def home_tabs(teamid):
teamname = teamslist[teamslist['id'] == teamid]['name'].iloc[0]
teamcolor = [v for k, v in teamcolors.items() if k == teamname][0]
return html.Div([
dcc.Tabs(
id='tabs-home',
value='previous',
children=[
dcc.Tab(label='Previous', value='previous'),
dcc.Tab(label='Next', value='next'),
dcc.Tab(label='Reddit', value='reddit'),
],
colors={
'primary': teamcolor,
'background': '#F9F9F9',
'border': '#D6D6D6',
},
),
html.Div(id='tabs-home-content')
],
className='pretty_container three columns')
def players_plotstats(position, stat, linestat, teamid, players, goalies,
players_list, forwards_list, goalie_list):
if position in players_list:
df = pd.DataFrame.from_dict(players)
if position == 'Forwards':
df = df[df['Position'].isin(forwards_list)]
elif position == 'Defenders':
df = df[df['Position'] == 'D']
else:
df = df[df['Position'] == position]
else:
df = pd.DataFrame.from_dict(goalies)
df = df[df['Position'] == position]
df['Time on Ice'] = df['Time on Ice'].str.split(':').apply(
lambda x: int(x[0]))
teamname = teamslist[teamslist['id'] == teamid]['name'].iloc[0]
teamcolor = [v for k, v in teamcolors.items() if k == teamname]
# Create figure with secondary y-axis
plot = make_subplots(specs=[[{"secondary_y": True}]])
# Add traces
plot.add_trace(
go.Bar(x=df['Player'], y=df[stat], name="{}".format(stat)),
secondary_y=False,
)
#plot = px.bar(df, x='Player', y=stat, text=stat)
plot.update_traces(marker_color=teamcolor[0])
plot.update_xaxes(type='category')
size_x = df[stat].max() * 0.20
size_y = df[stat].max() * 0.20
# Build player list
for data in plot['data']:
x_list = data['x']
y_list = data['y']
player_ids = []
player_portraits = []
for player in x_list:
portrait = df[df['Player'] == player][''].str.extract(
r"\[(.*?)\]").iloc[0][0]
player_ids.append(id)
player_portraits.append(portrait)
for x, y, z in zip(x_list, y_list, player_portraits):
plot.add_layout_image(dict(
source=z,
x=x,
y=y + size_y,
))
plot.update_layout_images(
dict(xref="x",
yref="y",
sizex=size_x,
sizey=size_y,
xanchor='center',
yanchor='middle'))
plot.update_yaxes(range=[0, df[stat].max() + 20],
showticklabels=False,
showgrid=False)
plot.update_xaxes(showgrid=False)
if linestat is not None:
plot.add_trace(
go.Scatter(x=df['Player'],
y=df[linestat],
name="{}".format(linestat),
marker=dict(color='black')),
secondary_y=True,
)
plot.update_layout(showlegend=False)
plot.update_yaxes(range=[0, df[linestat].max() + 20],
showticklabels=False,
showgrid=False,
secondary_y=True)
plot.update_layout(margin=dict(l=10, r=10, t=10, b=10), )
return plot
def league_placements(teamid):
teamstatsplace = pd.read_sql_table('dailyteamstatsplace', con=engine)
df = teamstatsplace[teamstatsplace['team.id'] == teamid]
df_standings = league_standings[league_standings['team.id'] == teamid][[
'divisionRank', 'conferenceRank', 'leagueRank'
]]
for column in df_standings.columns:
df_standings[column] = df_standings[column].apply(
lambda x: str(x) + 'th')
df_standings[column] = df_standings[column].str.replace('1th', '1st')
df_standings[column] = df_standings[column].str.replace('2th', '2nd')
df_standings[column] = df_standings[column].str.replace('3th', '3rd')
teamname = teamslist[teamslist['id'] == teamid]['name'].iloc[0]
teamcolor = [v for k, v in teamcolors.items() if k == teamname][0]
def placement(df, column):
value = df[column]
return value
return html.Div([
html.Div([
html.Div(
[
html.P('League Rank', ),
