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I have a dash app that plots a dataframe which has a date component, and an entry that is either true or false. There are two graphs in the dashboard, one with the data vs date, and one with a percentage of True/False like below:
I can zoom in on the date range and select a subset clicking with the mouse.
I would like to feed this range back into the second graph.
At the moment to produce the above dashboard the relevant part of the code looks like:
from re import template
import pandas as pd
import plotly.express as px
from dash import Dash, Input, Output, dcc, html
from flask import globals
def init_dashboard(server):
evicted_df = pd.read_csv("app/data/evicted_jobs_node.csv", sep="\t")
all_df = pd.read_csv("app/data/all_jobs_node.csv", sep="\t")
all_df["datetime"] = pd.to_datetime(all_df["datetime"])
all_df = all_df.set_index(["datetime"])
all_df["evicted"] = all_df["id_job"].isin(evicted_df["id_job"])
app = Dash(__name__, server=server, routes_pathname_prefix="/dash/")
app.layout = html.Div(
[
html.Div(
className="row",
children=[
html.Div(
className="six columns",
children=[dcc.Graph(id="graph-with-dropdown")],
style=dict(width="75%"),
),
html.Div(
className="six columns",
children=[dcc.Graph(id="graph-with-dropdown2")],
style=dict(width="25%"),
),
],
style=dict(display="flex"),
),
html.Div(
className="row",
children=[
html.Div(
className="six columns",
children=[
dcc.Dropdown(
id="partition-dropdown",
options=[
"Partition (default is all)",
*all_df["partition"].unique(),
],
value="Partition (default is all)",
clearable=False,
searchable=False,
)
],
style={
"width": "50%",
"justify-content": "center",
},
),
html.Div(
className="six columns",
children=[
dcc.Dropdown(
id="node-dropdown",
options=[
"Number of Nodes (default is all)",
*sorted(
[
int(nodes)
for nodes in all_df["nodes_alloc"].unique()
]
),
],
value="Number of Nodes (default is all)",
clearable=False,
searchable=False,
)
],
style=dict(width="50%"),
),
],
style=dict(display="flex"),
),
]
)
init_callbacks(app, df, all_df)
return app.server
def init_callbacks(app, df, all_df):
#app.callback(
Output("graph-with-dropdown2", "figure"),
[Input("node-dropdown", "value"), Input("partition-dropdown", "value")],
)
def update_evicted_fig(selected_nodes, selected_partition):
if selected_nodes != "Number of Nodes (default is all)":
filtered_df = all_df[all_df["nodes_alloc"] == selected_nodes]
else:
filtered_df = all_df
if selected_partition != "Partition (default is all)":
filtered_df = filtered_df[filtered_df["partition"] == selected_partition]
x = ["Not Evicted", "Evicted"]
df1 = filtered_df.groupby(["evicted"]).count().reset_index()
fig = px.bar(
df1,
y=[
100
* filtered_df[filtered_df["evicted"] == False].size
/ filtered_df.size,
100
* filtered_df[filtered_df["evicted"] == True].size
/ filtered_df.size,
],
x=x,
color="evicted",
color_discrete_map={True: "red", False: "green"},
labels={"x": "Job Status", "y": "% of Jobs"},
)
fig.update_layout(transition_duration=500)
return fig
#app.callback(
Output("graph-with-dropdown", "figure"),
[Input("node-dropdown", "value"), Input("partition-dropdown", "value")],
)
def update_evicted_fig(selected_nodes, selected_partition):
if selected_nodes != "Number of Nodes (default is all)":
filtered_df = all_df[all_df["nodes_alloc"] == selected_nodes]
else:
filtered_df = all_df
if selected_partition != "Partition (default is all)":
filtered_df = filtered_df[filtered_df["partition"] == selected_partition]
print(
filtered_df[filtered_df["evicted"] == True]
.groupby([pd.Grouper(freq="6H")])
.sum(numeric_only=True)["node_hours"]
)
fig = px.bar(
x=filtered_df[filtered_df["evicted"] == False]
.groupby([pd.Grouper(freq="6H")])
.sum(numeric_only=True)["node_hours"]
.index,
y=filtered_df[filtered_df["evicted"] == False]
.groupby([pd.Grouper(freq="6H")])
.sum(numeric_only=True)["node_hours"],
labels={
"x": "Date",
"y": "Node hours",
},
title="Job Status",
barmode="stack",
)
fig.add_bar(
name="Evicted",
x=filtered_df[filtered_df["evicted"] == True]
.groupby([pd.Grouper(freq="6H")])
.sum(numeric_only=True)["node_hours"]
.index,
y=filtered_df[filtered_df["evicted"] == True]
.groupby([pd.Grouper(freq="6H")])
.sum(numeric_only=True)["node_hours"],
)
fig.update_layout(transition_duration=500)
return fig
return app.server
Is what I am hoping to do possible, and if so is there some documentation or a worked example someone could highlight for me?
