def create_pie(value, name, color='rgba(59, 64, 72, 100)', **card_props):
# TODO: Read in bgcolor from theme
fig = {
'data': [{
'values': value,
'textinfo': 'none',
'hoverinfo': 'value+percent',
'type': 'pie',
'hole': 0.5,
'marker': {
'colors': [color, 'var(--border)'],
'line': {
'width': 20,
'color': 'var(--background)'
}
}
}],
'layout': {
'margin': {
'l': 10,
'r': 10,
't': 10,
'b': 10
},
'showlegend': False,
'height': 200,
}
}
pie = ddk.Graph(id='id' + name,
figure=fig,
config={'displayModeBar': False})
return ddk.Card(pie, **card_props)
from dash.dependencies import Input, Output
app = dash.Dash(__name__)
server = app.server # expose server variable for Procfile
app.layout = ddk.App([
ddk.Header([
ddk.Logo(src=app.get_asset_url('logo.png')),
ddk.Title('Dash Enterprise Sample Application'),
]),
ddk.Row(children=[
ddk.Card(children=ddk.Graph(figure={
'data': [{
'x': [1, 2, 3, 4],
'y': [4, 1, 6, 9],
'line': {
'shape': 'spline'
}
}]
}, )),
]),
ddk.Row(children=[
ddk.Card(width=50,
children=ddk.Graph(figure={
'data': [{
'x': [1, 2, 3, 4],
'y': [4, 1, 6, 9],
'line': {
'shape': 'spline'
}
}]
'max-height': 100,
'width': 'auto'
}),
ddk.Title('TELONAS2'),
ddk.SectionTitle('', id='final_date'),
html.Button('Refresh', style={'float': 'right'}, id='refresh', n_clicks=0),
]),
ddk.Block(
children=[
dcc.Tabs(id='selected-tab', value='load',
children=[
dcc.Tab(label="Load", value='load',
children=[ddk.Card(width=100,
children=[
dcc.Loading(id='load_loader', children=[
ddk.Graph(id="load_plot", config=graph_config)]),
]
)
]
)
]
),
dcc.Tab(label="Profiles", value='profiles',
children=[ddk.Card(width=100,
children=[
dcc.Loading(id='profile_loader', children=[
ddk.Graph(id="profile_plot", config=graph_config)])
]
)
]
)
),
]
), # end of app-description Card and it's children
]), # end of About tab and it's children
]), # end of dcc.Tabs() and it's children
] # end of left-hand column - children
), # end of left-hand column
ddk.Block( # right-hand column
width=80,
children=[
ddk.Card( # map of canada
padding=0,
children=[
ddk.CardHeader(
title='Geographic Representation of Funding'),
ddk.Graph(id='map-graph'),
]),
ddk.Card( # Companies Dataframe Table
children=[
ddk.CardHeader(
title='Search by Company or Project Keyword'),
ddk.DataTable(
id='companies-table',
columns=[{
"name": i,
"id": i
} for i in df[[
'Company_Name', 'Project', '$_Amount'
]].columns],
fill_width=False,
filter_action='native',
import dash_core_components as dcc
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import requests
from datetime import datetime as dt
r = requests.get("https://financialmodelingprep.com/api/v3/quote/BTCUSD")
time = []
price = []
app = dash.Dash()
server = app.server
app.layout = ddk.App(children=[
ddk.Card(ddk.Graph(id="graph")),
dcc.Interval(id="liveupdate", interval=10000, n_intervals=0),
])
@app.callback(Output("graph", "figure"), [Input("liveupdate", "n_intervals")])
def gaph_update(n):
price.append(
requests.get("https://financialmodelingprep.com/api/v3/quote/BTCUSD").
json()[0]["price"])
time.append(
dt.utcfromtimestamp(
int(
requests.get(
"https://financialmodelingprep.com/api/v3/quote/BTCUSD").
