style=dict_style['text']['small'])
],
style=dict_style['section']['filter_style'])
filter_type_of_calls = dbc.FormGroup(
[
html.Div('Select type of calls', style=dict_style['text']['small']),
dcc.Dropdown(id='filter_type_of_calls',
options=ls_opt_filter_type_of_calls,
style=dict_style['text']['small'])
],
style=dict_style['section']['filter_style'])
##################### Filter card ####################
filters = dbc.Card([
dbc.CardHeader('Filters', className='text-center'),
dbc.Row([dbc.Col(filter_date_execution),
dbc.Col()]),
dbc.Row([dbc.Col(filter_segment),
dbc.Col(filter_category)]),
dbc.Row([dbc.Col(filter_split_skill),
dbc.Col(filter_type_of_calls)]),
dbc.CardFooter(dbc.Button('Submit filters',
color='primary',
id='but_submit_filters',
block=True,
n_clicks=0),
style={'margin-top': '20px'})
],
className='m-4'
#style={'width':'30%', 'display':'inline-block'}
'height': '60px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin-bottom': '20px'
}),
],
justify="center"), images_component,
images_component_cell,
dbc.Card([
dbc.CardHeader("Similarity Porcentage: {}".format(90),
style={
"color": "white",
"text-align": "center",
"font-size": "20px"
},
id="similarity-result"),
dbc.CardBody([
dbc.Button("Get Similarity",
color="dark",
style={
"margin-top": "20px",
"margin-bottom": "20px"
},
block=True)
]),
],
style={
"margin-top": "20px",
import re
from typing import Tuple, Optional
import dash_bootstrap_components as dbc
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
import plotly.graph_objects as go
import numpy as np
import numpy_financial as npf
from dash.exceptions import PreventUpdate
from app import app
first_card = dbc.Card([
dbc.CardHeader("Mortgage details:"),
dbc.CardBody([
dbc.FormGroup([
dbc.Label("Deposit size (£ ,000)"),
dbc.Input(id="deposit-size", type="number"),
]),
dbc.FormGroup([
dbc.Label("Purchase price (£ ,000)"),
dbc.Input(id="purchase-price", type="number"),
]),
dbc.FormGroup([
dbc.Label("Offer term (years): "),
dcc.Slider(
id="offer-term",
value=3,
marks={i: f"{i}"
var_name='Monetary Aggregates',
value_name='share_values')
df_growth = pd.melt(df_growth,
id_vars=cols[0],
value_vars=cols[1:],
var_name='Monetary Aggregates',
value_name='growth_values')
categories = df_level['Monetary Aggregates'].unique()
height = 600
width = 600
dropdown_level = dbc.Card([
dbc.CardHeader("Levels (Billions of Birr)"),
dcc.Dropdown(id='dropdown_level',
options=[{
'label': i,
'value': i
} for i in categories],
multi=True,
value=['Money supply']),
],
body=True)
dropdown_share = dbc.Card([
dbc.CardHeader("Shares (Percent)"),
dcc.Dropdown(id='dropdown_share',
options=[{
'label': i,
app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
application = app.server
app.title = 'ELISAQuant'
app.layout = html.Div([
#header
html.Div([
html.H1("ELISAQuant:", className = 'header-item'),
html.H4("An app to easily and reproducibly quantify analyte concentration", className = 'header-item')
], id = 'header'),
#body
html.Div([
html.Div([
dbc.Card([
dbc.CardHeader("Upload Data"),
dbc.CardBody([
html.Br(),
#data needed to process the data
html.Div([
dbc.Label("Choose Template", size = 'lg', style = {'width':'50%'}),
dbc.Button(html.Span([html.Img(src=app.get_asset_url('info.png'), style={'height':'100%', 'width':'100%'})]), color = 'link', id = 'temp-info-button', className = 'info-button'),
dbc.Modal([
dbc.ModalBody([
html.P("Please use one of the following two templates for your plate:"),
html.P("Option 1:"),
html.Img(src = app.get_asset_url('option_1.png'), style = {'width': '100%', 'height': '100%'}),
html.Br(),
html.Br(),
html.P("Option 2:"),
html.Img(src = app.get_asset_url('option_2.png'), style = {'width': '100%', 'height': '100%'})
def initialize_tables():
children = [
dbc.Row([
dbc.Col(
dbc.Card([
dbc.CardHeader(
html.H4("Faculty Members", className="card-title")),
dbc.CardBody([
dash_table.DataTable(
id='faculty_table',
columns=[{
"name": i,
"id": i,
"deletable": False,
"selectable": True
} for i in faculty_df.columns],
data=faculty_df.to_dict('records'),
style_table={
'overflowX': 'auto',
'minWidth': '100%',
'overflowY': 'auto',
'height': 400,
},
style_as_list_view=False,
style_header={
'backgroundColor': 'rgb(30, 30, 30)'
},
style_cell={
'backgroundColor': 'rgb(50, 50, 50)',
'color': 'white'
},
style_data_conditional=(
community_colors(community_color_dict) +
data_bars(faculty_df, 'Degree') +
data_bars(faculty_df, 'Pagerank')),
column_selectable=False,
row_selectable=False,
row_deletable=False,
css=[{
'selector': '.row',
'rule': 'margin: 0'
}],
page_current=0,
page_size=20,
page_action='native',
filter_action='native',
sort_action='native', # custom
sort_mode='multi',
)
])
])),
dbc.Col(
dbc.Card([
dbc.CardHeader(html.H4("Students",
className="card-title")),
dbc.CardBody([
dash_table.DataTable(
id='students_table',
columns=[{
"name": i,
"id": i,
"deletable": False,
"selectable": True
} for i in student_df.columns],
data=student_df.sort_values(
['Degree'],
ascending=False).to_dict('records'),
style_table={
'overflowX': 'auto',
'minWidth': '100%',
'overflowY': 'auto',
'height': 400,
},
style_as_list_view=False,
style_header={
'backgroundColor': 'rgb(30, 30, 30)'
},
style_cell={
'backgroundColor': 'rgb(50, 50, 50)',
'color': 'white'
},
style_data_conditional=(
community_colors(community_color_dict) +