I don't have you df so maybe you can refer my code to revise yours:
import pandas as pd
import numpy as np
import plotly.express as px
import dash
import dash_html_components as html
from dash import dcc
from dash_extensions.enrich import Input, Output, State, ServersideOutput
import dash_bootstrap_components as dbc
from dash.exceptions import PreventUpdate
df_2 = df[(df['BAS_DT'] >= '2022-01-01')]
df5 = df_2.pivot_table(values='USD_XC_BL',
index=['BAS_DT'],
aggfunc=np.sum).reset_index()
fig_3 = px.bar(df5,
x='BAS_DT',
y='USD_XC_BL',
labels='BAS_DT',
hover_name='BAS_DT', color_discrete_sequence=px.colors.qualitative.Alphabet)
fig_3.update_layout(xaxis_title="", yaxis_title="", plot_bgcolor='rgba(0,0,0,0)', margin=dict(l=0, r=0, t=0, b=0))
fig_3.update_xaxes(showline=False, showgrid=False),
fig_3.update_yaxes(showline=False, showgrid=False, separatethousands=True, tickformat=',.0f')
app = dash.Dash(__name__)
app.layout = html.Div([
dbc.Row([
dbc.Col([
dbc.Card([
dbc.CardBody([
dbc.Row([
dbc.Col([
html.H5('Amount by Currency', style={"text-align": "center"}),
dcc.Loading(children=[dcc.Graph(id='histogram_map', figure=fig_3)], color='#119DFF',
type='dot')
], width={'size': 12, 'offset': 0, 'order': 2}, style={"text-align": "left"}),
]),
])
]),
], xs=6),
dbc.Col([
dbc.Card([
dbc.CardBody([
dbc.Row([
dbc.Col([
html.H5('Overdue Status', style={"text-align": "center"}),
dcc.Loading(children=[dcc.Graph(id='overdue_map', figure={})], color='#119DFF', type='dot')
], width={'size': 12, 'offset': 0, 'order': 2}, style={"text-align": "left"}),
]),
])
]),
], xs=6),
], className='p-2 align-items-stretch')
])
#app.callback(
Output('overdue_map', 'figure'),
Input('histogram_map', 'clickData'))
def update_y_timeseries(clickData):
if clickData:
country_name = clickData['points'][0]['hovertext']
df_3 = df[df['BAS_DT'] == country_name]
df_4 = df_3.pivot_table(values='CLOC_CUR_XC_BL',
index=['APL_DTL_NAME'],
aggfunc=pd.Series.nunique).reset_index()
fig = px.bar(df_4,
x='APL_DTL_NAME',
y='CLOC_CUR_XC_BL'
, color_discrete_sequence=px.colors.qualitative.Alphabet)
fig.update_layout(xaxis_title="", yaxis_title="", plot_bgcolor='rgba(0,0,0,0)') # plot_bgcolor='rgba(0,0,0,0)'
fig.update_xaxes(showline=False, showgrid=False),
fig.update_yaxes(showline=False, showgrid=False, separatethousands=True)
fig.update_traces(width=0.3)
return fig
else:
raise PreventUpdate
if __name__ == "__main__":
app.run_server(debug=True)
I'm using clickData to return point as date, and then use this date to filter data and then make new bar graph.