# children=[
# dcc.Graph(figure=px.scatter_geo(df2, lat='Latitude', lon='Longitude', color="Period", size='LatLongPeriodCount',
# hover_name="Country").update_geos(projection_type="orthographic")),
# ],
# ),
ddk.Card(
width=43,
children=[
ddk.CardHeader(title='Which Country Fossils Were Found'),
dcc.Graph(id='display-map', figure={}),
],),
ddk.Card(
width=56,
children=[
ddk.CardHeader(title='Total Found by Country'),
ddk.Graph(id='display-scatter', figure={}),
],
),
# px.scatter(df, x="MillionsYears", y=len(df.axes[0]), color="Period"),
],
),
]
),
@app.callback(
Output('display-type', 'options'),
[Input('period', 'value')],
)
def set_type_options(chosen_type):
ddk.Block(children=[
ddk.DataCard(id="dc1", width=25, label="Dividend Yield", value="-"),
ddk.DataCard(id="dc2", width=25, label="Peg Ratio", value="-"),
ddk.DataCard(id="dc3", width=25, label="Beta", value="%"),
ddk.DataCard(id="dc4", width=25, label="Country", value="-"),
]),
ddk.Block(children=[
ddk.Card(rounded=True,
children=[
ddk.Graph(
id="graph",
figure={
"data": [
go.Scatter(x=iex.get_prices(
"AAPL", "2015-01-01", "2016-01-01").index,
y=iex.get_prices(
"AAPL", "2015-01-01",
"2016-01-01")["Adj Close"])
],
"layout":
go.Layout(xaxis={'showgrid': False},
yaxis={'showgrid': False})
})
])
])
])
@app.callback([
Output("graph", "figure"),
Output("dc4", "value"),
Output("dc3", "value"),
var_list.append({'label': var, 'value': var})
vars[set] = var_list
external_stylesheets = ['https://codepen.io./chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__)
app.layout = html.Div([
#Baro
html.Div([
html.Label(['Barometric Pressure']),
ddk.Card(width=100,
children=[ddk.Graph(id='baro-graphic',
figure = px.scatter(data['baro'],
y=data['baro']['BaroPres'],
x=data['baro']['time']
)
)],
)
]),
html.Div([
#html.H3('Column 1'),
html.Label(['Scientific Data']),
dcc.Dropdown(
id="select_sci",
options=vars['sci'],
value=vars['sci'][0]['value']
#multi=True
),
ddk.Card(width=100,
children=[ddk.Graph(id='sci-graphic')],
])
]),
ddk.ControlCard(
width=25,
children=[
ddk.ControlItem(children=[
dcc.Dropdown(id="dd2", options=time, value="15min")
])
]),
ddk.ControlCard(
width=25,
children=[
ddk.ControlItem(
children=[dcc.Input(id="Input_Value", value=5)])
]),
ddk.Card(children=[ddk.Graph(id="graph")])
])
@app.callback(Output("graph", "figure"), [
Input("dd1", "value"),
Input("dd2", "value"),
Input("Input_Value", "value")
])
def update_graph(dd1, dd2, Input_Value):
r = requests.get(
"https://financialmodelingprep.com/api/v3/historical-chart/%s/%s" %
(dd2, dd1))
df = pd.DataFrame.from_dict(r.json())
df["date"] = pd.to_datetime(df["date"])
df["SMA"] = df["close"].rolling(int(Input_Value)).mean()
children=[ddk.ControlItem(children=[dcc.Dropdown(id="dropdown", options=iex.companies, value="AAPL"),
ddk.ControlItem(width=50,children=[dcc.DatePickerRange(id="datepicker",start_date="2015-01-01",end_date="2016-01-01",display_format="YYYY-MM-DD")])])],
)),