html.H6(placement(df_standings, 'leagueRank'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Conference Rank'),
html.H6(placement(df_standings, 'conferenceRank'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Division Rank', ),
html.H6(placement(df_standings, 'divisionRank'),
style={
'color': teamcolor,
'font-weight': 'bold'
})
],
id="rank",
className="mini_container",
),
html.Div(
[
html.P('Wins', ),
html.H6(placement(df, 'stat.wins'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Losses', ),
html.H6(placement(df, 'stat.losses'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('OT', ),
html.H6(placement(df, 'stat.ot'),
style={
'color': teamcolor,
'font-weight': 'bold'
})
],
id="record",
className="mini_container",
),
html.Div(
[
html.P('Goals a Game', ),
html.H6(placement(df, 'stat.goalsPerGame'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Goals Against a Game', ),
html.H6(placement(df, 'stat.goalsAgainstPerGame'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Goals Goals Against Ratio', ),
html.H6(placement(df, 'stat.evGGARatio'),
style={
'color': teamcolor,
'font-weight': 'bold'
})
],
id="goal",
className='mini_container',
),
html.Div(
[
html.P('Save Percentage', ),
html.H6(placement(df, 'stat.savePctRank'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Shooting Percentage', ),
html.H6(placement(df, 'stat.shootingPctRank'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Shots a Game', ),
html.H6(placement(df, 'stat.shotsPerGame'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Shots Allowed', ),
html.H6(placement(df, 'stat.shotsAllowed'),
style={
'color': teamcolor,
'font-weight': 'bold'
})
],
id="shot",
className="mini_container",
),
html.Div(
[
html.P('Power Play Percentage', ),
html.H6(placement(df, 'stat.powerPlayPercentage'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Power Play Opportunities', ),
html.H6(placement(df, 'stat.powerPlayOpportunities'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Penalty Kill Percentage', ),
html.H6(placement(df, 'stat.penaltyKillPercentage'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Penalty Kill Opportunities', ),
html.H6(placement(df, 'stat.penaltyKillOpportunities'),
style={
'color': teamcolor,
'font-weight': 'bold'
})
],
id="pp",
className="mini_container",
),
html.Div(
[
html.P('Faceoff Win Percentage', ),
html.H6(placement(df, 'stat.faceOffWinPercentage'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Faceoffs Taken', ),
html.H6(placement(df, 'stat.faceOffsTaken'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Faceoffs Won', ),
html.H6(placement(df, 'stat.faceOffsWon'),
style={
'color': teamcolor,
'font-weight': 'bold'
}),
html.P('Faceoffs Lost', ),
html.H6(placement(df, 'stat.faceOffsLost'),
style={
'color': teamcolor,
'font-weight': 'bold'
})
],
id="faceoff",
className="mini_container",
),
],
id="info-container",
className="row container-display",
style={
'flex-wrap': 'wrap',
'textAlign': 'center'
}),
], )
def table_players(teamid):
teamname = teamslist[teamslist['id'] == teamid]['name'].iloc[0]
teamcolor = [v for k, v in teamcolors.items() if k == teamname]
#df_roster = teams(str(teamid)).roster()
roster_players = pd.read_sql_table('dailyplayers', con=engine)
df_roster = roster_players[roster_players['team.id'] == int(teamid)]
playerlist = df_roster['person.id'].to_list()
def f(row):
portrait = app.get_asset_url('/portraits/' + str(row['person.id']) +
'.png')
