dcc.Graph(id='timeseries', config={'displayModeBar': False}, animate=True) ]), html.Div(className='eight columns div-for-charts bg-grey', children=[ dcc.Graph(id='timeseries1', config={'displayModeBar': False}, animate=True) ]) ], ) ]) @app.callback(Output('timeseries', 'figure'), [Input('lovbruddstype', 'value'), Input('years', 'value')]) def update_graph(lovbruddstyper, years): trace1 = [] df_sub = df1 for lovbrudd in lovbruddstyper: trace1.append( go.Line( x=df_sub[df_sub['lovbruddstype'] == lovbrudd] ['år'].sort_values(axis=0, ascending=True).unique(), y=df_sub[df_sub['lovbruddstype'] == lovbrudd]['value'], mode='x', #opacity=0.9, name='lovbruddstype', textposition='bottom center'))
'font-family': 'Sans-Serif', 'color': "rgba(117, 117, 117, 0.95)" }), dcc.Tabs(id="tabs-example", value='tab-1-example', children=[ dcc.Tab(label='Overview', value='tab-1-example'), dcc.Tab(label='In/Out', value='tab-2-example'), dcc.Tab(label='Test', value='tab-3-example'), ]), dbc.Row(html.H1('')), html.Div(id='tabs-content-example') ]) @app.callback(Output('tabs-content-example', 'children'), [Input('tabs-example', 'value')]) def render_content(tab): if tab == 'tab-1-example': return html.Div([ dbc.Row([ dbc.Col([ html.H1('Overall balance'), simple_data_table.visual_simple_data_table(overview), ]), dbc.Col([ html.H1('Balance over time'), dbc.Row( multi_line_chart.visual_dropdown( 'my-dropdown',
'color': colors['text'] } ), html.Div(children='What happens when you self-teach python and work in marketing', style={ 'textAlign': 'center', 'color': colors['text'] }), dcc.Graph(id='main_graph'), dcc.Interval( id="query_update",interval=6000,n_intervals=0), ]) @app.callback(Output('main_graph', 'figure'),Input('query_update', 'n_intervals')) def update_figure(n): df = read_and_plot() fig = px.bar(df, x='Word', y='Frequency') fig.update_layout( font_family="Courier New", font_color="black", title_font_family="Times New Roman", title_font_color="black") fig.update_traces(marker_color='MediumPurple') return fig if __name__ == '__main__': app.run_server(debug=True, host='0.0.0.0',port=8080)
app.layout = dbc.Container([ dcc.Store(id="store"), dcc.Interval(id="interval", interval=500), html.H2("Redis / RQ demo", className="display-4"), html.P(EXPLAINER), html.Hr(), dbc.Textarea(id="text", className="mb-3"), dbc.Button("Upper case", id="button", color="primary", className="mb-3"), dbc.Collapse(dbc.Progress(id="progress", className="mb-3"), id="collapse"), html.P(id="output"), ]) @app.callback( Output("store", "data"), [Input("button", "n_clicks")], [State("text", "value")], ) def submit(n_clicks, text): if n_clicks: id_ = uuid.uuid4() # queue the task queue.enqueue(slow_loop, text, id_, job_id=str(id_)) # record queuing in the database result = Result(id=id_, queued=datetime.datetime.now()) db.session.add(result) db.session.commit()
'find the most relevant movies and/or tv series that will absolutely delight you! So, lets go!!', style={ 'textAlign': 'center', 'color': colors['text'] } ), dcc.Tabs(id="tabs-example", value='tab-1', children=[ dcc.Tab(label='Personal Choice Based Recommendation', value='tab-1'), dcc.Tab(label='Genre/Time Based Recommendation', value='tab-2'), ]), html.Div(id='tabs-content-display') ]) @app.callback(Output('tabs-content-display', 'children'), [Input('tabs-example', 'value')]) def render_content(tab): if tab == 'tab-1': return tab1.tab1_layout elif tab == 'tab-2': return tab2.tab2_layout # Tab 1 callback @app.callback(Output('my-table', 'children'), [Input('movie_list_input', 'value')]) def update_table(selected_movie): movie_list = nmr.userchoice_based_movie_recommendation(selected_movie) return nmr.generate_table(movie_list)