ddk.Block(children=[ddk.DataCard(id="dc1", width=25, label="Dividend Yield", value="-"),
ddk.DataCard(id="dc2", width=25, label="Peg Ratio", value="-"),
ddk.DataCard(id="dc3", width=25, label="Beta", value="%"),
ddk.DataCard(id="dc4", width=25, label="Country", value="-"),
]),
ddk.Block(children=[ddk.Card(rounded=True, children=[ddk.Graph(id="graph", figure={
"data": [go.Scatter(x=iex.get_prices("AAPL","2015-01-01","2016-01-01").index, y=iex.get_prices("AAPL","2015-01-01","2016-01-01")["Adj Close"])], "layout": go.Layout(xaxis={
'showgrid': False
},
yaxis={
'showgrid': False
})
}
)])])
])
@app.callback([Output("graph", "figure"),Output("dc4", "value"),
Output("dc3", "value"),
Output("dc2", "value"),
Output("dc1", "value")], [Input("dropdown", "value"),Input("datepicker","start_date"),Input("datepicker","end_date")])
def update_card1(value,start_date,end_date):
profile = iex.get_company(value)
def Graphs():
df_streamtube = ddk.datasets.df_streamtube()
df_choropleth = ddk.datasets.df_choropleth()
df_scattergeo = ddk.datasets.df_scattergeo()
df_iris = ddk.datasets.df_iris()
x = [1, 2, 3]
labels = ['Montreal', 'Tofu Bowl', 'Tropical Beaches']
labels_long = [
'Montreal', 'New York City', 'Tokyo',
'Cincinatti', 'Miami', 'London', 'Vancouver'
]
values_long = [1, 2, 3, 1, 5, 6, 7]
y1 = [3, 1, 2]
y2 = [4, 10, 4]
y3 = [5, 2, 3]
y4 = [9, 3, 8]
y5 = [10, 5, 12]
y6 = [11, 8, 10]
y7 = [1, 2, 1]
y8 = [5, 3, 1]
z = [5, 3, 1]
matrix = [
[1, 2, 3],
[4, 1, 2],
[1, 3, 4]
]
open = [33.0, 33.3, 33.5, 33.0, 34.1]
high = [33.1, 33.3, 33.6, 33.2, 34.8]
low = [32.7, 32.7, 32.8, 32.6, 32.8]
close = [33.0, 32.9, 33.3, 33.1, 33.1]
dates = [dt(year=2013, month=10, day=10),
dt(year=2013, month=11, day=10),
dt(year=2013, month=12, day=10),
dt(year=2014, month=1, day=10),
dt(year=2014, month=2, day=10)]
r = [0.5, 1, 2, 2.5, 3, 4]
theta = [35, 70, 120, 155, 205, 240]
datas = [
[
{'type': 'scatter', 'x': x, 'y': y1, 'mode': 'lines'},
{'type': 'scatter', 'x': x, 'y': y2, 'mode': 'lines'},
],
[
{'type': 'scatter', 'x': x, 'y': y1, 'mode': 'lines'},
{'type': 'scatter', 'x': x, 'y': y2, 'mode': 'lines'},
{'type': 'scatter', 'x': x, 'y': y3, 'mode': 'lines'},
{'type': 'scatter', 'x': x, 'y': y4, 'mode': 'lines'},
],
[
{'type': 'scatter', 'x': x, 'y': y1, 'mode': 'lines'},
{'type': 'scatter', 'x': x, 'y': y2, 'mode': 'lines'},
{'type': 'scatter', 'x': x, 'y': y3, 'mode': 'lines'},
{'type': 'scatter', 'x': x, 'y': y4, 'mode': 'lines'},
{'type': 'scatter', 'x': x, 'y': y5, 'mode': 'lines'},
{'type': 'scatter', 'x': x, 'y': y6, 'mode': 'lines'},
{'type': 'scatter', 'x': x, 'y': y7, 'mode': 'lines'},
{'type': 'scatter', 'x': x, 'y': y8, 'mode': 'lines'},
],
[
{'type': 'scatter', 'x': x, 'y': y1, 'mode': 'markers'},
{'type': 'scatter', 'x': x, 'y': y2, 'mode': 'markers'},
],
[
{'type': 'scatter', 'x': x, 'y': y1, 'mode': 'markers'},
{'type': 'scatter', 'x': x, 'y': y2, 'mode': 'markers'},
{'type': 'scatter', 'x': x, 'y': y3, 'mode': 'markers'},
{'type': 'scatter', 'x': x, 'y': y4, 'mode': 'markers'},
