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I'm pretty new to dash and trying to place two dropdowns side by side each other but they don't seem to work at all, instead they are below each other. I think I'm messing up in 'className' arrangement of HTML div's. The code is as follows:
app.layout = html.Div([
html.Div( [
html.H1("Web Application Dashboards with Dash", style={'text-align': 'center'}),
] ),
html.Div(
className = "row",children =[
html.Div(className='six columns', children=[
dcc.Dropdown(
id='dropdown_dataset',
options=[
{'label': 'diabetes', 'value': 'diabetes'},
{'label': 'Custom Data', 'value': 'custom'},
{'label': 'Linear Curve', 'value': 'linear'},
],
value='diabetes',
clearable=False,
searchable=False,
)])
,html.Div(className='six columns', children=[
dcc.Dropdown(
id='dropdown_dataset_2',
options=[
{'label': 'sinh', 'value': 'sinh'},
{'label': 'tanh', 'value': 'cosh'},
],
value='diabetes',[![enter image description here][1]][1]
clearable=False,
searchable=False,
)])
])
])
if __name__ == '__main__':
app.run_server(host='127.0.0.1',port = '5000',debug=False,use_reloader=False)
Can you point where I'm making the mistake and is there any documentation to refer for this ?
This will do it. I've added display='flex' to the div that contains both dropdowns, and set the width to 50% for the divs that contain only single dropdowns. You could certainly set those styles in your CSS file using the IDs or classnames instead of coding them inline like this.
html.Div(
className="row", children=[
html.Div(className='six columns', children=[
dcc.Dropdown(
id='dropdown_dataset',
options=[
{'label': 'diabetes', 'value': 'diabetes'},
{'label': 'Custom Data', 'value': 'custom'},
{'label': 'Linear Curve', 'value': 'linear'},
],
value='diabetes',
clearable=False,
searchable=False,
)], style=dict(width='50%'))
, html.Div(className='six columns', children=[
dcc.Dropdown(
id='dropdown_dataset_2',
options=[
{'label': 'sinh', 'value': 'sinh'},
{'label': 'tanh', 'value': 'cosh'},
],
value='diabetes', # [![enter image description here][1]][1]
clearable=False,
searchable=False,
)], style=dict(width='50%'))
], style=dict(display='flex'))
I am trying to download the data frame using the download button in-dash app but I am unable to put logic where I can put this in my call back. I am generating the data frame based on user selection and using Dash_table.DataTable.
here is the full code:
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
import dash_bootstrap_components as dbc
import datetime
import dash_table
from Dash_App.app import app
import pandas as pd
row1 = html.Div(
[
dbc.Row([
dbc.Col([
dbc.Input(id="ad_account_id",
type="text",
placeholder="Account ID",
style={'width': '150px'}),
]),
dbc.Col([
dbc.Input(id="app_id",
type="text",
placeholder="App ID",
style={'width': '150px'}),
]),
dbc.Col([
dbc.Input(id="access_token",
type="text",
style={'width': '150px'},
placeholder="Access Token")
]),
dbc.Col([
dbc.Input(id="app_secret",
type="text",
style={'width': '150px'},
placeholder="App Secret")
]),
dbc.Col([
dcc.Dropdown(
id='dimensions',
options=[{'label': i, 'value': i} for i in ['Campaign', 'Placement', 'Creative']],
multi=True,
style={'width': '150px'},
placeholder='Dimensions')
]),
dbc.Col([
dcc.Dropdown(
id='metrics',
options=[{'label': i, 'value': i} for i in ['Impressions', 'Clicks', 'Conversions']],
multi=True,
style={'width': '150px'},
placeholder='Metrics')
])
], align="center"),
], style={'margin-top': 20, 'margin-left': -100}
)
row2 = html.Div([
dbc.Row([
dbc.Col([
dcc.DatePickerSingle(
id='start-date',
placeholder="Start Date",
min_date_allowed=datetime.datetime.now().strftime('2018-01-01'),
max_date_allowed=datetime.datetime.today().date(),
display_format='YYYY-MM-DD',
style={'width': '150px', 'margin-left': 180}
),
], ),
dbc.Col([
# html.Br(),
dcc.DatePickerSingle(
id='end-date',
placeholder="End Date",