data_bars(student_df, 'Degree') +
data_bars(student_df, 'Pagerank')),
column_selectable=False,
row_selectable=False,
row_deletable=False,
css=[{
'selector': '.row',
'rule': 'margin: 0'
}],
page_current=0,
page_size=20,
page_action='native',
filter_action='native',
sort_action='native', # custom
sort_mode='multi',
)
])
]))
])
]
return children
def make_asset_card(asset_info, show_money=True):
def get_color(value):
if not isinstance(value, (float, int)):
return None
if value > 0:
return 'text-danger'
if value < 0:
return 'text-success'
return None
header = dbc.CardHeader([
html.H5(
html.A(
f'{asset_info["name"]}({asset_info["code"]})',
href=f'/asset/{asset_info["code"].replace(".", "").lower()}',
target='_blank'
),
className='mb-0'
),
html.P(f'更新日期 {asset_info["price_date"]}', className='mb-0'),
])
body_content = []
body_content.append(
make_card_component(
[
{'item_cls': html.P, 'type': 'text', 'content': '持有金额/份额'},
{'item_cls': html.H4, 'type': 'money', 'content': asset_info['money']},
{'item_cls': html.P, 'type': 'amount', 'content': asset_info['amount']}
],
show_money=show_money,
)
)
body_content.append(
make_card_component(
[
{'item_cls': html.P, 'type': 'text', 'content': '日收益'},
{
'item_cls': html.H4,
'type': 'money',
'content': asset_info['day_return'],
'color': get_color(asset_info['day_return']),
},
{
'item_cls': html.P,
'type': 'percent',
'content': asset_info['day_return_rate'],
'color': get_color(asset_info['day_return']),
}
],
show_money=show_money,
)
)
body_content.append(
make_card_component(
[
{'item_cls': html.P, 'type': 'text', 'content': '现价/成本'},
{'item_cls': html.H4, 'type': 'price', 'content': asset_info['price']},
{'item_cls': html.P, 'type': 'price', 'content': asset_info['avg_cost'] or 'N/A'}
],
show_money=show_money,
)
)
asset = Asset.get(zs_code=asset_info['code'])
prices = []
for item in asset.history.order_by(AssetMarketHistory.date.desc()).limit(10):
if item.close_price is not None:
prices.append({
'date': item.date,
'price': item.close_price,
})
else:
prices.append({
'date': item.date,
'price': item.nav,
})
if len(prices) >= 10:
break
prices.sort(key=itemgetter('date'))
df = pd.DataFrame(prices)
df['date'] = pd.to_datetime(df['date'])
fig = go.Figure()
fig.add_trace(
go.Scatter(
x=df['date'],
y=df['price'],
showlegend=False,
marker={'color': 'orange'},
mode='lines+markers',
)
)
fig.update_layout(
width=150,
height=100,
margin={'l': 4, 'r': 4, 'b': 20, 't': 10, 'pad': 4},
xaxis={'showticklabels': False, 'showgrid': False, 'fixedrange': True},
yaxis={'showticklabels': False, 'showgrid': False, 'fixedrange': True},
)
fig.update_xaxes(
rangebreaks=[
{'bounds': ["sat", "mon"]},
{
'values': get_holidays(df.date.min(), df.date.max(), False)
}
]
)
body_content.append(
make_card_component(
[
{'item_cls': html.P, 'type': 'text', 'content': '十日走势'},
{
'item_cls': None,
'type': 'figure',
'content': fig
}
],
show_money=show_money
)
)
body_content.append(
make_card_component(
[
{'item_cls': html.P, 'type': 'text', 'content': '累计收益'},
{
'item_cls': html.H4,
'type': 'money',
'content': asset_info['return'],
'color': get_color(asset_info['return']),
},
{
'item_cls': html.P,
'type': 'percent',
'content': asset_info['return_rate'],
'color': get_color(asset_info['return']),
}
],
show_money=show_money,
)
)
body_content.append(
make_card_component(
[
{'item_cls': html.P, 'type': 'text', 'content': '占比'},
{'item_cls': html.H4, 'type': 'percent', 'content': asset_info['position']},
],
show_money=show_money,
)
)
card = dbc.Card(
[
header,
dbc.CardBody(
dbc.Row(
[dbc.Col([card_component]) for card_component in body_content],
),
className='py-2',
)
],
className='my-auto'
)
return card
dbc.CardHeader([
dbc.InputGroup(
size="sm",
children=[
dbc.Button(
id=f"button-fractal-{path}-clear",
children="Clear",
color="warning",
n_clicks=0,
),
dbc.DropdownMenu(
id=f"dropdownmenu-fractal-{path}",
label=f"Fractal {path.capitalize()}",
color="primary",
direction="right",
addon_type="prepend",
children=[
dbc.DropdownMenuItem(
header=True,
children=f"Examples:",
)
] + [
dbc.DropdownMenuItem(
id=f"dropdownmenuitem-fractal-{key}-{path}",
children=key,
n_clicks=0,
)
for key in Fractal.example_paths[path].keys()
],
),
dbc.Input(
f"input-fractal-{path}",
value="Custom Linear Shape",
disabled=False,
),
dbc.Button(
id=f"button-fractal-{path}-undo",
children="Undo",
color="primary",
n_clicks=0,
),
dbc.InputGroupText(
children="Modifying:",
),
dbc.Button(
id=f"button-fractal-{path}-mod",
children=fractal_segment_datum["name"],
color="primary",
n_clicks=1,
),
],
),
]),
# Local Imports
from gui.app import app
from utils.router import Router
router = Router()
page = html.Div(children=[
dbc.Row([
# DASHBOARD
dbc.Col([
# GENERAL INFO
html.Div([
dbc.Card([
dbc.CardHeader(html.P('Account Balance', className='label')),
dbc.CardBody([
html.P('$3203.71')
])
])
], className='dashboard-element-div'),
# POSITIONS
html.Div([
dbc.Card([
dbc.CardHeader(html.P('Top Positions', className='label')),
dbc.CardBody([
html.P('QQQ: $276.71 (0.37%)'),
html.P('TSLA: $420.69 (0.31%)'),
html.P('GLD: $315.81 (0.27%)'),
html.P('FNV: $154.17 (0.26%)'),
def layout(self):
return dbc.Card([
make_hideable(dbc.CardHeader([
html.Div([
html.H3(self.title, id='decisionpath-title-' + self.name),
make_hideable(html.H6(self.subtitle,
className='card-subtitle'),
hide=self.hide_subtitle),