html.Br(), # Choropleth map html.Div([dcc.Graph(id="att_level_map", figure={})], style={ "padding-left": "25%", "padding-right": "25%" }) ]) #------------------------------------------------ # Connect Plotly graphs with Dash components @app.callback([ Output(component_id="output_container", component_property="children"), Output(component_id="att_level_map", component_property="figure") ], [Input(component_id="dt_pick_single", component_property="date")]) def update_graph(date_picked): print(date_picked) print(type(date_picked)) # Print Date selected container = f"Date selected: {date_picked[:10]}" # Because date_picked is of type str, need to conver to int date_picked = int(date_picked[8:10]) # FIGURE # center of map lat = 42.355753 lng = -83.076760
fluid=True, dark=True, color="primary") ], width=12) ]), dcc.Location(id="url", refresh=False, pathname="/apps/welcome"), html.Div(id='page-content', children=[]), dbc.Row( dbc.Col( html.Div( "(c) CAD Group 6 - Keele University - Built by Dash on Flask", style={"text-align": "center"}))) ]) @app.callback(Output('page-content', 'children'), [Input('url', 'pathname')]) def display_page(pathname): if pathname == '/apps/seminars': return seminars.layout if pathname == '/apps/exhibitions': return exhibitions.layout if pathname == '/apps/discussions': return discussions.layout else: return welcome.layout if __name__ == '__main__': app.run_server(debug=False)
from dash.dependencies import Input, Output, State import re # df = pd.read_csv( # 'https://gist.githubusercontent.com/chriddyp/' + # '5d1ea79569ed194d432e56108a04d188/raw/' + # 'a9f9e8076b837d541398e999dcbac2b2826a81f8/'+ # 'gdp-life-exp-2007.csv') external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css'] app = dash.Dash(__name__, external_stylesheets=external_stylesheets) app.layout=html.Div([ html.Div([html.H4(children='电影数据散点图')], style={'padding-bottom': '20px'}), html.Div(id='scatter'), ]) @app.callback(Output('scatter','children'), ) def update_output_scatter_marker(Input): client = pymongo.MongoClient('mongodb://127.0.0.1:27017/') db = client.douban collection = db.detail pattern = re.compile('20') result = collection.find({'release_time': pattern}) data_initial = pd.DataFrame(list(result)) #X轴 release_date = data_initial['release_time'] release_date_list = [] for i in release_date: release_date_list.append(i) scatter_x = pd.Series(data=release_date_list) #Y轴
html.Div([ dcc.Dropdown( id='yaxis-column', options=[{'label': i, 'value': i} for i in available_indicators], value='RH' ), ], style={'width': '48%', 'float': 'right', 'display': 'inline-block'}) ]), dcc.Graph(id='indicator-graphic'), ]) @app.callback( Output('indicator-graphic', 'figure'), [Input('xaxis-column', 'value'), Input('yaxis-column', 'value'),]) def update_graph(xaxis_column_name, yaxis_column_name): fig = px.scatter(x=df[xaxis_column_name], y=df[yaxis_column_name], color=df['PM High']) fig.update_layout( margin={'l': 40, 'b': 40, 't': 10, 'r': 0}, hovermode='closest') fig.update_xaxes(title=labels[xaxis_column_name]) fig.update_yaxes(title=labels[yaxis_column_name]) return fig
{ 'label': 'No', 'value': 0 }, ], value=0, labelStyle={ 'display': 'inline-block', 'fontSize': 24 })), ]) ]) @app.callback( Output('feature-graphic', 'figure'), [Input('mu', 'value'), Input('sd', 'value'), Input('z', 'value')]) def update_graph(mu, sd, z): x = np.linspace(mu - (4 * sd), mu + (4 * sd), 1001) y = [norm.pdf(i, mu, sd) for i in x] zx = [ mu - (3 * sd), mu - (2 * sd), mu - sd, mu + sd, mu + (2 * sd), mu + (3 * sd) ] zy = [norm.pdf(i, mu, sd) for i in zx] trace0 = go.Scatter(x=x, y=y, mode='lines', hoverinfo='none') trace1 = go.Bar(x=zx, y=zy, text=['Z=-3', 'Z=-2', 'Z=-1', 'Z=1', 'Z=2', 'Z=3'],
