Develop Reference

Dropdown and Datatable in dash

I have the datepicker component which filters the datatable (top 10 songs on that specific date).Also I would like to have the bar chart which shows the total number of streamed songs of that top 10 songs (10 bars accordingly) preferably with dropdown core component with the options of the titles of songs that where filtered based on the date (the ones that datatable shows). with the below codem, the dropdown component shows all unique song titles thate are in the df but as I already said I want only the ones which will be picked after filtering on date.
Viz: https://imgur.com/a/i2FY83V
import dash
import dash_core_components as dcc
import dash_html_components as html
import dash_table
from dash.dependencies import Output, Input
import plotly.express as px
import dash_bootstrap_components as dbc
from datetime import date
import pandas as pd
df = pd.read_csv('bel.csv')
app = dash.Dash(__name__, external_stylesheets=[dbc.themes.LITERA],
meta_tags=[{'name' : 'viewport',
'content': 'width=device-width, initial-scale=1.0' }]
)
# layout
app.layout = dbc.Container([
dbc.Row([
dbc.Col([
html.H1('Top songs in Belgium',className='text-center text-primary,mb-4'),
html.P ('Analyze the Top streamed songs in a month of between March & April',
className='text-center'),
], width= 12)
]),
dbc.Row([
dbc.Col([
dcc.DatePickerSingle(
id = 'my-date-picker-single',
min_date_allowed=date(2022,3,1),
max_date_allowed= date(2022,5,1),
initial_visible_month=date(2022,3,1),
date= date(2022,3,1)
),
dash_table.DataTable(
id ='datatable-interactivity',
columns=[
{"name": i, "id": i, "deletable": False, "selectable": True, "hideable": True}
if i == "iso_alpha3" or i == "year" or i == "id"
else {"name": i, "id": i, "deletable": False, "selectable": True}
for i in df.loc[0:4,['Rank', 'Title']]
],
data =df.to_dict('records'),
editable= False,
style_as_list_view=True,
style_header={
'backgroundColor': 'white',
'fontWeight': 'bold',
},
style_data={
'whiteSpace': 'normal',
'height':'auto',
'backgroundColor': 'rgb(50, 50, 50)',
'color': 'white'},
),
], width=5),
dbc.Col([
dcc.Dropdown(id='my-dpdn', multi=True,
placeholder="Select a title",
options=[{'label': x, 'value': x}
for x in sorted(df['Title'].unique())]),
dcc.Graph(id='bar-fig', figure={}),
], width ={'size':5})
]),
dbc.Row([
]),
], fluid= True)
def date_string_to_date(date_string):
return pd.to_datetime(date_string, infer_datetime_format=True)
#app.callback(
dash.dependencies.Output('datatable-interactivity', 'data'),
dash.dependencies.Input('my-date-picker-single','date')
)
def update_data (date):
data = df.to_dict('records')
if date:
mask = (date_string_to_date(df['Chart Date']) == date_string_to_date(date))
data= df.loc[mask].head(10).to_dict('records')
return data
# -------------------------------------------------------------------------
if __name__ == '__main__':
app.run_server(debug=True)

Dash DataTable filter columns cannot be hidden

I'm using style_data_conditional to hide columns in a data table. Works!
But when adding
filter_actions='native'
the rows will be like
|c1|c2|c6|c7|
\filter\filter\filter\filter\filter\filter\filter\
(this row is longer than the table because the display:None isn't applied)
|1|2|6|7
Versions:
dash==1.13.4
dash-auth==1.3.2
dash-bootstrap-components==0.10.7
dash-core-components==1.10.1
dash-extensions==0.0.31
dash-html-components==1.0.3
dash-renderer==1.5.1
dash-table==4.8.1
Here is code to reproduce the DataTable
import dash_table
import dash
import dash_html_components as html
import pandas as pd
app= dash.Dash(__name__)
df=pd.DataFrame([
[1,2,3], [1,2,3],[1,2,3]
],
columns=['1','2','3'])
app.layout = html.Div([
dash_table.DataTable(
data=df.to_dict('records'),
columns=[ {"name":i,"id":i } for i in df.columns],
style_table={'padding-right':'2rem',
'padding-left':'2rem',
'padding-bottom':'1rem'
},
page_size=14,
row_selectable="single",
page_action='native', #front end
# sort_mode='single',
sort_action='native',
editable=True,
filter_action='native',
style_data_conditional=[{'if': {'column_id': '2',},
'display': 'None',},],
style_header_conditional=[{'if': {'column_id': '2',},
'display': 'None',},]
),
])
if __name__ == '__main__':
app.run_server()