],
[
{'type': 'scatter', 'x': x, 'y': y1, 'mode': 'markers'},
{'type': 'scatter', 'x': x, 'y': y2, 'mode': 'markers'},
{'type': 'scatter', 'x': x, 'y': y3, 'mode': 'markers'},
{'type': 'scatter', 'x': x, 'y': y4, 'mode': 'markers'},
{'type': 'scatter', 'x': x, 'y': y5, 'mode': 'markers'},
{'type': 'scatter', 'x': x, 'y': y6, 'mode': 'markers'},
{'type': 'scatter', 'x': x, 'y': y7, 'mode': 'markers'},
{'type': 'scatter', 'x': x, 'y': y8, 'mode': 'markers'},
],
[
{
'type': 'scatter', 'x': x, 'y': y1, 'marker': {'color': y2},
'mode': 'markers'
},
],
[
{'type': 'scatter', 'x': x, 'y': y1, 'mode': 'lines+markers'},
{'type': 'scatter', 'x': x, 'y': y2, 'mode': 'lines+markers'},
],
[
{'type': 'bar', 'x': labels, 'y': y1},
{'type': 'bar', 'x': labels, 'y': y2},
],
[
{'type': 'bar', 'x': labels, 'y': y1},
{'type': 'bar', 'x': labels, 'y': y2},
{'type': 'bar', 'x': labels, 'y': y3},
{'type': 'bar', 'x': labels, 'y': y4},
],
[
{'type': 'bar', 'x': labels, 'y': y1},
{'type': 'bar', 'x': labels, 'y': y2},
{'type': 'bar', 'x': labels, 'y': y3},
{'type': 'bar', 'x': labels, 'y': y4},
{'type': 'bar', 'x': labels, 'y': y5},
{'type': 'bar', 'x': labels, 'y': y6},
{'type': 'bar', 'x': labels, 'y': y7},
{'type': 'bar', 'x': labels, 'y': y8},
],
[
{'type': 'scatter', 'x': x, 'y': y1, 'mode': 'lines', 'fill': 'tonexty'},
{'type': 'scatter', 'x': x, 'y': y2, 'mode': 'lines', 'fill': 'tonexty'},
],
[
{'type': 'heatmap', 'z': matrix}
],
[
{'type': 'contour', 'z': matrix}
],
[
{'type': 'histogram2d', 'x': x, 'y': y1}
],
[
{'type': 'histogram2dcontour', 'x': x, 'y': y1}
],
[
{'type': 'pie', 'labels': labels, 'values': y1}
],
[
{'type': 'pie', 'labels': labels_long, 'values': values_long}
],
[
{'type': 'box', 'y': y1},
{'type': 'box', 'y': y2}
],
[
{'type': 'box', 'y': y1, 'boxpoints': 'all'},
{'type': 'box', 'y': y2, 'boxpoints': 'all'}
],
[
{'type': 'violin', 'y': y1},
{'type': 'violin', 'y': y2}
],
[
{'type': 'violin', 'y': y1, 'points': 'all'},
{'type': 'violin', 'y': y2, 'points': 'all'}
],
[
{'type': 'histogram', 'y': y1}
],
[
{'type': 'scatter3d', 'x': x, 'y': y1, 'z': z, 'mode': 'markers'},
{'type': 'scatter3d', 'x': x, 'y': y2, 'z': z, 'mode': 'markers'}
],
[
{'type': 'scatter3d', 'x': x, 'y': y1, 'z': z, 'mode': 'lines'},
{'type': 'scatter3d', 'x': x, 'y': y2, 'z': z, 'mode': 'lines'}
],
[
{'type': 'scatter3d', 'x': x, 'y': y1, 'z': z, 'mode': 'markers+lines'},
{'type': 'scatter3d', 'x': x, 'y': y2, 'z': z, 'mode': 'markers+lines'}
],
[
{'type': 'surface', 'z': matrix}
],
[
{
'type': 'cone',
'x': [row[0] for row in cone_data],
'y': [row[1] for row in cone_data],
'z': [row[2] for row in cone_data],
'u': [row[3] for row in cone_data],
'v': [row[4] for row in cone_data],
'w': [row[5] for row in cone_data],
}
],
[
{
'type': 'streamtube',
'x': df_streamtube['x'],
'y': df_streamtube['y'],
'z': df_streamtube['z'],
'u': df_streamtube['u'],
'v': df_streamtube['v'],
'w': df_streamtube['w'],
'sizeref': 0.5
}
],
[
{
'type': 'choropleth',