dbc.Tooltip(self.description,
target='decisionpath-title-' + self.name),
]),
]),
hide=self.hide_title),
dbc.CardBody([
dbc.Row([
make_hideable(dbc.Col([
dbc.Label(f"{self.explainer.index_name}:",
id='decisionpath-index-label-' + self.name),
dbc.Tooltip(
f"Select {self.explainer.index_name} to display decision tree for",
target='decisionpath-index-label-' + self.name),
self.index_selector.layout(),
],
md=4),
hide=self.hide_index),
make_hideable(dbc.Col([
dbc.Label("Show tree:",
id='decisionpath-tree-label-' + self.name),
dbc.Tooltip(
f"Select decision tree to display decision tree for",
target='decisionpath-tree-label-' + self.name),
dbc.Select(
id='decisionpath-highlight-' + self.name,
options=[{
'label': str(tree),
'value': tree
} for tree in range(self.explainer.no_of_trees)],
value=self.highlight)
],
md=2),
hide=self.hide_highlight),
make_hideable(dbc.Col([self.selector.layout()], width=2),
hide=self.hide_selector),
make_hideable(dbc.Col([
dbc.Button("Generate Tree Graph",
color="primary",
id='decisionpath-button-' + self.name),
dbc.Tooltip(
"Generate visualisation of decision tree. "
"Only works if graphviz is properly installed,"
" and may take a while for large trees.",
target='decisionpath-button-' + self.name)
],
md=2,
align="end"),
hide=self.hide_button),
]),
dbc.Row([
dbc.Col([
dcc.Loading(id="loading-decisionpath-" + self.name,
children=html.Img(id="decisionpath-svg-" +
self.name)),
]),
]),
]),
])
dbc.NavItem(dbc.NavLink("USF Covid Website", href="https://www.usf.edu/coronavirus/", target='__black',
external_link=True, style=dict(hover=const.COLORS.LIGHT_GOLD)))
],
brand="COVID-19 Dashboard for University of South Florida ",
style=dict(overflowX='hidden', borderBottom='solid 1px white'),
brand_href="/home",
color=const.COLORS.LIGHT_GREEN,
fluid=True,
dark=True,
id='navigation',
expand='lg',
)
# Cards
tampa_card_content = [
dbc.CardHeader(html.H4("Tampa Campus"),
style=dict(color=const.COLORS.DARK_GREEN, background=const.COLORS.LIGHT_GREY)),
dbc.CardBody(
[
html.H4("Total Cases", className="card-title"),
html.H5(
"",
id='tampa_card_total_cases',
className="card-text",
),
html.H4('Latest Update', className='card-title'),
html.H5(
"",
id='tampa_card_update',
className="card-text",
),
def make_card(i):
return dbc.Card([
dbc.CardHeader(
dbc.Button(
'RL010101',
color='link',
n_clicks=0,
id=f'edit-rules-group-{i}-toggle'
)
),
dbc.Collapse([
dbc.CardBody([
dbc.Row([
dbc.Col([
dbc.InputGroup([
dbc.InputGroupAddon(
'Tag', addon_type='prepend',
className='input-group-prepend-110'
),
dbc.Input(),
])
], xs=12, sm=12, md=4, lg=4, xl=4),
dbc.Col([
dbc.InputGroup([
dbc.InputGroupAddon(
'IP Rad.', addon_type='prepend',
className='input-group-prepend-110'
),
dbc.Input(),
])
], className='breakColLine', xs=12, sm=12, md=4, lg=4, xl=4),
dbc.Col([
dbc.InputGroup([
dbc.InputGroupAddon(
'IP Equip.', addon_type='prepend',
className='input-group-prepend-110'
),
dbc.Input(),
])
], className='breakColLine', xs=12, sm=12, md=4, lg=4, xl=4),
], className='breakRowLine'),
dbc.Row([
dbc.Col([
dbc.InputGroup([
dbc.InputGroupAddon(
'FE', addon_type='prepend',
className='input-group-prepend-110'
),
dbc.Input(),
])
], xs=12, sm=12, md=4, lg=4, xl=4),
dbc.Col([
dbc.InputGroup([
dbc.InputGroupAddon(
'CN', addon_type='prepend',
className='input-group-prepend-110'
),
dbc.Input(),
])
], className='breakColLine', xs=12, sm=12, md=4, lg=4, xl=4),
dbc.Col([
dbc.InputGroup([
dbc.InputGroupAddon(
'Protocolo', addon_type='prepend',
className='input-group-prepend-110'
),
dbc.Select(options=[
dict(label='', value=''),
dict(label='UDP', value='UDP'),
dict(label='TCP', value='TCP'),
]),
])
], className='breakColLine', xs=12, sm=12, md=4, lg=4, xl=4),
], className='breakRowLine'),
dbc.Row([
dbc.Col([
dbc.InputGroup([
dbc.InputGroupAddon(
'Porta Tx', addon_type='prepend',
className='input-group-prepend-110'
),
dbc.Input(),
])
], xs=12, sm=12, md=4, lg=4, xl=4),
dbc.Col([
dbc.InputGroup([
dbc.InputGroupAddon(
'Porta Rx', addon_type='prepend',
className='input-group-prepend-110'
),
dbc.Input(),
])
], className='breakColLine', xs=12, sm=12, md=4, lg=4, xl=4),
dbc.Col([
dbc.InputGroup([
dbc.InputGroupAddon(
'Regra', addon_type='prepend',
className='input-group-prepend-110'
),
dbc.Select(options=[
dict(label='', value=''),
dict(label='Ativa', value='A'),
dict(label='Inativa', value='I'),
]),
])
], className='breakColLine', xs=12, sm=12, md=4, lg=4, xl=4),
], className='breakRowLine'),
]),
], id=f"edit-rules-collapse-{i}")
])
asignar = []
for row in labels:
asignar.append(colores[row])
f1 = basec[slct_axisX].values
f2 = basec[slct_axisY].values
fig40 = go.Figure(data=go.Scattergl(
x=f1,
y=f2,
mode='markers',
marker=dict(color=asignar, colorscale='Viridis', line_width=1)))
return fig40
# -----------------------------------------------------------
card1 = dbc.Card([
dbc.CardHeader("¿Que es el Secop"),
dbc.CardBody(
"El (SECOP) también denominado Servicio Electrónico de Contratación Pública por sus siglas en español, es un sistema que permite "
"a las entidades estatales cumplir con las obligaciones de publicidad de los diferentes actos expedidos en los procesos contractuales "
"y permite a los interesados en participar en los procesos de contratación, proponentes, veedurías y a la ciudadanía en general, consultar "
"el estado de los mismos.")