min_date_allowed=datetime.datetime.now().strftime('2018-01-01'),
max_date_allowed=datetime.datetime.today().date(),
display_format='YYYY-MM-DD',
style={'width': '150px', 'margin-left': 60}
)], align="center"),
])
])
row3 = html.Div([
dbc.Row([
dbc.Col([
html.Button(id='submit-button', type='submit', children='Submit', style={'width': '150px', 'margin-top': 5,
'margin-left': 370}),
], width={"order": "first"}),
dbc.Col([
html.Div(id='output_div'),
])
])
])
row4 = html.Div([
html.A(html.Button('Download Data', id='download-button'), id='download-link-facebook',
style={'width': '120px', 'margin-top': 10, 'margin-left': 345})
])
tab_1_layout = dbc.Container(children=[
row1,
html.Br(),
row2,
html.Br(),
row3,
row4
]
)
#app.callback(Output('output_div', 'children'),
[Input('submit-button', 'n_clicks')],
[State('ad_account_id', 'value'),
State('app_id', 'value'), State('access_token', 'value'),
State('app_secret', 'value'), State('dimensions', 'value'),
State('metrics', 'value'),
State('start-date', 'date'),
State('end-date', 'date'),
],
)
def update_output(clicks, ad_account_id, app_id, access_token, app_secret, dimensions, metrics, start_date, end_date):
if clicks is not None:
my_ad_account = ad_account_id
my_app_id = app_id
my_access_token = access_token
my_app_secret = app_secret
my_dimensions = dimensions
my_metrics = metrics
my_start_date = start_date
my_end_date = end_date
df = pd.read_csv('usa-agricultural-exports-2011.csv', encoding='ISO-8859-1')
new_df_col_list = my_dimensions + my_metrics
print(new_df_col_list)
dff = df[new_df_col_list]
return html.Div([
dash_table.DataTable(
css=[{'selector': '.row',
'rule': 'margin: 0; white-space: inherit; overflow: inherit; text-overflow: inherit;'}],
id='table',
columns=[{"name": i, "id": i} for i in dff.columns],
data=dff.to_dict("rows"),
style_cell={"fontFamily": "Arial", "size": 10, 'textAlign': 'left',
'width': '{}%'.format(len(dff.columns)), 'textOverflow': 'ellipsis', 'overflow': 'hidden'},
style_table={'maxHeight': '200px', 'overflowY': 'scroll', 'maxWidth': '1500px', 'overflowX': 'scroll'},
row_selectable="multi",
selected_rows=[],
editable=True,
style_header={'backgroundColor': '#ffd480', 'color': 'white', 'height': '10', 'width': '10',
'fontWeight': 'bold'},
style_data={'whiteSpace': 'auto', 'height': 'auto', 'width': 'auto'},
tooltip_data=[
{
column: {'value': str(value), 'type': 'markdown'}
for column, value in row.items()
} for row in dff.to_dict('rows')
],
tooltip_duration=None
),
], style={'margin-top': 30, 'display': 'inline-block', 'margin-left': 20, 'width': '100%'})
I never expected this is going to like this simple. I added the 'export' argument in my dash table and its solved.
return html.Div([
dash_table.DataTable(
css=[{'selector': '.row',
'rule': 'margin: 0; white-space: inherit; overflow: inherit; text-overflow: inherit;'}],
id='table',
export = "csv"
columns=[{"name": i, "id": i} for i in dff.columns],
data=dff.to_dict("rows"),
style_cell={"fontFamily": "Arial", "size": 10, 'textAlign': 'left',
'width': '{}%'.format(len(dff.columns)), 'textOverflow': 'ellipsis', 'overflow': 'hidden'},
style_table={'maxHeight': '200px', 'overflowY': 'scroll', 'maxWidth': '1500px', 'overflowX': 'scroll'},
row_selectable="multi",
selected_rows=[],
editable=True,
style_header={'backgroundColor': '#ffd480', 'color': 'white', 'height': '10', 'width': '10',
'fontWeight': 'bold'},
style_data={'whiteSpace': 'auto', 'height': 'auto', 'width': 'auto'},
tooltip_data=[
{
column: {'value': str(value), 'type': 'markdown'}
for column, value in row.items()
} for row in dff.to_dict('rows')
],
tooltip_duration=None
),
], style={'margin-top': 30, 'display': 'inline-block', 'margin-left': 20, 'width': '100%'})
Hello I am working on a dash app, and somehow I am not able to update graphs between different divs callback. This is how the app works:
The user gives a url input on the frontend in a textinput box and button is clicked to run analysis.
