MLB_Research_Sheets / src /streamlit_app.py
James McCool
fixing some div spacing
3c6c2d6
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)