Hope this help.
I am trying to get into using Plotly Dash and I am getting stuck on this one piece where I would like to dynamically add a user-defined number of dropdowns. Here is what I tried:
# Import required libraries
import dash
import math
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
# App Begins
app = dash.Dash(
__name__, meta_tags=[{"name": "viewport", "content": "width=device-width"}],
)
app.title = "Tool"
server = app.server
# Create global chart template
mapbox_access_token = "pk.eyJ1IjoicGxvdGx5bWFwYm94IiwiYSI6ImNrOWJqb2F4djBnMjEzbG50amg0dnJieG4ifQ.Zme1-Uzoi75IaFbieBDl3A"
layout = dict(
autosize=True,
automargin=True,
margin=dict(l=30, r=30, b=20, t=40),
hovermode="closest",
plot_bgcolor="#F9F9F9",
paper_bgcolor="#F9F9F9",
legend=dict(font=dict(size=10), orientation="h"),
title="Satellite Overview",
mapbox=dict(
accesstoken=mapbox_access_token,
style="light",
center=dict(lon=-78.05, lat=42.54),
zoom=7,
),
)
# Create app layout
app.layout = html.Div(
[
dcc.Store(id="aggregate_data"),
# empty Div to trigger javascript file for graph resizing
html.Div(id="output-clientside"),
html.Div(
[
html.Div(
[
html.Img(
src=app.get_asset_url("dash-logo.png"),
id="plotly-image",
style={
"height": "60px",
"width": "auto",
"margin-bottom": "25px",
},
)
],
className="one-third column",
),
html.Div(
[
html.Div(
[
html.H3(
"Dash Tool",
style={"margin-bottom": "0px"},
),
]
)
],
className="one-half column",
id="title",
),
],
id="header",
className="row flex-display",
style={"margin-bottom": "25px"},
),
html.Div(
[
html.Div(
[
html.P("Quantity 1:", className="control_label"),
dcc.Input(
id="quantity_1",
type="number",
placeholder=33.
),
html.P("Quantity 2:", className="control_label"),
dcc.Input(
id="quantity_2",
type="number",
placeholder=-115.
),
html.P("Number of Drop Downs:", className="control_label"),
dcc.Slider(
id="drop_downs",
min=2,
max=10,
value=2,
step=1.0,
className="dcc_control",
),
html.P("Load Inputs:", className="control_label"),
dcc.Checklist(
id='sources_flag',
options=[
{'label': 'Yes', 'value': 'Y'},
],
value=['Y'],
labelStyle={'display': 'inline-block'}
),
html.Div(id='source_dropdown_container', children=[]),
html.Div(id='source_dropdown_container_output'),
html.Div(id='source_file_container', children=[]),
html.Div(id='source_file_container_output'),
],
className="pretty_container four columns",
id="cross-filter-options",
),
],
className="row flex-display",
),
],
id="mainContainer",
style={"display": "flex", "flex-direction": "column"},
)
# Create callbacks
#app.callback(
[
Output(component_id='source_dropdown_container_output', component_property='children'),
],
[
Input(component_id='drop_downs', component_property='value'),
Input(component_id='sources_flag', component_property='value'),
]
)
def update_source_dropdowns(value, value_1):
"""Controls the number of drop-downs available to choose sources"""
if value_1 == 'Y':
children = []
for i in range(0, value):
new_dropdown = dcc.Dropdown(
id=f'''source_dropdown_{str(i)}''',
options=['GOOG', 'FB', 'TDOC', 'FANG']
)
children.append(new_dropdown)
print(children)
print(type(children))
return children
I keep running into a callback error. The drop down is constructed properly, so I am kind of confused as to why that error is being invoked.
dash.exceptions.InvalidCallbackReturnValue: The callback ..source_dropdown_container_output.children.. is a multi-output.
Expected the output type to be a list or tuple but got:
None.