How do I use Dash Loading with Dash Store?

I am writing a simple Dash page. I get data from external APIs etc. and put this in a dcc.Store. The Graphs then pull the data and plot in callbacks. I am trying to implement the dcc.Loading functionality as the pulling of the data can take some time. However I can't figure out how to trigger the Loading for the Graphs when the work is being done by Store.
Below is an example:
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
from dash.exceptions import PreventUpdate
import plotly.express as px
import pandas as pd
import time
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div(children=[
html.H1(children='Hello Dash'),
html.Div(children='''
Dash: A web application framework for Python.
'''),
dcc.Dropdown(
id='demo-dropdown',
options=[
{'label': 'New York City', 'value': 'NYC'},
{'label': 'Montreal', 'value': 'MTL'},
{'label': 'San Francisco', 'value': 'SF'}
],
value='NYC'
),
dcc.Loading(
id='loading01',
children=html.Div(id='loading-output')),
# Store certain values
dcc.Store(
id='session',
storage_type='session'),
])
#app.callback(Output('loading-output', 'children'),
[Input('session', 'modified_timestamp')],
[State('session', 'data')])
def loading_graph(ts, store):
if store is None:
raise PreventUpdate
if 'NYC' in store['value']:
v = 1
elif 'SF' in store['value']:
v=2
else:
v=3
return dcc.Graph(
id='example-graph',
figure={
'data': [
{'x': [1, 2, 3], 'y': [4*v, 1*v, 2*v], 'type': 'bar', 'name': 'SF'},
{'x': [1, 2, 3], 'y': [2, 4, 5], 'type': 'bar', 'name': u'Montréal'},
],
'layout': {
'title': 'Dash Data Visualization'
}
}
)
#app.callback(Output('session', 'data'),
[Input('demo-dropdown', 'value')],
[State('session', 'data')])
def storing(value, store):
store = store or {}
store['value'] = value
time.sleep(3)
return store
if __name__ == '__main__':
app.run_server(debug=True)
I guess I was hoping for the spinner to be present whilst Store was fetching things.
Thanks in advance for any help or pointers.

If you want to show a loader when the storing callback is called it also needs to have an output to a Loading components' children property.
You can't have duplicate callback outputs, so you could either combine the callbacks into a single callback. Then you could have a single spinner that is active for as long as the combined callback takes to execute.
Or you could have multiple Loading components: One for each callback function:
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
from dash.exceptions import PreventUpdate
import time
external_stylesheets = ["https://codepen.io/chriddyp/pen/bWLwgP.css"]
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div(
children=[
html.H1(children="Hello Dash"),
html.Div(
children="""
Dash: A web application framework for Python.
"""
),
dcc.Dropdown(
id="demo-dropdown",
options=[
{"label": "New York City", "value": "NYC"},
{"label": "Montreal", "value": "MTL"},
{"label": "San Francisco", "value": "SF"},
],
value="NYC",
),
dcc.Loading(id="loading01", children=html.Div(id="loading-output1")),
dcc.Loading(id="loading02", children=html.Div(id="loading-output2")),
# Store certain values
dcc.Store(id="session", storage_type="session"),
]
)
#app.callback(
Output("loading-output2", "children"),
Input("session", "modified_timestamp"),
State("session", "data"),
prevent_initial_call=True,
)
def loading_graph(ts, store):
if store is None:
raise PreventUpdate
if "NYC" in store["value"]:
v = 1
elif "SF" in store["value"]:
v = 2
else:
v = 3
time.sleep(2)
return dcc.Graph(
id="example-graph",
figure={
"data": [
{
"x": [1, 2, 3],
"y": [4 * v, 1 * v, 2 * v],
"type": "bar",
"name": "SF",
},
{"x": [1, 2, 3], "y": [2, 4, 5], "type": "bar", "name": u"Montréal"},
],
"layout": {"title": "Dash Data Visualization"},
},
)
#app.callback(
Output("session", "data"),
Output("loading-output1", "children"),
Input("demo-dropdown", "value"),
State("session", "data"),
)
def storing(value, store):
time.sleep(2)
store = store or {}
store["value"] = value
return store, ""
if __name__ == "__main__":
app.run_server(debug=True)