The user can select the view mode as well before running the analysis, The view mode depends on the dropdown selector
The url is used to display a video frame and run a python function.
The processed results should be stored in the dcc.store component.
The stored data is then called in to update the graphs.
Below is the callback codes:
#Video Selection
#app.callback(Output("video-display", "url"),
[Input("submit_button", "n_clicks")],
[State('video_url', 'value')])
def select_footage(n_clicks, video_url):
if n_clicks is not None and n_clicks > 0:
url = video_url
return url
# Processing and Storing the results in dcc.store
#app.callback(Output("intermediate-value", "data"),
[Input("submit_button", "n_clicks")],
[State('video_url', 'value')])
def video_processing(n_clicks, value ):
global frame
if n_clicks is not None and n_clicks > 0:
frame = python_func(url)
return frame.to_json(orient='split')
# Callback to change the graph view mode div
#app.callback(Output("div-graph-mode", "children"),
[Input("dropdown-graph-view-mode", "value")])
def update_graph_mode(value):
if value == "graphical":
return [
html.Div(
children=[
html.P(children="Retention Score of Detected Labels",
className='plot-title'),
dcc.Graph(
id="bar-score-graph",
style={'height': '55vh', 'width': '100%'}
),
html.P(children="Audience Retention Behavior",
className='plot-title'),
dcc.Graph(
id="line_chart_retention",
style={'height': '45vh', 'width': '100%'}
)
]
)
]
else:
return []
#app.callback(Output("div-table-mode", "children"),
[Input("dropdown-graph-view-mode", "value")])
def update_table_mode(dropdown_value):
if dropdown_value == "table":
return [
html.Div(
children=[
html.P(children="Retention By Label",
className='plot-title'),
html.Div([
table.DataTable(
id="label_retention",
)],
style={'height': '45vh'}),
html.P(children="Retention by Time Stamp",
className='plot-title'),
html.Div([
table.DataTable(
id="timestamp_retention",
style_table={'maxHeight': '40vh', 'width': '100%', 'overflowY': 'scroll'})],
style={'height': '40vh'}
)
]
)
]
else:
return []
# Updating Graphs
#app.callback(Output("label_retention", "figure"),
[Input("dropdown-graph-view-mode", "value")])
def update_table_bar(value):
global frame
if frame is not None:
print(frame)
print("table")
print(value)
#app.callback(Output("bar-score-graph", "figure"),
[Input("dropdown-graph-view-mode", "value")])
def update_score_bar(value):
global frame
if frame is not None:
print(frame)
print("graph")
print(value)
Now what happens is that if I try to toggle between the two graph view modes, the app does not reflect the graphs and requires to click on the button again to get the results. So, basically I believe the data does not gets lost in the dcc.store component when I toggle with the dropdowns.
How can I make the app behave in a way that my python function runs only once on the submit button, but then I am able to toggle between the view modes to see the graphs.
Thanks a lot in advance!!
P.S. This is just a snippet of codes, as the code is too long, but please let me know if you would want to see the entire code.
UPDATE: I have just realised that when I select the Graph Mode, the app prints the results for Table Mode and when I select the table model, the app prints the results for graph mode. I am not able to figure out as to why this is happening.