Any guidance or help is appreciated. All I am trying to do is add based on user input a dynamic number of drop downs to the layout.
you have three errors in your callback
there is only one return, hence do not define Output as a list
conditional check is wrong, should be if value_1 == ['Y']:
doc.Dropdown() options argument needs to define list of dict
# Create callbacks
#app.callback(
Output(component_id='source_dropdown_container_output', component_property='children'),
[
Input(component_id='drop_downs', component_property='value'),
Input(component_id='sources_flag', component_property='value'),
]
)
def update_source_dropdowns(value, value_1):
"""Controls the number of drop-downs available to choose sources"""
print("cb", value, value_1)
if value_1 == ['Y']:
children = []
for i in range(0, value):
new_dropdown = dcc.Dropdown(
id=f'''source_dropdown_{str(i)}''',
options=[{"label":v, "value":v } for v in ['GOOG', 'FB', 'TDOC', 'FANG']],
)
children.append(new_dropdown)
print(children)
print(type(children))
return children
I have been banging my head off the wall all day and cannot find a way to fit a dash indicator inside of a dash_bootstrap_components card.
It seems that the body of the card and the graph do not live inside of the card. I am not very familiar with dash so it is difficult to find a way to solve the issue.
here is what I have been able to do so far in terms of plotting the indicator:
fig3 = go.Figure()
fig3.add_trace(go.Indicator(
mode = "number+delta",
number = {"font":{"size":40},'prefix': "$"},
value = 2045672,
delta = {'reference': 30000},
gauge = {'shape': "bullet"},
title = {"text": "On Hand<br><span style='font-size:0.9em;color:gray'></span>"},
#title='Stock On Hand',
domain = {'x': [0, 1], 'y': [0, 1]},
))
fig3.update_layout(paper_bgcolor = "rgba(0,0,0,0)",
plot_bgcolor = "rgba(0,0,0,0)",
autosize=False,
width = 200,
height=200,
)
fig3.update_traces(align="center", selector=dict(type='indicator'))
I am forced to specify width and height for the indicator otherwise it is way too big, however this cause issues because its size does not adjust in regards to the card.
here is the html dash code for the box and the plot:
html.Div(children=[
html.Div(children=[
html.Div(children=[
html.Div(children=[
dbc.Card(
[dbc.CardBody(
[dcc.Graph(figure=fig3)
]
)],className="card", style={"width": "15rem", "height":"8rem"}
),
], className='jumbotron', style={'background-color': '#fffffff'}),
])
],className="col-3 mx-auto"),
],className="row p-0 h-100", style={'background-color': '#f7f7f7', 'height':110}),
], className="full-width p-0 h-100", style={'background-color': '#fffffff'}),
and here is what the final output looks like:
I am not sure what else I can try to bring the graph inside of the box, any help would be appreciated
Remove the instances where you set the height in the style of dash components and the indicator doesn't get cut off.
So you can do something like this:
app.layout = html.Div(
children=[
html.Div(
children=[
html.Div(
children=[
html.Div(
children=[
dbc.Card(
[
dbc.CardBody(
[dcc.Graph(figure=fig3)],
style={"width": "15rem"},
)
]
)
],
className="jumbotron",
style={"backgroundColor": "#fffffff"},
)
],
className="col-3 mx-auto",
)
],
className="row p-0 h-100",
style={"backgroundColor": "#f7f7f7"},
)
],
className="full-width p-0 h-100",
style={"backgroundColor": "#fffffff"},
)
I've also changed the casing of the style properties to camelCase as this is what React (which dash uses) likes.