Plotly/Dash -- range filter resets on hoverData

I am trying capture mouse hover events using Dash. I capture the position of the mouse using hoverData.
The problem appears when I filter the time series using the range selector or the range slider. The plot correctly reduces to the selected time, but when I hover it with the mouse it resets to the main view (whole main series).
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import plotly.graph_objs as go
from dash.dependencies import Input, Output
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv")
app.layout = html.Div([
dcc.Graph(
id='stock-plot'
),
], className="container")
#app.callback(
Output('stock-plot', 'figure'),
[Input('stock-plot', 'hoverData')])
def drawStockPrice(hoverData):
traces = [go.Scatter(
x=df.Date,
y=df['AAPL.High'],
mode='lines',
opacity=0.7,
connectgaps=True),
]
return {'data': traces,
'layout': go.Layout(colorway=["#5E0DAC", '#FF4F00', '#375CB1', '#FF7400', '#FFF400', '#FF0056'],
height=600,
title=f"Closing prices",
xaxis={"title": "Date",
'rangeselector': {'buttons': list([{'count': 1, 'label': '1M',
'step': 'month',
'stepmode': 'backward'},
{'count': 6, 'label': '6M',
'step': 'month',
'stepmode': 'backward'},
{'step': 'all'}])},
'rangeslider': {'visible': True}, 'type': 'date'},
yaxis={"title": "Price (USD)"},
)}
if __name__ == '__main__':
app.run_server(debug=True)

I am sure there should be a better solution but this is what I got (Dash v1.6.0):
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import plotly.graph_objs as go
from dash.dependencies import Input, Output, State
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv")
layout = go.Layout( colorway=["#5E0DAC", '#FF4F00', '#375CB1', '#FF7400', '#FFF400', '#FF0056'],
height=600,
title=f"Closing prices",
xaxis={"title": "Date",
'rangeselector': {'buttons': list([{'count': 1, 'label': '1M',
'step': 'month',
'stepmode': 'backward'},
{'count': 6, 'label': '6M',
'step': 'month',
'stepmode': 'backward'},
{'step': 'all'}]
),
},
'rangeslider': {'visible': True},
'type': 'date',
},
yaxis={"title": "Price (USD)"},
)
traces = [go.Scatter( x=df.Date,
y=df['AAPL.High'],
mode='lines',
opacity=0.7,
connectgaps=True
)]
app.layout = html.Div([
dcc.Graph(
id='stock-plot',
figure={
'data': traces,
'layout': layout
}
),
], className="container")
#app.callback(
Output('stock-plot', 'figure'),
[Input('stock-plot', 'hoverData'),
Input('stock-plot', 'relayoutData')],
[State('stock-plot', 'figure')]
)
def drawStockPrice(hoverData, selected, figure):
data = figure['data']
layout = figure['layout']
if selected is not None and 'xaxis.range' in selected:
layout['xaxis']['range'] = selected['xaxis.range']
return {'data': data,
'layout': layout
}
if __name__ == '__main__':
app.run_server(debug=True)