'z': df_choropleth['GDP (BILLIONS)'],
'locations': df_choropleth['CODE'],
'text': df_choropleth['COUNTRY']
}
],
[
{
'type': 'scattergeo',
'lon': df_scattergeo['long'],
'lat': df_scattergeo['lat'],
'mode': 'markers',
}
],
[
{
'type': 'scattermapbox',
'lon': df_scattergeo['long'],
'lat': df_scattergeo['lat'],
'mode': 'markers',
}
],
[
{
'type': 'candlestick',
'open': open,
'high': high,
'low': low,
'close': close
}
],
[
{
'type': 'ohlc',
'open': open,
'high': high,
'low': low,
'close': close
}
],
[
{'type': 'scatterternary', 'a': x, 'b': y1, 'c': y2, 'mode': 'markers'},
],
[
{'type': 'scatterternary', 'a': x, 'b': y1, 'c': y2, 'mode': 'lines'},
],
[
{'type': 'scatterpolar', 'r': r, 'theta': theta, 'mode': 'markers'},
],
[
{'type': 'scatterpolar', 'r': r, 'theta': theta, 'mode': 'lines'},
],
[
dict(
type='parcoords',
dimensions=list([
dict(range=[0,8],
constraintrange=[4,8],
label='Sepal Length', values=df_iris['sepal_length']),
dict(range=[0,8],
label='Sepal Width', values=df_iris['sepal_width']),
dict(range=[0,8],
label='Petal Length', values=df_iris['petal_length']),
dict(range=[0,8],
label='Petal Width', values=df_iris['petal_width'])
])
)
],
[
dict(
type='sankey',
node=dict(
label=["Nuclear", "Wind Energy", "Thermal", "Bio Conversion", "Airline Industry", "Losses"],
),
link=dict(
source=[0, 1, 0, 2, 3, 3],
target=[2, 3, 3, 4, 4, 5],
value=[8, 4, 2, 8, 4, 2]
)
)
],
[
{
'type': 'carpet',
'a': [4, 4, 4, 4.5, 4.5, 4.5, 5, 5, 5, 6, 6, 6],
'b': [1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3],
'y': [2, 3.5, 4, 3, 4.5, 5, 5.5, 6.5, 7.5, 8, 8.5, 10],
}
],
[
{
'type': 'contourcarpet',
'a': [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3],
'b': [4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6],
'z': [1, 1.96, 2.56, 3.0625, 4, 5.0625, 1, 7.5625, 9, 12.25, 15.21, 14.0625],
},
{
'type': 'carpet',
'a': [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3],
'b': [4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6],
'x': [2, 3, 4, 5, 2.2, 3.1, 4.1, 5.1, 1.5, 2.5, 3.5, 4.5],
'y': [1, 1.4, 1.6, 1.75, 2, 2.5, 2.7, 2.75, 3, 3.5, 3.7, 3.75],
}
]
]
return html.Div([
ddk.Card(width=25, children=[
ddk.CardHeader(title=data[0]['type']),
ddk.Graph(
id='graph-{}'.format(i),
figure={
'data': data,
'layout': {
'title': 'Hello World',
}
}
)
])
for (i, data) in enumerate(datas)
])
import dash
import dash_design_kit as ddk
import plotly.express as px
import pandas as pd
app = dash.Dash(__name__)
server = app.server # expose server variable for Procfile
df = pd.DataFrame({
"Fruit": ["Apples", "Oranges", "Bananas", "Apples", "Oranges", "Bananas"],
"Amount": [4, 1, 2, 2, 4, 5],
"City": ["SF", "SF", "SF", "Montreal", "Montreal", "Montreal"]
})
fig = px.bar(df, x="Fruit", y="Amount", color="City", barmode="group")
app.layout = ddk.App(
show_editor=True,
children=[
ddk.Header([ddk.Title('Hello Dash')]),
ddk.Card(children=[
ddk.CardHeader(
title='Dash: A Web application framework for Python.'),
ddk.Graph(figure=fig)
])
])