I want to align two Dropdown menus and a DatePickerRange horizontally. But with the following code:
import dash
import dash_core_components as dcc
import dash_html_components as html
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
style_dict = dict(width='100%',
border='1.5px black solid',
height='50px',
textAlign='center',
fontSize=25)
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div(children=[
html.H1(children='Hello Dash'),
# placeholder
html.Div(style={'width': '2%', 'display': 'inline-block'}),
html.Div(
dcc.Dropdown(
id = 'start_hour',
options = [{'label': i, 'value': i} for i in list(range(0,24))],
style=style_dict,
), style={'width': '20%', 'display': 'inline-block'}),
# placeholder
html.Div(style={'width': '2%', 'display': 'inline-block'}),
html.Div(
dcc.DatePickerRange(
id='date_picker_range',
style=style_dict
), style={'width': '14%', 'display': 'inline-block', 'fontSize': 20}),
# placeholder
html.Div(style={'width': '2%', 'display': 'inline-block'}),
html.Div(
dcc.Dropdown(
id = 'end_hour',
options = [{'label': i, 'value': i} for i in list(range(0,24))],
style=style_dict
), style={'width': '20%', 'display': 'inline-block'}),
])
if __name__ == '__main__':
app.run_server(debug=False, use_reloader=False)
I got this layout:
If I zoom in I got this:
Is it possible to force the components to be aligned at the top edge, no matter how I zoom in or out?
As browser I use Firefox.
I had a problem similar to the one you are describing. I was creating a dashboard that looked like this:
dcc components without proper alignement
As you can see in the image, my dcc components, as well as their titles were not aligned correctly. I tried adding the style parameter verticalAlign and it worked as I expected. This is how the dashboard looked after adding that style parameter:
dcc components aligned
I'm attaching my dashboard Layout code so you can see where I placed the parameter mentioned:
## Dashboard layout
app.layout = html.Div( ## Master div
[
html.Div( ## Dashboard title
[
dcc.Markdown(dash_title)
]
),
html.Div( ## Select menus
[
html.Div( ## Stock select
[
dcc.Markdown(dash_stock_sel),
dcc.Dropdown(
id="select_stock",
options=[{"label": cmp, "value": tickers_base[cmp]["symbol"]} for cmp in tickers_base],
value="TSLA"
)
],
style={
"display": "inline-block",
"width": "20%"
}
),
html.Div( ## Date select dcc components
[
dcc.Markdown(dash_date_sel),
dcc.DatePickerRange(
id="select_dates",
min_date_allowed=date(2015, 1, 1),
max_date_allowed=date.today(),
initial_visible_month=date(2015, 1, 1),
end_date=date.today()
)
],
style={
"display": "inline-block",
"width": "30%",
"margin-left": "20px",
"verticalAlign": "top"
}
),
]
),
html.Div( ## Stock prices graph
[
dcc.Graph(
id="cstock_graph",
figure=stock_graph(def_company, datareader_api, def_start, def_end)
)
]
)
]
)
I hope this answer helps!
I'm new to dash and I'm having problems finding examples on using data frames within a callback. I created a weekly radio button and a monthly radio button.
When the monthly radio button is selected I would like the graph to pull data from df_monthly where each bar would be a monthly sum of pay. When the weekly radio button is checked I would like to see the graph populate each bar on a weekly basis which would be each row in the data frame since I get paid once a week.
I'm not certain where I'm going wrong but I keep receiving an error stating TypeError: update_fig() takes 0 positional arguments but 1 was given
The graph populates without data like the picture below. Thanks for any help on this matter.