How to use Callback to update Bar Graph in Dash

Since Dash is a fairly new framework for making interactive web-based graphs, there is not too many information that are specific or detailed for beginners. In my case I need to update a simple bar graph using a callback function.
The data does not render on the browser even though the server runs fine without prompting any errors.
Need help sorting out and understanding why data does not render.
import dash
from dash.dependencies import Output, Event
import dash_core_components as dcc
import dash_html_components as html
import plotly
import plotly.graph_objs as go
app = dash.Dash(__name__)
colors = {
'background': '#111111',
'background2': '#FF0',
'text': '#7FDBFF'
}
app.layout = html.Div( children = [
html.Div([
html.H5('ANNx'),
dcc.Graph(
id='cx1'
)
])
]
)
#app.callback(Output('cx1', 'figure'))
def update_figure( ):
return {
'data': [
{'x': ['APC'], 'y': [9], 'type': 'bar', 'name': 'APC'},
{'x': ['PDP'], 'y': [8], 'type': 'bar', 'name': 'PDP'},
],
'layout': {
'title': 'Basic Dash Example',
'plot_bgcolor': colors['background'],
'paper_bgcolor': colors['background']
}
}
if __name__ == '__main__':
app.run_server(debug=True)

You can use callback in a such way (I create dropdown menu for this):
import dash
from dash.dependencies import Output, Input
import dash_core_components as dcc
import dash_html_components as html
import plotly
import plotly.graph_objs as go
import pandas as pd
app = dash.Dash(__name__)
df = pd.DataFrame({'x': ['APC', 'PDP'], 'y': [9, 8]})
colors = {
'background': '#111111',
'background2': '#FF0',
'text': '#7FDBFF'
}
app.layout = html.Div(children=[
html.Div([
html.H5('ANNx'),
html.Div(
id='cx1'
),
dcc.Dropdown(id='cx2',
options=[{'label': 'APC', 'value': 'APC'},
{'label': 'PDP', 'value': 'PDP'},
{'label': 'Clear', 'value': None}
]
)
])])
#app.callback(Output('cx1', 'children'),
[Input('cx2', 'value')])
def update_figure(value):
if value is None:
dff = df
else:
dff = df.loc[df["x"] == value]
return html.Div(
dcc.Graph(
id='bar chart',
figure={
"data": [
{
"x": dff["x"],
"y": dff["y"],
"type": "bar",
"marker": {"color": "#0074D9"},
}
],
"layout": {
'title': 'Basic Dash Example',
"xaxis": {"title": "Authors"},
"yaxis": {"title": "Counts"},
'plot_bgcolor': colors['background'],
'paper_bgcolor': colors['background']
},
},
)
)
if __name__ == '__main__':
app.run_server(debug=True)

If you write output in your calback function then you need to provide input as well, it can be, slider, date picker or dropdown menu and etc. but in your case you dont need any input and output as your graph is not dynamic in this case. check here https://dash.plot.ly/getting-started-part-2
so in your case it is enough just to put id and figure into dcc.Graph component:
import dash
import dash_core_components as dcc
import dash_html_components as html
app = dash.Dash(__name__)
colors = {
'background': '#111111',
'background2': '#FF0',
'text': '#7FDBFF'
}
app.layout = html.Div( children = [
html.Div([
html.H5('ANNx'),
dcc.Graph(
id='cx1', figure={
'data': [
{'x': ['APC'], 'y': [9], 'type': 'bar', 'name': 'APC'},
{'x': ['PDP'], 'y': [8], 'type': 'bar', 'name': 'PDP'},
],
'layout': {
'title': 'Basic Dash Example',
'plot_bgcolor': colors['background'],
'paper_bgcolor': colors['background']
}}
)
])
]
)
if __name__ == '__main__':
app.run_server(debug=True)