return ''.format(portrait)
df_roster.insert(loc=0, column='', value=df_roster.apply(f, axis=1))
df_roster['jerseyNumber'] = df_roster['jerseyNumber'].apply(
lambda x: '#' + str(x))
df_goalies = df_roster[df_roster['position.abbreviation'] == 'G']
df_players = df_roster[df_roster['position.abbreviation'] != 'G']
df_players = df_players[[
'', 'person.fullName', 'jerseyNumber', 'position.abbreviation',
'stat.timeOnIce', 'stat.games', 'stat.points', 'stat.assists',
'stat.goals', 'stat.hits', 'stat.timeOnIcePerGame', 'stat.faceOffPct',
'stat.pim'
]]
df_players.columns = [
'', 'Player', 'Number', 'Position', 'Time on Ice', 'Games', 'Points',
'Assists', 'Goals', 'Hits', 'Time on Ice a Game', 'Faceoff %', 'PIM'
]
df_goalies = df_goalies[[
'', 'person.fullName', 'jerseyNumber', 'position.abbreviation',
'stat.savePercentage', 'stat.timeOnIce', 'stat.games', 'stat.shutouts',
'stat.wins', 'stat.losses', 'stat.ot', 'stat.saves',
'stat.gamesStarted', 'stat.shotsAgainst', 'stat.goalsAgainst'
]]
df_goalies.columns = [
'', 'Player', 'Number', 'Position', 'Save %', 'Time on Ice', 'Games',
'Shutouts', 'Wins', 'Losses', 'OT', 'Saves', 'Games Started',
'Shots Against', 'Goals Against'
]
# border color
border_team = '2px solid ' + str(teamcolor[0])
table = dash_table.DataTable(
columns=[{
'id': c,
'name': c
} if c != '' else {
'name': c,
'id': c,
'type': 'text',
'presentation': 'markdown'
} for c in df_players.columns],
data=df_players.to_dict('records'),
#page_size=6,
sort_action='native',
style_header={
'fontWeight': 'bold',
'font-family': '"Open Sans", sans-serif',
'textAlign': 'center',
'font-size': '10px',
'vertical-align': 'middle',
'backgroundColor': teamcolor,
'color': 'white'
},
style_cell={
'textAlign': 'center',
'fontWeight': 'bold',
'font-family': '"Open Sans", sans-serif',
'border': '1px solid #F7F7F7',
'border-bottom': border_team,
'font-size': '12px',
'backgroundColor': '#F9F9F9',
'color': 'black',
'maxHeight': '40px',
'minWidth': '0px',
'maxWidth': '96px',
},
style_cell_conditional=[
{
'if': {
'column_id': ''
},
'minWidth': '40px',
'width': '50px',
'maxWidth': '40px',
'textAlign': 'center',
},
],
style_table={
'maxHeight': '359px',
'overflowY': 'scroll',
#'overflowX': 'scroll',
'vertical-align': 'middle',
'padding': '0px',
},
style_as_list_view=True,
),
table_goalies = dash_table.DataTable(
columns=[{
'id': c,
'name': c
} if c != '' else {
'name': c,
'id': c,
'type': 'text',
'presentation': 'markdown'
} for c in df_goalies.columns],
data=df_goalies.to_dict('records'),
sort_action='native',
style_header={
'fontWeight': 'bold',
'font-family': '"Open Sans", sans-serif',
'textAlign': 'center',
'font-size': '10px',
'vertical-align': 'middle',
'backgroundColor': teamcolor,
'color': 'white'
},
style_cell={
'textAlign': 'center',
'fontWeight': 'bold',
'font-family': '"Open Sans", sans-serif',
'border': '1px solid #F7F7F7',
'border-bottom': border_team,
'font-size': '12px',
'backgroundColor': '#F9F9F9',
'color': 'black',
'maxHeight': '40px',
'minWidth': '0px',
'maxWidth': '96px',
},
style_cell_conditional=[
{
'if': {
'column_id': ''
},
'minWidth': '40px',
'width': '50px',
'maxWidth': '40px',
'textAlign': 'center',
},
],
style_table={
#'maxHeight': '359px',
'overflowY': 'scroll',
#'overflowX': 'scroll',
'vertical-align': 'middle',
'padding': '0px',
},
style_as_list_view=True,
),
return table, table_goalies, df_players, df_goalies
def tablebarplot_standings(standing, teamid, teamcolors, standingsy):