import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly.plotly as py
import plotly.graph_objs as go
import sqlite3
import pandas as pd
from functools import reduce
import datetime
conn = sqlite3.connect('paychecks.db')
df_ct = pd.read_sql('SELECT * FROM CheckTotal',conn)
df_earn = pd.read_sql('SELECT * FROM Earnings', conn)
df_whold = pd.read_sql('SELECT * FROM Withholdings', conn)
data_frames = [df_ct, df_earn, df_whold]
df_paystub = reduce(lambda left,right: pd.merge(left,right,on=['Date'], how='outer'), data_frames)
def date_extraction(df):
df['Date'] = pd.to_datetime(df['Date'])
df['Year'] = df['Date'].dt.strftime('%Y')
df['Month'] = df['Date'].dt.strftime('%B')
df['Day'] = df['Date'].dt.strftime('%d')
return df
date_extraction(df_paystub)
df_monthly = df_paystub.groupby(['Month']).sum()
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.css.append_css({'external_url': 'https://codepen.io/amyoshino/pen/jzXypZ.css'})
app.layout = html.Div(children=[
html.Div([
html.Div([
dcc.RadioItems(
id='data-view',
options=[
{'label': 'Weekly', 'value': 'Weekly'},
{'label': 'Monthly', 'value': 'Monthly'},
],
value='',
labelStyle={'display': 'inline-block'}
),
], className = 'two columns'),
html.Div([
dcc.Dropdown(
id='year-dropdown',
options=[
{'label': i, 'value': i} for i in df_paystub['Year'].unique()
],
placeholder="Select a year",
),
], className='five columns'),
html.Div([
dcc.Dropdown(
id='month-dropdown',
options=[
{'label': i, 'value': i} for i in df_paystub['Month'].unique()
],
placeholder="Select a month(s)",
multi=True,
),
], className='five columns'),
], className = 'row'),
# HTML ROW CREATED IN DASH
html.Div([
# HTML COLUMN CREATED IN DASH
html.Div([
# PLOTLY BAR GRAPH
dcc.Graph(
id='pay',
)
], className = 'six columns'),
# HTML COLUMN CREATED IN DASH
html.Div([
# PLOTLY LINE GRAPH
dcc.Graph(
id='hours',
figure={
'data': [
go.Scatter(
x = df_earn['Date'],
y = df_earn['RegHours'],
mode = 'lines',
name = 'Regular Hours',
),
go.Scatter(
x = df_earn['Date'],
y = df_earn['OtHours'],
mode = 'lines',
name = 'Overtime Hours',
)
]
}
)
], className='six columns')
], className='row')
], className='ten columns offset-by-one')
#app.callback(dash.dependencies.Output('pay', 'figure'),
[dash.dependencies.Input('data-view', 'value')])
def update_fig():
figure={
'data': [
go.Bar(
x = df_monthly['Month'],
y = df_monthly['CheckTotal'],
name = 'Take Home Pay',
),
go.Bar(
x = df_monthly['Month'],
y = df_monthly['EarnTotal'],
name = 'Earnings',
)
],
'layout': go.Layout(
title = 'Take Home Pay vs. Earnings',
barmode = 'group',
yaxis = dict(title = 'Pay (U.S. Dollars)'),
xaxis = dict(title = 'Date Paid')
)
}
return figure
if __name__ == "__main__":
app.run_server(debug=True)
Hi #prime90 and welcome to Dash.
In glancing at your callback signature it looks like the update_fig() function needs to take the Input you've given it (using dash.dependencies.Input).
The callback is sending this Input what changes in your app you've specified. So it's sending along the value of #data-view you've given to your function update_fig(), which doesn't currently accept any variables, causing the error message.
Just update your function signature and add a couple of boolean variables to rid yourself of the error and get the potential functionality:
def update_fig(dataview_value):
# define your weekly OR monthly dataframe
# you'll need to supply df_weekly similarly to df_monthly
# though DO NOT modify these, see note below!
df = df_weekly if dataview == 'weekly' else df_monthly
dfkey = 'Week' if 'week' in df.columns else 'Month' # eh, worth a shot!
figure={
'data': [
go.Bar(
x = df[dfkey],
y = df['CheckTotal'],
name = 'Take Home Pay',
),
go.Bar(
x = df[dfkey],
y = df['EarnTotal'],
name = 'Earnings',
)
],
'layout': go.Layout(
title = 'Take Home Pay vs. Earnings',
barmode = 'group',
yaxis = dict(title = 'Pay (U.S. Dollars)'),
xaxis = dict(title = 'Date Paid')
)
}
return figure
As was written in the comments above, you'll need to do some type of prior manipulation to create a df_weekly, as you have with your current df_monthly.
In addition, the code snippet I wrote assumes the df column is named "Week" and "Month"--obviously update these as is necessary.
Data manipulation in Dash:
Ensure you read the data sharing docs, as they highlight how data should never be modified out of scope.
I hope this helps :-)