I was finally able to resolve my issue as below:
#app.callback(Output("div-table-mode", "children"),
[Input("dropdown-graph-view-mode", "value")])
def update_table_mode(dropdown_value):
if dropdown_value == "tabular":
return [
html.Div(
children=[
html.P(children="Retention By Label",
className='plot-title', style={'margin': '0 0 1em 0'}),
html.Div([
table.DataTable(
id="label_retention",
columns=[{"name": i, "id": i} for i in label_retention.columns],
data=label_retention.to_dict("rows"),
style_table={'maxHeight': '40vh', 'width': '100%', 'overflowY': 'scroll'},
style_cell_conditional=[
{
'if': {'column_id': c},
'textAlign': 'left'
} for c in ['Labels']
],
style_data_conditional=[
{
'if': {'row_index': 'odd'},
'backgroundColor': 'rgb(248, 248, 248)'
}
],
style_header={
'backgroundColor': 'rgb(230, 230, 230)',
'fontWeight': 'bold'
}
)],
style={'height': '40vh'}),
html.P(children="Retention by Time Stamp",
className='plot-title', style={'margin': '1em 0 1em 0'}),
html.Div([
table.DataTable(
id="timestamp_retention",
columns=[{"name": i, "id": i} for i in timeline_retention.columns],
data=timeline_retention.to_dict("rows"),
style_table={'maxHeight': '40vh', 'width': '100%', 'overflowY': 'scroll'},
style_cell={'textAlign': 'left', 'minWidth': '20px', 'width': '20px', 'maxWidth': '50px',
'whiteSpace': 'normal'},
css=[{
'selector': '.dash-cell div.dash-cell-value',
'rule': 'display: inline; white-space: inherit; overflow: inherit; text-overflow: inherit;'
}],
style_data_conditional=[
{
'if': {'row_index': 'odd'},
'backgroundColor': 'rgb(248, 248, 248)'
}
],
style_header={
'backgroundColor': 'rgb(230, 230, 230)',
'fontWeight': 'bold'
}
)],
style={'height': '40vh'}
)
],
style={'backgroundColor': '#F2F2F2'}
)
]
else:
return []
#app.callback(Output("div-graph-mode", "children"),
[Input("dropdown-graph-view-mode", "value")])
def update_graph_mode(value):
if value == "graphical":
return [
html.Div(
children=[
html.P(children="Retention Score of Detected Labels",
className='plot-title', style={'margin': '0 0 1em 0', 'width': '100%'}),
dcc.Graph(
id="bar-score-graph",
figure=go.Figure({
'data': [{'hoverinfo': 'x+text',
'name': 'Detection Scores',
#'text': y_text,
'type': 'bar',
'x': label_retention["Description"],
'marker': {'color': colors},
'y': label_retention["sum"].tolist()}],
'layout': {'showlegend': False,
'autosize': False,
'paper_bgcolor': 'rgb(249,249,249)',
'plot_bgcolor': 'rgb(249,249,249)',
'xaxis': {'automargin': True, 'tickangle': -45},
'yaxis': {'automargin': True, 'range': [minval, maxval], 'title': {'text': 'Score'}}}
}
),
style={'height': '55vh', 'width': '100%'}
),
html.P(children="Audience Retention Behavior",
className='plot-title', style={'margin': '0 0 1em 0', 'width': '100%'}),
dcc.Graph(
id="line_chart_retention",
figure=go.Figure({
'data': [go.Scatter(x=label_retention['Start'], y=label_retention['sum'], mode='lines', name='Audience Retention',
line=dict(color='firebrick', width=4))],
'layout': {
'yaxis': {'title': {'text': 'Audience Retention'}, 'automargin': True},
'xaxis': {'title': {'text': 'Time Segment'}, 'automargin': True},
'paper_bgcolor': 'rgb(249,249,249)',
'plot_bgcolor': 'rgb(249,249,249)',
}
}),
style={'height': '45vh', 'width': '100%'}
)
],
style={'backgroundColor': '#F2F2F2', 'width': '100%'}
)
]
else:
return []
As part of a project, I want to visualize data, which is why I chose Dash. For example, the user should drag and drop the column Age and this will then be displayed graphically. How can I achieve this?
I would prefer to display the individual columns as buttons, which he can then 'just' pull.