])
#Page-1
card2 = dbc.Card([
dbc.CardHeader("Total de inversión por mil personas"),
dbc.CardBody(
"Este indicador permite conocer la inversión territorial de cada departamento por cada mil personas. Permite estandarizar la inversión de acuerdo con "
"la población de cada departemento, lo que hace que la inversión sea analizada de manera objetiva"
)
])
card3 = dbc.Card([
O['T2,0,0'] = TAB2.RC00.values
O['T2,1,0'] = TAB2.RC10.values
O['T3,0,0'] = TAB3.RC00.values
O['T3,1,0'] = TAB3.RC10.values
O['T4,0,0'] = TAB4.RC00.values
O['T4,1,0'] = TAB4.RC10.values
O['T5,0,0'] = TAB5.RC00.values
O['T5,1,0'] = TAB5.RC10.values
O['T6,0,0'] = TAB5.RC00.values
O['T6,1,0'] = TAB5.RC10.values
O['T6,2,0'] = TAB5.RC10.values
O['T6,3,0'] = TAB5.RC10.values
C = {
} # color code : primary, secondary, info, success, warning, danger, light, dark
C['T1,0,0'] = [
dbc.Card([dbc.CardHeader(T['T1,0,0']),
dbc.CardBody(O['T1,0,0'])],
color='light',
inverse=False,
outline=True)
]
C['T1,1,0'] = [
dbc.Card([dbc.CardHeader(T['T1,1,0']),
dbc.CardBody(O['T1,1,0'])],
color='light',
inverse=False,
outline=True)
]
C['T2,0,0'] = [
dbc.Card([dbc.CardHeader(T['T2,0,0']),
dbc.CardBody(O['T2,0,0'])],
from dash.dependencies import Input, Output, State
from plotly import graph_objs as go
from sentiment import dashapp
__navbar = dbc.NavbarSimple(children=[
dbc.NavItem(dbc.NavLink('API', href='/api/', external_link=True))
],
brand='SOCIAL MEDIA ANALYTICS',
brand_href='#',
sticky='top')
__metrics = dbc.Container([
html.Br(),
dbc.Card([
dbc.CardHeader(html.H5('MODEL TRAINING METRICS')),
# dbc.CardBody(id='card-body-metrics')
dbc.CardBody(
dbc.Row([
dbc.Col('DATA SET'),
dbc.Col('MODEL'),
dbc.Col('CONFUSION MATRIX'),
dbc.Col('CLASSIFICATION REPORT'),
]))
]),
html.Br()
])
__upper = dbc.Container([
html.Br(),
dbc.Row(
dbc.Col(
T['T,0,1'] = 'T__'
T['T,1,0'] = 'T__'
T['T,1,1'] = 'T__'
T['T,2,0'] = 'T__'
T['T,2,1'] = 'T__'
O = {}
O['T,_,_'] = None
O['T,0,0'] = TAB1.RC00.values
O['T,1,0'] = TAB1.RC10.values
O['T,1,1'] = TAB1.RC11.values
O['T,2,0'] = TAB1.RC20.values
O['T,2,1'] = TAB1.RC21.values
C = {
} # color code : primary, secondary, info, success, warning, danger, light, dark
C['T,0,0'] = [
dbc.Card([dbc.CardHeader(T['T,0,0']),
dbc.CardBody(O['T,0,0'])],
color='light',
inverse=False,
outline=True)
]
C['T,1,0'] = [
dbc.Card([dbc.CardHeader(T['T,1,0']),
dbc.CardBody(O['T,1,0'])],
color='light',
inverse=False,
outline=True)
]
C['T,1,1'] = [
dbc.Card([dbc.CardHeader(T['T,1,1']),
dbc.CardBody(O['T,1,1'])],
font_color='#333')
return fig
slider = dcc.Slider(min=2015,
max=2020,
value=2020,
marks={i: i
for i in range(2015, 2021)},
id='page_customer_suppliers_relation_slider')
layout = \
dbc.Container([
dbc.Row([
dbc.Col([]),
], md=12),
dbc.Row([
dbc.Col([
dbc.Card([
dbc.CardHeader("Основные поставщики"),
dbc.CardBody([
dcc.Graph(id="page_customer_plot_suppliers_relation"),
slider
]),
]),
], md=12),
]),
])
def Pitcher_Base_layout(app):
app.title = "KBO analysis"
year = count_year()
team_name = []
pitcher_name = []
app.layout = html.Div([
baselayout,
# 그래프
dbc.Container(
[
dbc.Row(
dbc.Col(children=[html.H2("선수를 선택해 주세요")],
style={
'margin-top': 80,
'margin-right': 10,
'margin-left': 10
},
id="title")),
dbc.Row(
dbc.Col(
dbc.Alert(
"해당 분석은 한국프로야구단 공식 홈페이지인 KBO에서 스크래핑한 데이터를 바탕으로 진행되었습니다.",
color="secondary",
style={
'margin-top': 10,
'margin-right': 10,
'margin-left': 10
}))),
dbc.Row([
dbc.Col(children=[
dbc.Card(
[
dbc.CardHeader("최근 선수 스탯"),
dbc.CardBody(dcc.Graph(id='graph1')),
],
style={
'width': "auto",
'margin-top': 20,
'margin-left': 10,
'margin-right': 10,
'margin-bottom': 20
}),
dbc.Card(
[
dbc.CardHeader("월별 피출루율 빈도"),
dbc.CardBody(dcc.Graph(id='graph3')),
],
style={
'width': "auto",
'margin-top': 20,
'margin-left': 10,
'margin-right': 10,
'margin-bottom': 20
})
],
xs=12,
sm=12,
md=6,
lg=6),
dbc.Col(dbc.Card(
[
dbc.CardHeader("연도별 스탯 변화 추이"),
dbc.CardBody(dcc.Graph(id='graph2'))
],
style={
'width': "auto",
'margin-top': 20,
'margin-left': 10,
'margin-right': 10,
'margin-bottom': 20
}),
xs=12,
sm=12,
md=6,
lg=6),
],