value='True', ) ], style={'display': 'none'}) ]) ]) ]) # App Layout app.layout = html.Div(children=[side_bar(), html.Div(id='layout')]) # CALLBACKS @app.callback([ Output("fighter-a", "valid"), Output("fighter-a", "invalid"), Output("fighter-b", "valid"), Output("fighter-b", "invalid"), Output("submit", "disabled") ], [Input("fighter-a", "value"), Input("fighter-b", "value")], [ State("fighter-a", "valid"), State("fighter-b", "valid"), State("fighter-a", "invalid"), State("fighter-b", "invalid"), State("submit", "disabled") ], prevent_initial_call=True) def check_name(a_name, b_name, a_curr_val, b_curr_val, a_curr_inv, b_curr_inv, b_dis):
config={ 'displayModeBar': False, 'scrollZoom': True }, style={ 'padding-bottom': '2px', 'padding-left': '2px', 'height': '90vh' }) ]), ]), ]) #Callback @app.callback(Output('graph', 'figure'), [ Input('boro_name', 'value'), Input('cuisine_name', 'value'), Input('grade_name', 'value') ]) def update_figure(boro_name, cuisine_name, grade_name): dff = df[(df['BORO'].isin(boro_name)) & (df['CUISINE'].isin(cuisine_name)) & (df['GRADE'].isin(grade_name))] #create figure locations = [ go.Scattermapbox( lon=dff['Longitude'], lat=dff['Latitude'], mode='markers', marker={'color': dff['Colors']},
md=12, lg=5, xl=5)), dbc.Row( dbc.Col(html.H2("Patient Count", className='text-center text-primary mb-4'), width=12)), dbc.Row( dbc.Card( dbc.CardImg( src= "https://raw.githubusercontent.com/AkankshKM/CapstoneImage/main/Prophet.png" ))) ]) @app.callback(Output(component_id='my-output', component_property='children'), Input(component_id='time', component_property='value'), Input(component_id='day', component_property='value'), Input(component_id='duration', component_property='value'), Input(component_id='esi', component_property='value'), Input(component_id='patientcount', component_property='value')) def update_output_div(time, day, duration, esi, patientcount): obj = Model() result = obj.test_model(time, day, duration, esi, patientcount) return 'Output: {}'.format(str(result)) if __name__ == '__main__': # model = joblib.load("./model.pkl") app.run_server(debug=True)
]) else: return html.I('Oura Connected!') def generate_oura_auth(): return [ html.Div(id='authorize-oura-container', className='twelve columns maincontainer', children=[ html.H4('Oura Connection'), html.Div(id='oura-auth', children=[test_oura_connection()] ), ])] # Callback for authorizing oura tokens @dash_app.callback(Output('oura-token-refresh', 'children'), [Input('url', 'search')], [State('url', 'pathname')]) def update_tokens(token, pathname): if 'oura' in pathname: if token: auth_code = re.findall('=(?<=\=)(.*?)(?=\&)', token)[0] auth_client.fetch_access_token(auth_code) save_oura_token(auth_client.session.token) # Main Dashboard Generation Callback @dash_app.callback( Output('oura-auth-layout', 'children'), [Input('oura-auth-canvas', 'children')] )
app.layout = html.Div([ dcc.Graph(id='graph-with-slider'), dcc.Slider( id='year-slider', min=df['year'].min(), max=df['year'].max(), value=df['year'].min(), marks={str(year): str(year) for year in df['year'].unique()}, step=None ) ]) @app.callback( Output('graph-with-slider', 'figure'), [Input('year-slider', 'value')]) def update_figure(selected_year): filtered_df = df[df.year == selected_year] traces = [] for i in filtered_df.continent.unique(): df_by_continent = filtered_df[filtered_df['continent'] == i] traces.append(dict( x=df_by_continent['gdpPercap'], y=df_by_continent['lifeExp'], text=df_by_continent['country'], mode='markers', opacity=0.7, marker={ 'size': 15, 'line': {'width': 0.5, 'color': 'white'}
), html.Br(), html.Div(id="updateSuccess"), ], md=6, ), ]), ], className="jumbotron", id="pageContent", ), ]) #### Affiche le nom de l'utilisateur connecté @app.callback(Output("username", "children"), [Input("pageContent", "children")]) def currentUserName(pageContent): try: username = current_user.username return username except AttributeError: return "" #### Affiche l'adresse mail de l'utilisateur connecté @app.callback(Output("email", "children"), [Input("pageContent", "children")]) def currentUserEmail(pageContent): try: email = current_user.email return email