With dropdown menu it had worked and by drag and drop I could also read a CSV file.I have read the database table as a data frame. Thank you in advance!
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div([
dcc.Upload(
id='upload-data',
children=html.Div([
'Drag and Drop '
]),
style={
'width': '100%',
'height': '60px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '10px'
},
multiple=True
),
html.Div([
dcc.Graph(
id='Graph2'
),
], style={'display': 'inline-block', 'width': '49%'}),
])
I am working on plotly dash app. I have an almost working example. The only thing that is not working is that I am not able to restrict the functions defined in the callbacks not to run when the page loads.
I have tried add checks for the n_clicks inside the callback however it doesnt seem to be working. It runs the function without the clicks as well
Below is the code for the dash
from datetime import date
import base64
import dash
import plotly
import dash
from dash.dependencies import Input, Output, State
from plotly.graph_objs import *
from datetime import datetime as dt
import dash_html_components as html
import dash_core_components as dcc
import flask
import pandas as pd
server = flask.Flask('app')
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash('app', server=server, external_stylesheets=external_stylesheets)
app.layout = html.Div(style={'backgroundColor': '#EFEAEA', 'margin': '0px', 'padding': '0px'}, children=[
html.Div([
html.Div([
html.Img(src='data:image/png;base64,{}'.format(encoded_image.decode()),
style={'width': '200px', 'height': '100px', 'display': 'inline-block', 'float': 'left', 'padding-left': '5px', 'padding-top': '5px'})
]),
html.Div([
html.Div([
html.Div([
dcc.Dropdown(
id='demographics',
options=[
{'label': 'All 18-49', 'value': '18_39'},
{'label': 'Female 25-54', 'value': '25_54 F'},
{'label': 'All 25-54', 'value': '25-54'},
],
placeholder="Select Demographics",
)
],
style={'width': '30.5%', 'display': 'inline-block', 'padding-right': '10px'}),
html.Div([
dcc.DatePickerRange(
id='my-date-picker-range',
start_date_placeholder_text="Select a Start Date",
end_date_placeholder_text="Select an End Date",
min_date_allowed=dt(2018, 1, 1),
max_date_allowed=dt(2050, 12, 31),
initial_visible_month=dt(2019, 1, 2),
style={'width': '600', 'display': 'inline-block', 'padding-right': '10px'}
),
html.Div(id='output-container-date-picker-range')
],
style={'width': '30.3%', 'display': 'inline-block', 'padding-right': '10px', 'position': 'relative'})
],
style={
'backgroundColor': '#EFEAEA',
'padding': '5px 10px'}),
html.Div([
html.Div([
dcc.Dropdown(
id='Horsepower',
options=[
{'label': '200', 'value': 'two_hundred'},
{'label': '250', 'value': 'two_hundred_fifty'},
{'label': '300', 'value': 'three_hundred'},
{'label': '350', 'value': 'three_hundred_fifty'},
{'label': '400', 'value': 'four_hundred'}
],
placeholder="Select TARP",
)
],
style={'width': '20%', 'display': 'inline-block', 'padding-right': '10px'}),
html.Div([
dcc.Dropdown(
id='Kilometers',
options=[
{'label': '250,000', 'value': 250000, 'type': 'number'},
{'label': '500,000', ''value': 500000, 'type': 'number'},
{'label': '750,000', 'value': 750000, 'type': 'number'},
{'label': '1,000,000', 'value': 1000000, 'type': 'number'},
],
placeholder="Select Impressions",
)
],
style={'width': '20%', 'display': 'inline-block', 'padding-right': '10px'}),
html.Div([
dcc.Dropdown(
id='Speed',
options=[
{'label': 'Low', 'value': 50, 'type': 'number'},
{'label': 'Average', 'value': 100, 'type': 'number'},
{'label': 'High', 'value': 150, 'type': 'number'},
],
placeholder="Select Frequency",
)
],