no_gutters=True,
justify="around"),
],
id="graphs",
style={
"width": "auto",
'margin-left': 210,
'color': None,
"transition": "all .2s",
"z-index": -1
},
fluid=True),
# 사이드바
html.Div(
[
html.Div(
[
dbc.Nav([
html.P("Main",
style={
'color': '#7E8083',
'font-size': '80%'
}),
html.Li(
dbc.Row([
dbc.Col(html.I(
className="fas fa-table fa-2x",
style={
'color': '#FFFFFF',
'margin-top': 10,
'font-size': 18
}),
width="auto"),
dbc.Col(
dbc.NavItem(
dbc.NavLink(
"Pitchers",
href=
"http://127.0.0.1:5000/pitchers/",
id="pitchers",
style={
"color": "#FFFFFF",
'margin-left': -28
}))),
dbc.Col(dbc.NavItem(
dbc.NavLink(
html.I(
className=
"fas fa-chevron-right fa-xs",
style={
'color': '#FFFFFF',
'margin-top': 8
}),
href=
"http://127.0.0.1:5000/pitchers/")
),
width=3)
])),
html.Div(
[
dbc.Row([
dbc.Col(
dcc.Dropdown(
id='year_select',
options=[{
'label': i,
'value': i
} for i in year],
value='year_select',
placeholder="year",
)),
dbc.Col(
dcc.Dropdown(
id='team_name_select',
options=[{
'label': i,
'value': i
} for i in team_name],
value='team_select',
placeholder="team",
))
],
no_gutters=True,
align="center",
justify="center"),
html.Br(),
dcc.Dropdown(
id='pitcher_name_select',
options=[{
'label': i,
'value': i
} for i in pitcher_name],
value='pitcher_select',
placeholder="Choose a pitcher",
)
],
style={
'width': '100%',
'display': 'inline-block',
'font-size': '80%',
'margin-bottom': 80,
'margin-top': 5
}),
html.P("Others",
style={
'color': '#7E8083',
'font-size': '80%'
}),
html.Li(
dbc.Row([
dbc.Col(html.I(
className="fas fa-project-diagram",
style={
'color': '#7E8083',
'margin-top': 12
}),
width="auto"),
dbc.Col(
dbc.NavItem(
dbc.NavLink(
"Teams",
href=
"http://127.0.0.1:5000/teams/",
id="teams",
style={
"color": "#7E8083",
'margin-left': -30
}))),
dbc.Col(dbc.NavItem(
dbc.NavLink(
html.I(
className=
"fas fa-chevron-right fa-xs",
style={
'color': '#7E8083',
'margin-top': 8
}),
href="http://127.0.0.1:5000/teams/"
)),
width=3)
])),
html.Li(
dbc.Row([
dbc.Col(html.I(
className="fas fa-chart-bar fa-2x",
style={
'color': '#7E8083',
'margin-top': 11,
'font-size': 20
}),
width="auto"),
dbc.Col(
dbc.NavItem(
dbc.NavLink(
"Batters",
href=
"http://127.0.0.1:5000/batters/",
id="batters",
style={
"color": "#7E8083",
'margin-left': -30
}))),
dbc.Col(dbc.NavItem(
dbc.NavLink(
html.I(
className=
"fas fa-chevron-right fa-xs",
style={
'color': '#7E8083',
'margin-top': 8
}),
href=
"http://127.0.0.1:5000/batters/")),
width=3)
])),
html.Li(
dbc.Row([
dbc.Col(html.I(
className="fas fa-balance-scale fa-2x",
style={
'color': '#7E8083',
'margin-top': 11,
'font-size': 17,
'margin-left': -1.5
}),
width="auto"),
dbc.Col(
dbc.NavItem(
dbc.NavLink(
"Comparer",
href=
"http://127.0.0.1:5000/comparer/",
id="comparer",
style={
"color": "#7E8083",
'margin-left': -30
}))),
dbc.Col(dbc.NavItem(
dbc.NavLink(
html.I(
className=
"fas fa-chevron-right fa-xs",
style={
'color': '#7E8083',
'margin-top': 8
}),
href=
"http://127.0.0.1:5000/comparer/")
),
width=3)
]))
],
vertical="md",
horizontal='start',
className="ml-auto"),
],
id="sidebar",
style={
"position": "fixed",
"top": 55,
"left": "0",
"bottom": 0,
"width": "13rem",
"padding": "2rem 1rem",
"background-color": "#353A3F",
"transition": "left .2s"
})
],
id="side",
style={
"position": "fixed",
"top": 55,
"left": "0",
"bottom": 0,
"width": "100%",
"background-color": "rgba(0, 0, 0, 0.5)",
"transition": "left .2s",
})
])
@app.callback(Output('team_name_select', "options"),
Input('year_select', "value"))
def team_name_list(value):
team_name = get_team_name(value)
return [{'label': i, 'value': i} for i in team_name]
@app.callback(
Output('pitcher_name_select', "options"),
[Input('year_select', "value"),
Input('team_name_select', "value")])
def pitcher_name_list(value1, value2):
pitcher_name = pitcher_list(value1, value2)
return [{'label': i, 'value': i} for i in pitcher_name]
@app.callback(Output('title', 'children'),
Input('pitcher_name_select', "value"))
def pitcher_select_name(value):
if value != 'pitcher_select' and value != None:
children = [html.H2(f"{value} 선수의 분석결과 입니다.")]
