|
|
| elif table_var_sp == 'League Long Term Baselines': |
| disp_raw = pitcher_long |
| disp_raw = disp_raw[disp_raw['Set'] == splits_var_sp] |
| disp_raw = disp_raw[['Player', 'PA', 'Hits', 'Singles', 'Doubles', 'Homeruns', 'Strikeoutper', 'Strikeouts', 'Walkper', 'Walks', 'xBA', 'xSLG', 'xwOBA', 'BABIP', 'AVG', 'FB%', 'True_AVG', 'xHits', 'xHRs', 'xHR/PA', 'HWSr']] |
|
|
| st.session_state['sp_disp_frame'] = disp_raw |
| page_var = len(st.session_state['sp_disp_frame']) / 2 |
| sp_disp_container = st.container(border = True) |
| sp_disp_container = sp_disp_container.empty() |
| |
| if table_var_sp in (['League Aggregate Baselines', 'League Short Term Baselines', 'League Long Term Baselines']): |
|
|
| with st.spinner("Full league baselines can take some time to load"): |
| time.sleep(5) |
| display_paginated_table(st.session_state['sp_disp_frame'], 50) |
| else: |
| with sp_disp_container: |
| st.dataframe(st.session_state['sp_disp_frame'].style.background_gradient(axis=0).background_gradient(cmap='RdYlGn_r').format(precision=2), height = 500, use_container_width = True, hide_index = True) |
|
|
| with hitter_tab: |
| with st.container(border = True): |
| st.info('Note: Splits options are available for all baseline tables') |
| col1, col2, col3, col4, col5 = st.columns(5) |
| with col1: |
| site_var_hitter = st.selectbox('Site', ['Draftkings', 'Fanduel'], key = 'site_var_hitter') |
| with col2: |
| table_var_hitter = st.selectbox('Table', ['Current Slate Overview', 'Active Baselines', 'League Aggregate Baselines', 'League Short Term Baselines', 'League Long Term Baselines'], key = 'table_var_hitter') |
| with col3: |
| splits_var_hitter = st.selectbox('Splits', ['Overall', 'RHP', 'LHP'], key = 'splits_var_hitter') |
| with col4: |
| position_type_hitter = st.selectbox('Do you want to view all Positions or Specific ones?', ['All', 'Specific'], key = 'position_type_hitter') |
| if position_type_hitter == 'Specific': |
| position_var_hitter = st.multiselect('Positions', ['C', '1B', '2B', '3B', 'SS', 'OF'], key = 'position_var_hitter') |
| else: |
| position_var_hitter = None |
| st.write('All Positions selected') |
| with col5: |
| team_type_hitter = st.selectbox('Do you want to view all Teams or Specific ones?', ['All', 'Specific'], key = 'team_type_hitter') |
| if team_type_hitter == 'Specific': |
| team_var_hitter = st.multiselect('Select Teams', slate_hitters['Team'].unique(), key = 'team_var_hitter') |
| else: |
| team_var_hitter = None |
| st.write('All Teams selected') |
|
|
| if table_var_hitter == 'Current Slate Overview': |
| disp_raw = slate_hitters |
| |
| if team_var_hitter is not None: |
| disp_raw = disp_raw[disp_raw['Team'].isin(team_var_hitter)] |
|
|
| if position_var_hitter: |
| position_mask = disp_raw['Position'].apply(lambda x: any(pos in x for pos in position_var_hitter)) |
| disp_raw = disp_raw[position_mask] |
| |
| disp_raw = disp_raw[disp_raw['Set'] == site_var_hitter] |
|
|
| elif table_var_hitter == 'Active Baselines': |
| disp_raw = hitter_info |
| |
| if team_var_hitter is not None: |
| disp_raw = disp_raw[disp_raw['Team'].isin(team_var_hitter)] |
| |
| if position_var_hitter: |
| position_mask = disp_raw['Position'].apply(lambda x: any(pos in x for pos in position_var_hitter)) |
| disp_raw = disp_raw[position_mask] |
| |
| disp_raw = disp_raw.drop(columns = ['DK_SD_Salary', 'FD_SD_Salary', 'DK_Own', 'FD_Own', 'DK_player_ID', 'FD_player_ID', 'Opp_TT']) |
|
|
| elif table_var_hitter == 'League Aggregate Baselines': |
| disp_raw = hitter_agg |
| |
| if team_var_hitter is not None: |
| disp_raw = disp_raw[disp_raw['Team'].isin(team_var_hitter)] |
|
|
| elif table_var_hitter == 'League Short Term Baselines': |
| disp_raw = hitter_short |
| |
| if team_var_hitter is not None: |
| disp_raw = disp_raw[disp_raw['Team'].isin(team_var_hitter)] |
|
|
| elif table_var_hitter == 'League Long Term Baselines': |
| disp_raw = hitter_long |
| |
| if team_var_hitter is not None: |
| disp_raw = disp_raw[disp_raw['Team'].isin(team_var_hitter)] |
|
|
| st.session_state['hitter_disp_frame'] = disp_raw |
| hitter_disp_container = st.container(border = True) |
| hitter_disp_container = hitter_disp_container.empty() |
|
|
| with hitter_disp_container: |
| if table_var_hitter in (['League Aggregate Baselines', 'League Short Term Baselines', 'League Long Term Baselines']): |
| with st.spinner("Full league baselines can take some time to load"): |
| time.sleep(7) |
| display_paginated_table(st.session_state['hitter_disp_frame'], 50) |
| else: |
| st.dataframe(st.session_state['hitter_disp_frame'].style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height = 750, use_container_width = True, hide_index = True) |
|
|
| with team_tab: |
| with st.container(border = True): |
| col1, col2, col3 = st.columns(3) |
| with col1: |
| site_var_team= st.selectbox('Site', ['DraftKings', 'FanDuel'], key = 'site_var_team') |
| with col2: |
| table_var_team = st.selectbox('Table', ['Team Baselines', 'Bullpen Baselines'], key = 'table_var_team') |
| |
| if table_var_team == 'Team Baselines': |
| st.session_state['team_disp_frame'] = slate_team |
| elif table_var_team == 'Bullpen Baselines': |
| st.session_state['team_disp_frame'] = bp_data |
|
|
| team_disp_container = st.container(border = True) |
| team_disp_container = team_disp_container.empty() |
|
|
| with team_disp_container: |
| st.dataframe(st.session_state['team_disp_frame'].style.background_gradient(axis=0).background_gradient(cmap='RdYlGn').format(precision=2), height = 750, use_container_width = True, hide_index = True) |