style={'width': '20%', 'display': 'inline-block', 'padding-right': '10px'}),
html.Div([
html.Button('Submit', id='submit_button', type='submit', n_clicks=1,
style={'width': '100px', 'height': '34.5px', 'margin-bottom': '8px',
'border-radius': '4px', 'display': 'inline-block', 'background-color': '#2D91C3', 'color': 'white'})
],
style={'display': 'inline-block', 'padding-bottom': '20px', 'verticalAlign': 'middle'}),
], style={
'backgroundColor': '#EFEAEA',
'padding': '5px'})
], style={'position': 'relative', 'left': '250px'})
]),
html.Div([
html.Div([
dcc.Graph(id='example-graph', config={'modeBarButtonsToRemove': ['pan2d', 'lasso2d', 'sendDataToCloud',
'select2d', 'autoScale2d', 'resetScale2d',
'toggleSpikelines',
'hoverClosestCartesian']})
],
style={'width': '49.3%', 'display': 'inline-block', 'border': 'thin grey solid', 'margin-left': '5px',
'margin-right': '2.5px', 'margin-top': '5px', 'margin-bottom': '2.5px'}),
html.Div([
dcc.Graph(id='example-graph1')
],
style={'width': '49.3%', 'display': 'inline-block', 'border': 'thin grey solid', 'margin-left': '2.5px',
'margin-right': '5px', 'margin-top': '5px', 'margin-bottom': '2.5px', 'backgroundColor': '#EFEAEA'})
], style={'backgroundColor': '#EFEAEA'}),
html.Div([
dcc.Graph(id='graph1')
],
style={'width': '99.2%', 'height': '120%', 'display': 'inline-block', 'border': 'thin grey solid', 'margin-left': '2.5px',
'margin-right': '5px', 'margin-top': '5px', 'margin-bottom': '2.5px', 'backgroundColor': '#EFEAEA'})
])
#app.callback(Output('example-graph1', 'figure'),
[Input('submit_button', 'n_clicks')],
[State('my-date-picker-range', 'start_date'),
State('my-date-picker-range', 'end_date')])
def update_graph(n_clicks, start_date, end_date):
if n_clicks > 0:
df = df_new
start_date_temp = dt.strptime(start_date, '%Y-%m-%d')
end_date_temp = dt.strptime(end_date, '%Y-%m-%d')
start_date_new = start_date_temp.replace(start_date_temp.year - 1)
end_date_new = end_date_temp.replace(end_date_temp.year - 1)
end_date_string = end_date_new.strftime('%Y-%m-%d')
start_date_string = start_date_new.strftime('%Y-%m-%d')
mask = (df['Date'] >= start_date_string) & (df['Date'] <= end_date_string)
filtered_df = df.loc[mask]
trace = Scatter(
y=filtered_df['Weights'],
x=filtered_df['Date'],
line=plotly.graph_objs.scatter.Line(
color='#42C4F7'
),
hoverinfo='skip',
error_y=plotly.graph_objs.scatter.ErrorY(
type='data',
array=filtered_df['Gender'],
thickness=1.5,
width=2,
color='#B4E8FC'
),
mode='lines'
)
layout1 = Layout(
height=450,
xaxis=dict(
showgrid=False,
showline=False,
zeroline=False,
fixedrange=True,
title='Time Elapsed (sec)'
),
yaxis=dict(
showline=False,
fixedrange=True,
zeroline=False,
),
margin=plotly.graph_objs.layout.Margin(
t=45,
l=50,
r=50
)
)
return Figure(data=[trace], layout=layout1)
else:
return {"I am the boss"}
The reason I presume the n_clicks checks is not working because I get the following error
TypeError: strptime() argument 1 must be str, not None
I believe the error is because of the below code inside the function as the first time the page loads start_date would be none type.
start_date_temp = dt.strptime(start_date, '%Y-%m-%d')
Can some one please help to resolve the issue. What I expect that when the page loads the call back function should not run.
Thanks a lot in advance !!
Here is your problem:
html.Button('Submit', id='submit_button', type='submit', n_clicks=1,
You've preset n_clicks to have a value. Just remove that n_clicks=1 part, and it will load the page as None. You will then need to check n_clicks like this (or similar):
if n_clicks is not None and n_clicks > 0:
It worked for me, and ran until it broke with my example df.