else:
children = [html.H2("선수를 선택해 주세요")]
return children
@app.callback(
Output('pitcher_name_select', "value"),
[Input('year_select', "value"),
Input('team_name_select', "value")])
def test_one(value1, value2):
if value1 == None or value2 == None:
return None
@app.callback(Output("sidebar", "style"), Output("graphs", "style"),
Output("side", "style"), [Input("sidebtn", "n_clicks")], [
State("sidebar", "style"),
State("graphs", "style"),
State("side", "style")
])
def toggle(n, style1, style2, style3):
if n and style1['left'] == "0" and style2['margin-left'] == 210:
style1['left'] = "-13rem"
style2['margin-left'] = 0
style3['width'] = 0
return style1, style2, style3
else:
style1['left'] = "0"
style2['margin-left'] = 210
style3['width'] = "100%"
return style1, style2, style3
@app.callback(Output("graph1", "figure"), Output("graph2", "figure"), [
Input('team_name_select', "value"),
Input('pitcher_name_select', "value")
])
def pitcher_stat(value1, value2):
scores, df = pitcher_yearly_base(value1, value2)
fig1 = go.Figure(
go.Bar(x=scores[-1][3:],
y=['평균실점(RA9) ', '평균자책점(ERA) ', '수비무관투구(FIP) '],
orientation='h',
marker_color='#000000',
width=0.4,
opacity=0.6))
fig1.update_layout(margin=dict(l=0, r=0, t=0, b=0),
template='plotly_white',
yaxis=dict(showticklabels=True,
ticks='',
tickfont_size=15),
height=300,
showlegend=False)
fig2 = make_subplots(rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=0.1,
specs=[[{
"type": "scatter"
}], [{
"type": "table"
}]])
fig2.add_trace(
go.Scatter(x=df['YEAR'],
y=df['RA9'],
name='평균실점(RA9)',
marker_color='#243858'))
fig2.add_trace(
go.Scatter(x=df['YEAR'],
y=df['ERA'],
name='평균자책점(ERA)',
marker_color='#EC7D7A'))
fig2.add_trace(
go.Scatter(x=df['YEAR'],
y=df['FIP'],
name='수비무관투구(FIP)',
marker_color='#F5CA6F'))
fig2.add_trace(
go.Table(
columnorder=[1, 2, 3, 4, 5],
columnwidth=[7.5, 10, 10, 10, 10],
header=dict(values=['YEAR', 'RA9', 'ERA', 'FIP'],
height=32,
fill_color='#6E757C',
line_color='#6E757C',
align='center',
font=dict(color='white')),
cells=dict(values=[df.YEAR, df.RA9, df.ERA, df.FIP],
fill_color='white',
line_color='#6E757C',
font=dict(color='black'),
align='center',
height=32),
), 2, 1)
fig2.update_layout(height=695,
margin=dict(l=0, r=0, t=0, b=0),
template='plotly_white',
yaxis=dict(anchor="free",
side="left",
position=0.015),
xaxis=dict(tickmode='linear', dtick=1),
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="left",
x=0))
return fig1, fig2
@app.callback(Output("graph3", "figure"), [
Input('team_name_select', "value"),
Input('pitcher_name_select', "value")
])
def pitcher_graph(value1, value2):
temp = pitcher_prop(value1, value2)
fig = go.Figure()
fig.add_trace(
go.Scatter(x=temp['date'],
y=temp['OBP'],
mode='markers',
name='피출루율(OBP)',
marker=dict(size=10,
color=temp['OBP'],
colorscale='Viridis',
showscale=True)))
fig.update_layout(margin=dict(l=0, r=0, t=0, b=0),
template='plotly_white',
height=300,
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1))
return fig
return app
dbc.NavbarBrand("Emerging Risk Detection",
className="ml-2")),
],
align='center',
no_gutters=True,
),
href='https://github.com/Dhruv26/10K-emerging-risk-detection',
)
],
color="dark",
dark=True,
sticky="top",
)
WORDCLOUD_PLOTS = [
dbc.CardHeader(html.H5("Risks for a company")),
dbc.CardBody(
[
dcc.Loading(
id="loading-bigrams-comps",
children=[
dbc.Alert(
"Something's gone wrong! Give us a moment, but try loading this page again if problem persists.",
id="no-data-alert-bigrams_comp",
color="warning",
style={"display": "none"},
),
dbc.Row([
dbc.Col(html.P("Choose two companies to compare:"),
md=12),
dbc.Col(
import dash_bootstrap_components as dbc
import dash_core_components as dcc
import dash_html_components as html
import bing_maps_smartcity as bms
from data.bingmaps_data import pp_roadworks, pp_congestions, pp_webcams, pp_energy, pl_roadworks, pg_webcams
##################
# Row 0 - Functionality Tree
##################
func_tree = html.Div([
dbc.Button([
html.Img(src = './static/down-icon.png', className = 'icon d-inline-block mb-1', ),
], id = 'overview_tree_button', outline=False, className = 'tree_button'),
dbc.Collapse([
dbc.Card([
dbc.CardHeader('Functionality Tree', className = 'card_header'),
html.Img(src='./static/Showcase UI Overview.jpg', style=dict(height = '500px')),
], className = 'card py-2')
],id="overview_tree_collapse",)])
##################
# Map
##################
card_map = dbc.Card([dbc.CardHeader('City Detection Points', className = 'card_header'),
# return bingmap in callback
bms.BingMaps(
id = 'city-map',
polygons = pg_webcams,
polylines = pl_roadworks,
pushpins = pp_roadworks + pp_congestions + pp_webcams + pp_energy
)
state_recovered = df_state[df_state['State'] == v_index]['Recovered']
state_deceased = df_state[df_state['State'] == v_index]['Deaths']
return state_confirmed,state_active,state_recovered,state_deceased
body = html.Div([
html.H1("COVID INDIA DASHBOARD",style={
'textAlign': 'center',
'height' :'75px',
'font-size':'50px',
'color': '#ffffff'
})
#cards
,dbc.Row([
dbc.Col(dbc.Card([