return html.Div( [ html.H1("Metaswitch Tinder", className="text-center"), html.Br(), *is_signed_in_fields, html.Br(), mentee_request.layout(), html.Div(id="dummy-signin-{}".format(NAME), hidden=True), ], className="container", id="my-div", ) @app.callback( Output("my-div".format(NAME), "children"), [], [], [Event(mentee_request.submit_button, "click")], ) def submit_mentee_information(): log.debug("%s - %a clicked", NAME, mentee_request.submit_button) session.set_post_login_redirect( href(__name__, mentee_request.submit_request)) @app.callback( Output("dummy-signin-{}".format(NAME), "children"), [], [], [Event("signin-{}".format(NAME), "click")],
def execute(self): """Execute the link. :returns: status code of execution :rtype: StatusCode """ settings = process_manager.service(ConfigObject) ds = process_manager.service(DataStore) # --- your algorithm code goes here self.logger.debug('Now executing link: {link}.', link=self.name) app = dash.Dash( __name__, assets_folder=self.assets_folder, ) figure_childs = du.figure_grid(len(self.figures), self.figures, layout_kwargs=self.layout_kwargs) app.layout = html.Div([ html.Div([ du.row([ du.column([ html.H1(self.app_title), *self.controls, html.H2('Filter by:'), *self.filter_controls ], className="two columns"), du.column(figure_childs, className='ten columns'), ]) ]) ]) # Make the callbacks -- This needs to be done manually for each control! # FIGURE 1 @app.callback(Output('fig_0', 'figure'), [ Input('dropdown_0', 'value'), Input('slider_0', 'value'), Input('filter_dropdown', 'value') ]) def update_fig1(col, bins, filter): return du.make_histogram(ds[self.read_key], col, bins, filter, self.layout_kwargs) # FIGURE 2 @app.callback(Output('fig_1', 'figure'), [ Input('dropdown_1', 'value'), Input('slider_1', 'value'), Input('filter_dropdown', 'value') ]) def update_fig2(col, bins, filter): return du.make_histogram(ds[self.read_key], col, bins, filter, self.layout_kwargs) # FIGURE 3 @app.callback(Output('fig_2', 'figure'), [ Input('dropdown_2', 'value'), Input('dropdown_3', 'value'), Input('filter_dropdown', 'value') ]) def update_fig3(x, y, filter): return du.make_scatter(ds[self.read_key], x, y, filter, self.layout_kwargs) # save app in datastore ds[self.store_key] = app return StatusCode.Success
]), html.Div([ html.Span('The last click occurred at: '), html.Span(id='app1-output2', children=None), ]) ''' ]) ]) # Modifies the 'children' property of the element with ID 'app1-output' # The 'children' property is whatever is stored within a HTML tag: <div>children go here</div> # Children can be a list of elements or a single element # @app.callback( Output('app1-output', 'children'), [Input('app1-button', 'n_clicks')]) ''' @app.callback( [ Output('app1-output', 'children'), Output('app1-output2', 'children'), ], [ Input('app1-button', 'n_clicks') ]) def update_click_count(n_clicks): if n_clicks == 0: timestamp = 'never' else: timestamp = datetime.today().strftime('%Y-%m-%d %H:%M:%S') return n_clicks, timestamp
'width': '48%', 'float': 'right', 'display': 'inline-block' }) ]), dcc.Graph(id='indicator-graphic'), html.Div([ dcc.Markdown( "Are stewards (steward activity measured by the ‘steward’ variable) having an impact on the health of trees? " ), dcc.Graph(id='ind-graph') ]) ]) @app.callback(Output('indicator-graphic', 'figure'), [Input('xaxis-column', 'value'), Input('yaxis-column', 'value')]) def update_graph(xaxis_column_name, yaxis_column_name): dff = df[df['boroname'] == xaxis_column_name] dff = df[df['spc_common'] == yaxis_column_name] traces = [] for i in dff.health.unique(): df_h = dff[dff['health'] == i] traces.append( go.Bar( x=df_h[df_h['spc_common'] == yaxis_column_name]['health'], y=df_h[df_h['boroname'] == xaxis_column_name]['percentage'], text=df_h[df_h['spc_common'] == yaxis_column_name]['health'], name=i))