#teamslist = teams().teams().sort_values(by=['name'])
teamname = teamslist[teamslist['id'] == teamid]['name'].iloc[0]
teamcolor = [v for k, v in teamcolors.items() if k == teamname]
# Build dataframe
if standing == 'league':
df = league_standings
else:
type_id = teamslist[teamslist['id'] == teamid][standing +
'.id'].iloc[0]
if standing == 'conference':
df = conf_standings[conf_standings[standing + '.id'] == type_id]
else:
df = div_standings[div_standings[standing + '.id'] == type_id]
df = pd.json_normalize(df['teamRecords'].iloc[0])
# Clean dataframe
df = df[[
'team.id', 'team.name', 'points', 'gamesPlayed', 'leagueRecord.wins',
'leagueRecord.losses', 'leagueRecord.ot', 'row', 'streak.streakCode',
'goalsAgainst', 'goalsScored'
]]
team_index = df.index[df['team.id'] == teamid].tolist()
def f(row):
logo = app.get_asset_url('/logos/' + str(row['team.id']) + '.svg')
return ''.format(logo)
df.insert(loc=0, column='', value=df.apply(f, axis=1))
df = df[[
'', 'team.name', 'points', 'gamesPlayed', 'leagueRecord.wins',
'leagueRecord.losses', 'leagueRecord.ot', 'row', 'streak.streakCode',
'goalsAgainst', 'goalsScored'
]]
df.columns = [
'', 'Team', 'Points', 'Games', 'Wins', 'Losses', 'OT', 'ROW', 'Streak',
'Goals Against', 'Goals Scored'
]
# Build table
table = dash_table.DataTable(
columns=[{
'id': c,
'name': c
} if c != '' else {
'name': c,
'id': c,
'type': 'text',
'presentation': 'markdown'
} for c in df.columns],
data=df.to_dict('records'),
#page_size=8,
sort_action="native",
style_header={
'fontWeight': 'bold',
'font-family': '"Open Sans", sans-serif',
'textAlign': 'center',
'font-size': '10px',
'vertical-align': 'middle',
'background-color': 'black',
'color': 'white'
},
style_cell={
'textAlign': 'center',
'fontWeight': 'bold',
'font-family': '"Open Sans", sans-serif',
'border': '1px solid #F7F7F7',
'border-bottom': '1px solid black',
'font-size': '12px',
'backgroundColor': '#F7F7F7',
'maxHeight': '40px',
'minWidth': '0px',
'maxWidth': '96px',
},
style_cell_conditional=[
{
'if': {
'column_id': ''
},
'minWidth': '40px',
'width': '50px',
'maxWidth': '40px',
'textAlign': 'center',
},
],
style_data_conditional=[{
'if': {
'filter_query': '{Team} = "' + teamname + '"'
},
"backgroundColor": teamcolor[0],
'color': 'white'
}],
style_table={
'maxHeight': '450px',
'overflowY': 'scroll',
'vertical-align': 'middle',
'padding': '0px',
},
style_as_list_view=True,
),
if standingsy is None:
standingsy = 'Points'
plot = px.bar(df,
x='Team',
y=standingsy,
color='Team',
color_discrete_map=teamcolors,
text=standingsy,
height=350)
plot.update_xaxes(type='category')
size_x = df[standingsy].max() * 0.10
size_y = df[standingsy].max() * 0.10
for x in plot['data']:
if x['x'] is not None:
team = x['legendgroup']
team_x = x['x']
team_y = x['y']
# find logo url based on team name
teamid_select = teamslist[teamslist['name'] == team]['id'].iloc[0]
logo = app.get_asset_url('/logos/' + str(teamid_select) + '.svg')
plot.add_layout_image(
dict(
source=logo,
x=np.array(team_x[0]),
y=np.array(team_y[0] + size_y),
))
plot.update_layout_images(
dict(xref="x",
yref="y",
sizex=size_x,
sizey=size_y,
xanchor='center',
yanchor='middle'))
plot.update_layout(showlegend=False)
plot.update_yaxes(
range=[0, df[standingsy].max() + df[standingsy].max() * 0.25],
showticklabels=False,
title=None)
plot.update_xaxes(showticklabels=False, title=None)
plot.update_layout(margin=dict(l=10, r=10, t=10, b=10), )
return table, plot