dbc.CardHeader([html.H4("Confirmed",style={'height':'10px','font-size':'20px'})]),
dbc.CardBody([
html.P(india_confirmed,style={'font-size':'20px'})
]),
], color="danger", inverse=True,style={"height": "10rem",'textAlign':'center'}))
,dbc.Col(dbc.Card([
dbc.CardHeader([html.H4("Active",style={'height':'10px','font-size':'20px'})]),
dbc.CardBody([
html.P(india_active,style={'font-size':'20px'})
])
], color="warning", inverse=True,style={"height": "10rem",'textAlign':'center'}))
,dbc.Col(dbc.Card([
dbc.CardHeader([html.H4("Recovered",style={'height':'10px','font-size':'20px'})]),
dbc.CardBody([
import dash_html_components as html
from dash.dependencies import Input, Output, State
app = dash.Dash(__name__,
external_stylesheets=[dbc.themes.LUMEN
]) # https://bootswatch.com/default/
app.layout = html.Div([
html.Div(html.H6(
"Product: a beautiful Pizza reheated after a day in the fridge, for $99"
),
style={"text-align": "center"}),
html.Hr(),
dbc.CardHeader(
dbc.Button(
"Why should I buy reheated pizza for $99?",
color="link",
id="button-question-1",
)),
dbc.Collapse(dbc.CardBody("Because it's a lot better than a hotdog."),
id="collapse-question-1",
is_open=False),
dbc.CardHeader(
dbc.Button(
"Does it have extra cheese?",
color="link",
id="button-question-2",
)),
dbc.Collapse(dbc.CardBody(
"Yes, and it is made from the goats of Antarctica, which keeps the cheese cold and fresh."
),
id="collapse-question-2",
dropdown = dbc.Card([
dcc.Dropdown(id='id_holding',
options=[{
'label': i,
'value': i
} for i in categories],
multi=True,
value=categories),
],
body=True)
levels = dbc.Card(
[
dcc.Graph(id='id_levels'),
html.Small("Source: National Bank of Ethiopia"),
dbc.CardHeader(dbc.Button("Notes", color="link", id="button_levels")),
dbc.Collapse(dbc.CardBody("""
This variable is stock. So, one would expect an increasing trend over time.
"""),
id="collapse_levels",
is_open=False),
],
body=True,
)
growth = dbc.Card(
[
dcc.Graph(id='id_growth'),
html.Small("Source: National Bank of Ethiopia"),
@app.callback(Output('debugger_div', 'children'),
[Input('page_market_plot_change_prices', 'selectedData')])
def selected_data(selected):
print(selected)
# View
layout = \
dbc.Container([
inputs.layout,
dbc.Row([
dbc.Col([
dbc.Card([
dbc.CardHeader("Заказчики"),
dbc.CardBody([
html.Div(id="page_market_table_top_customers", className='data-table'),
]),
]),
], md=12),
]),
dbc.Row([
dbc.Col([
dbc.Card([
dbc.CardHeader("Поставщики"),
dbc.CardBody([
html.Div(id="page_market_table_top_suppliers", className='data-table'),
]),
]),
], md=12),
],
no_gutters=True,
className="mt-2"),
dbc.Row(children=dbc.Col(html.Div("A single, half-width column, width=6",
className="bg-secondary p-2"),
width=6),
className="mt-2"),
dbc.Row(children=dbc.Col(html.Div("An automatically sized column",
className="bg-secondary p-2"),
width="auto"),
className="mt-2"),
# 卡片类 ========================================================================================
html.Div(children=dbc.Row(children=[
dbc.Col(children=dbc.Card([
dbc.CardHeader("Header"),
dbc.CardBody([
dbc.CardTitle("This card has a title"),
dbc.CardText("And some text"),
]),
])),
dbc.Col(children=dbc.Card([
dbc.CardBody([
dbc.CardTitle("This card has a title"),
dbc.CardText("and some text, but no header"),
]),
],
outline=True,
color="primary")),
dbc.Col(children=dbc.Card([
dbc.CardBody([
isosurfs_vtk.append(child)
# -----------------------------------------------------------------------------
# 3D Viz
# -----------------------------------------------------------------------------
vtk_view = dash_vtk.View(id="vtk-view", children=vehicle_vtk + isosurfs_vtk)
# -----------------------------------------------------------------------------
# Control UI
# -----------------------------------------------------------------------------
controls = [
dbc.Card([
dbc.CardHeader("Geometry"),
dbc.CardBody([
dcc.Checklist(
id="geometry",
options=[{
'label': ' body',
'value': 'body'
}, {
'label': ' drivetrain',
'value': 'drive-train'
}, {
'label': ' front-wing',
'value': 'front-wing'
}, {
'label': ' rear-wing',
'value': 'rear-wing'
"""
dff = pd.DataFrame(rows)
fig = go.Figure(
data=[
go.Bar(name="Confirmed", x=dff["Country/Region"], y=dff["Confirmed"],marker_color=' #40A0E0'),
go.Bar(name="Recovered", x=dff["Country/Region"], y=dff["Recovered"],marker_color='SeaGreen'),
go.Bar(name="Dead", x=dff["Country/Region"], y=dff["Dead"],marker_color='grey'),
]
)
fig.update_layout(barmode="stack", margin=dict(l=10, r=5, t=10, b=5), height=250, width=718)
return html.Div([dcc.Graph(figure=fig)])
# cards for world figured: world confirmed cases, world recovered cases, world dead cases
card_confirmed = [
dbc.CardHeader("WORLD CONFIRMED CASES", style={"fontSize": 12, "fontWeight": "bold"}),
dbc.CardBody(
[
# html.H5("Card title", className="card-title"),
html.P("%.2f" % int(data_table["Confirmed"].sum()), style={"fontSize": 15, "fontWeight": "bold"}),
]
),
]
card_recovered = [
dbc.CardHeader("WORLD RECOVERED CASES", style={"fontSize": 12, "fontWeight": "bold"}),
dbc.CardBody(
[