'width': '100%', 'height': '60px', 'lineHeight': '60px', 'borderWidth': '1px', 'borderStyle': 'dashed', 'borderRadius': '5px', 'textAlign': 'center', 'margin': '10px' }, multiple=False), html.Br(), html.Div(id='output-data-upload'), pp_graph ]) @app.callback(Output('output-data-upload', 'children'), [ Input('upload-data', 'contents'), Input('upload-data', 'filename') ]) def update_table(contents, filename): table = html.Div() if contents: df = parse_data(contents, filename) des_df = df.describe(include="all").reset_index() percent_missing = (df.isnull().sum() * 100 / len(df)) miss_df = pd.DataFrame({'Column_Name': df.columns,'Percent_Missing': percent_missing}).reset_index(drop = True) table = html.Div([ html.H4("Data Statistics for the Uploaded File Name: {}".format(filename)), html.H6('Number of Columns: {} and Number of Rows: {}'.format(df.shape[0], df.shape[1])),
"justify-content": "center", "margi-top": 10, }, ), html.Div(id="clustering-plot", children=[clustering_scatter]), ], ), ]) ########################################################################################## # CALLBACKS ########################################################################################## @app.callback( Output("correlation-scatter", "figure"), [ Input("correlation-x-axis-dropdown", "value"), Input("correlation-y-axis-dropdown", "value"), ], ) def update_correlation_scatter_figure( x_axis_dropdown_value: str, y_axis_dropdown_value: str) -> typing.Dict: """ Callback aimed to changes the Iris scatter content by selecting x and y axis data sets :param x_axis_dropdown_value: the name of the data that will be displayed in the x axis :param y_axis_dropdown_value: the name of the data that will be displayed in the y axis :return: the data and the layout content
app = dash.Dash(__name__, external_stylesheets=external_stylesheets) app.layout = html.Div( html.Div([ html.H4("TERRA Satellite Live Feed"), html.Div(id="live-update-text"), dcc.Graph(id="live-update-graph"), dcc.Interval( id="interval-component", interval=1 * 1000, # in milliseconds n_intervals=0, ), ])) @app.callback(Output("live-update-text", "children"), [Input("interval-component", "n_intervals")]) def update_metrics(n): lon, lat, alt = satellite.get_lonlatalt(datetime.datetime.now()) style = {"padding": "5px", "fontSize": "16px"} return [ html.Span("Longitude: {0:.2f}".format(lon), style=style), html.Span("Latitude: {0:.2f}".format(lat), style=style), html.Span("Altitude: {0:0.2f}".format(alt), style=style), ] # Multiple components can update everytime interval gets fired. @app.callback(Output("live-update-graph", "figure"), [Input("interval-component", "n_intervals")]) def update_graph_live(n):
ceil_marks = list(range(500, len(route_df), 500)) + [len(route_df) - 1] slider_marks = {f: f'{f} to {c}' for f, c in zip(floor_marks, ceil_marks)} app.layout = html.Div(children=[ html.H1(children='Openflights data'), dcc.Graph(id='world-map-graph'), dcc.Slider(id='flights-slider', min=100, max=len(route_df), value=500, marks=slider_marks, step=None) ]) @app.callback(Output('world-map-graph', 'figure'), [Input('flights-slider', 'value')]) def update_world_map(num_routes): fig = go.Figure() # plot the locations fig.add_trace( go.Scattergeo(lon=loc_df['longitude'], lat=loc_df['latitude'], hoverinfo='text', text=loc_df['name'], mode='markers', marker=dict(size=2, color='rgb(255, 0, 0)'))) # plot the flights r_df = route_df.iloc[num_routes:num_routes + 500]