# html.H5("Card title", className="card-title"),
html.P("%.2f" % round(data_table["Recovered"].sum()), style={"fontSize": 15, "fontWeight": "bold"}),
]
def create_poltab_card_pol(projdf, compdf, poldf, poldata):
polname = ''
desc = ''
projusedin_cols = [
{"name": ['Project'], "id": "projname"},
{"name": ['Project Version'], "id": "projvername"},
]
compusedin_cols = [
{"name": ['Component'], "id": "compname"},
{"name": ['Component Version'], "id": "compvername"},
]
usedbyprojstitle = html.P('Projects with Violations:', className="card-text", )
usedbycompstitle = html.P('Components with Violations:', className="card-text", )
projstable = dash_table.DataTable(
columns=projusedin_cols,
style_header={'backgroundColor': 'rgb(30, 30, 30)', 'color': 'white'},
id='poltab_card_projtable'
)
compstable = dash_table.DataTable(
columns=compusedin_cols,
style_header={'backgroundColor': 'rgb(30, 30, 30)', 'color': 'white'},
# data=comps_data.to_dict('records'),
# page_size=4, sort_action='native',
# row_selectable="single",
# sort_by=[{'column_id': 'score', 'direction': 'desc'}],
# merge_duplicate_headers=False,
id='poltab_card_comptable'
)
projselbutton = html.Div(
dbc.Button("Filter on Project", color="primary", className="mr-1", id="filter_polcard_proj_button", size='sm'),
)
compselbutton = html.Div(
dbc.Button("Filter on Component", color="primary", className="mr-1", id="filter_polcard_comp_button",
size='sm'),
)
if poldata is not None:
polid = poldata['polid']
polname = poldata['polname']
desc = poldata['desc']
# projlist = []
# projverlist = []
# for projid in projpolmapdf[projpolmapdf['polid'] == polid].projverid.unique():
# projlist.append(projdf[projdf['projverid'] == projid].projname.values[0])
# projverlist.append(projdf[projdf['projverid'] == projid].projvername.values[0])
#
# complist = []
# compverlist = []
# for compid in comppolmapdf[comppolmapdf['polid'] == polid].compverid.unique():
# complist.append(compdf[compdf['compverid'] == compid].compname.values[0])
# compverlist.append(compdf[compdf['compverid'] == compid].compvername.values[0])
#
projlist = []
projverlist = []
for projid, row in projdf.iterrows():
if len(poldf[(poldf['polid'] == polid)]) > 0:
projlist.append(row['projname'])
projverlist.append(row['projvername'])
complist = []
compverlist = []
for compid in compdf.index.values:
if len(poldf[(poldf['polid'] == polid)]) > 0:
complist.append(compdf.loc[compid]['compname'])
compverlist.append(compdf.loc[compid]['compvername'])
projs_data = pd.DataFrame({
"projname": projlist,
"projvername": projverlist
})
projstable = dash_table.DataTable(
columns=projusedin_cols,
data=projs_data.to_dict('records'),
style_header={'backgroundColor': 'rgb(30, 30, 30)', 'color': 'white'},
page_size=4, sort_action='native',
row_selectable="single",
filter_action='native',
merge_duplicate_headers=False,
id='poltab_card_projtable'
)
comps_data = pd.DataFrame({
"compname": complist,
"compvername": compverlist
})
compstable = dash_table.DataTable(
columns=compusedin_cols,
data=comps_data.to_dict('records'),
style_header={'backgroundColor': 'rgb(30, 30, 30)', 'color': 'white'},
page_size=4, sort_action='native',
row_selectable="single",
filter_action='native',
merge_duplicate_headers=False,
id='poltab_card_comptable'
)
return dbc.Card(
[
dbc.CardHeader("Policy Details"),
dbc.CardBody(
[
html.H4("Policy: " + polname, className="card-title"),
# html.H6("Description: " , className="card-subtitle"),
html.P(desc),
],
),
usedbyprojstitle, projstable, projselbutton,
usedbycompstitle, compstable, compselbutton,
], id="poltab_card_pol",
# style={"width": "28rem", "height": "50rem"},
# style={"width": "28rem"},
)
src="https://gnps-cytoscape.ucsd.edu/static/img/GNPS_logo.png",
width="120px"),
href="https://gnps.ucsd.edu"),
dbc.Nav([
dbc.NavItem(
dbc.NavLink("GNPS FBMN Group Comparison Dashboard", href="#")),
],
navbar=True)
],
color="light",
dark=False,
sticky="top",
)
DASHBOARD = [
dbc.CardHeader(html.H5("GNPS FBMN Group Comparison Dashboard")),
dbc.CardBody([
dcc.Location(id='url', refresh=False),
html.Div(id='version', children="Version - 0.1"),
html.Br(),
html.H3(children='GNPS Task Selection'),
dbc.Input(className="mb-3",
id='gnps_task',
placeholder="Enter GNPS FBMN Task ID"),
html.Br(),
html.H3(children='Metadata Selection'),
dcc.Dropdown(id="metadata_columns",
options=[{
"label": "Default",
"value": "Default"
}],
html.A(dbc.Col(html.Img(src=settings.LOGO, height="45px")),
href='/'),
dbc.Col(dbc.NavbarBrand(id='navbar-brand',
className='ml-2'),
style={'margin-left': '10px'})
],
align='center',
no_gutters=True)
],
fixed='top',
className='wa-navbar')
]),
dbc.Col([
dbc.Row([
dbc.Card([
dbc.CardHeader(add_help(html.H6('Created by'), 'created')),
html.Div(id='created-by')
],
className='col-md-3'),
dbc.Card([
dbc.CardHeader(add_help(html.H6('Messages'), 'messages')),
html.Div(id='count-message')
],
className='col-md'),
dbc.Card([
dbc.CardHeader(add_help(html.H6('Words'), 'words')),
html.Div(id='count-word')
],
className='col-md'),
dbc.Card([
dbc.CardHeader(add_help(html.H6('Emoji'), 'emoji')),