plot_bgcolor="#F4F4F8", autofill=True, margin=dict(t=75, r=50, b=100, l=50), ), ), ), ], ), ], ), ], ) @app.callback( Output("county-choropleth", "figure"), [Input("year-select", "value")], [State("county-choropleth", "figure")], ) def display_map(year, figure): cm = dict(zip(BINS, DEFAULT_COLORSCALE)) data = [ dict( lat=df_lat_lon["Latitude "], lon=df_lat_lon["Longitude"], text=df_lat_lon["Hover"], type="scattermapbox", hoverinfo="text", marker=dict(size=5, color="white", opacity=0), )
]), html.Br(), ]), ]), ], style={'background-color': '#CCD7EA'}, ), ]), ]), html.Br(), ], className='ccontent') @app.callback( Output("sma_collapse", "is_open"), [Input("formula_sma", "n_clicks")], [State("sma_collapse", "is_open")], ) def toggle_collapse(n, is_open): ''' this function is used to open collapse bar ''' if n: return not is_open return is_open @app.callback( Output("rsi_collapse", "is_open"), [Input("formula_rsi", "n_clicks")],
html.P([ html.Label("Choose a county"), dcc.Dropdown(id = 'opt_c')#, options = opt_state, value = 'The Whole State') ], style = {'width': '400px', 'fontSize' : '20px', 'padding-left' : '100px', 'display': 'inline-block'}) ]) ## Step 5. Add callback functions @app.callback( Output('opt_c', 'options'), [Input('opt_s', 'value')]) def set_state_options(selected_state): return [{'label': i, 'value': i} for i in Dict[selected_state]] @app.callback( Output('opt_c', 'value'), [Input('opt_c', 'options')]) def set_county_value(available_options): return available_options[0]['value'] @app.callback(Output('google_fig', 'figure'), [Input('slider', 'value'), Input('opt_s', 'value')]) def update_figure(input2, selected_state):
min = min_week, max = max_week, value = [max_week-4,max_week], step=1, marks = {ind:str(ind) for ind in range(min_week, max_week,4)}) checklist_flagtypes = dcc.Checklist( id = 'cl_flagtypes', value=['disinformation', 'fakenews', 'unreliable', 'propaganda'], options= [{'label':t,'value':t} for t in flagtypes] ) radio_coronatopic = dcc.RadioItems( id = 'rd_coronatopic', value="yes", options= [{'label': 'yes', 'value':"yes"}, {'label': 'no','value':"no"}] ) @app.callback( Output(component_id='show_dates', component_property='children'), [Input(component_id='sl_week', component_property='value')] ) def update_output_div1(input_value): return('%s -> %s' % (week_day_df.loc[input_value[0]].loc['min'], week_day_df.loc[input_value[1]].loc['max'])) ### LAYOUT app.layout = \ html.Div( children=[ ### hidden html.Div(id='filtered_json_week', style={'display': 'none'}),
app.scripts.config.serve_locally = True year_options = [] for year in df['year'].unique(): year_options.append({'label': str(year), 'value': year}) app.layout = html.Div([ dcc.Graph(id='graph'), dcc.Dropdown(id='year-picker', options=year_options, value=df['year'].min()) ]) @app.callback(Output('graph', 'figure'), [Input('year-picker', 'value')]) def update_figure(selected_year): filtered_df = df[df['year'] == selected_year] traces = [] for continent_name in filtered_df['continent'].unique(): df_by_continent = filtered_df[filtered_df['continent'] == continent_name] traces.append( go.Scatter(x=df_by_continent['gdpPercap'], y=df_by_continent['lifeExp'], mode='markers', opacity=0.7, marker={'size': 15},
, # Numeric input for the trade amount html.Div(dcc.input(id = "trade_amount", type = 'numeric')) , # Submit button for the trade html.Div(dcc.input(id = "submit", type = 'text')) ]) # Callback for what to do when submit-button is pressed @app.callback( [ ( Output(component_id='my-output', component_property='children'), Input(component_id='my-input', component_property='figure') ], ) ) def update_candlestick_graph(n_clicks, value): # n_clicks doesn't get used, we only include it for the dependency. # Now we're going to save the value of currency-input as a text file. currency_pair = open("value.txt", "w+"), # Wait until ibkr_app runs the query and saves the historical prices csv while(ibkr.app.py): # Read in the historical prices