Develop Reference

Time axis not update ploty-dash which is obtain from excel sheet when its updated

Hi I'm new to plotly dash. My objective is to draw a graph when excel sheet is updated.
The lines are updated when I add a new row to sheet but axises are not animated or updated. But when I refresh the browser it graph was updated and axis also updated. Here is my code. Any help would be highly appreciated
import dash
from datetime import datetime as dt
from dash.dependencies import Output, Input
from dash import dcc
from dash import html
from plotly.subplots import make_subplots
import plotly.graph_objs as go
import pandas as pd
def check_acc_data():
df = pd.read_excel("test.xlsx")
last_10_df = df.tail(10)
# print(last_10_df)
time_ = last_10_df['time'].values.tolist()
# time_2=["14:00","14:30","15:00","15:30","16:00","16:30","17:00","17:30","18:00","18:30"]
temp = last_10_df['temperature'].values.tolist()
humidity = last_10_df['Humidity'].values.tolist()
test_str = [date_obj.strftime('%H:%M') for date_obj in time_]
return test_str,temp,humidity
app = dash.Dash(__name__)
#fig = px.line(x=test_str, y=[temp, humidity])
app.layout = html.Div([
html.H4('Dashboard'),
dcc.Interval('graph-update', interval = 2000, n_intervals = 0),
html.Div(children='''
Temperature Humidity and Time variation.
'''),
dcc.Graph(
id='example-graph',
figure={},
animate=True
)
])
#app.callback(
dash.dependencies.Output('example-graph','figure'),
[dash.dependencies.Input('graph-update', 'n_intervals')])
def update_figure(n):
time1,temp1,humid1=check_acc_data()
fig = make_subplots(specs=[[{"secondary_y": True}]])
fig.add_trace(
go.Scatter(x=time1, y=temp1, mode="lines+markers", name='Temperature'),
secondary_y=False
)
fig.add_trace(
go.Scatter(x=time1, y=humid1, mode="lines+markers", name='Humidity'),
secondary_y=True,
)
fig.update_layout(yaxis=dict(range=[-2.5,50]),
yaxis1=dict(range=[-2.5,100]),
)
return fig
if __name__ == '__main__':
app.run_server(debug=True, port=10451)

Add line plot to existing plotly express chart

import dash
from dash import Dash, html, dcc, Output, Input, callback
import plotly.graph_objects as go
import plotly.express as px
df1 = pd.read_csv(filepath+filename, index_col="Date")
df1.index = pd.to_datetime(df1.index)
df1["Measure1_SMA"] = df1["Measure1"].rolling(20).mean()
df1["Measure2_SMA"] = df1["Measure2"].rolling(20).mean()
app = Dash(__name__)
my_dropdown = dcc.Dropdown(options = ['Measure1', 'Measure2'],
value = df1.columns[:2],
multi = False,
style = {'width':'50%'})
my_graph = dcc.Graph(figure={})
app.layout = html.Div([
html.H1('Metrics (Values)', style = {'textAlign':'center'}),
html.Label("Metrics: "),
my_dropdown,
my_graph
])
#callback(
Output(component_id=my_graph, component_property='figure'),
Input(component_id=my_dropdown, component_property='value')
)
def update_graph(dropdown_value):
plot_figure = px.bar(data_frame=df1, y=dropdown_value, x=df1.index)
#plot_figure.add_line()
print(dropdown_value)
return plot_figure
if __name__ == "__main__":
app.run_server(debug=True)
I want to create a single plot on the plotly dashboard with an option to toggle between Measure1 and Measure2. Selecting the dropdown_value will create a bar graph of Measure1 on y-axis and Date on x-axis. I also want to plot a line graph on the same plot which will be the rolling average of previous 20 days for the value selected from the dropdown.
I tried adding a add_line() method but not sure how to use it.

Creates a data frame from which the value columns and SMA columns are extracted, using the values obtained from the drop-down selections. Draw a bar graph in the created data frame and add the SMA in scatter plot line mode. drawing two graphs, I think I need to make a graph with two axes. since I could not add graphs to px.line, I reused the data in px.line to create the first I have used the data from px.line as the first graph. The sample data is stock price data.
import dash
from dash import Dash, html, dcc, Output, Input, callback
import plotly.graph_objects as go
import plotly.express as px
from plotly.subplots import make_subplots
import yfinance as yf
df1 = yf.download("AAPL", start="2021-01-01", end="2021-03-01")
df1["Close_SMA"] = df1["Close"].rolling(20).mean()
df1["High_SMA"] = df1["High"].rolling(20).mean()
df1 = df1[['High','Close','Close_SMA','High_SMA']]
app = Dash(__name__)
my_dropdown = dcc.Dropdown(options = ['Close', 'High'],
value = 'Close',
multi = False,
style = {'width':'50%'})
my_graph = dcc.Graph(figure={})
app.layout = html.Div([
html.H1('Metrics (Values)', style = {'textAlign':'center'}),
html.Label("Metrics: "),
my_dropdown,
my_graph
])
#callback(
Output(component_id=my_graph, component_property='figure'),
Input(component_id=my_dropdown, component_property='value')
)
def update_graph(dropdown_value):
sma = '{}_SMA'.format(dropdown_value)
dff = df1[[dropdown_value,sma]]
dff = dff.dropna()
plot_figure = make_subplots(specs=[[{"secondary_y": True}]])
fig = px.bar(data_frame=dff, y=dropdown_value, x=dff.index)
plot_figure.add_trace(fig.data[0], secondary_y=False)
plot_figure.add_trace(go.Scatter(x=dff.index, y=dff[sma], name=sma, mode='lines'), secondary_y=True)
plot_figure.update_layout(yaxis_title='Close')
return plot_figure
if __name__ == "__main__":
app.run_server(debug=True)

Produce multiple plots using dash callbacks

I'm not clear how I could dynamically create multiple charts at once - or if that is not possible then how I could loop through a list of values using a single callback.
For example in the code below list of continents is a a list of filter options. Is it possible to basically make it so when this page loads, I see 5 charts automatically?
Currently, what I'm doing is I have to type 5 #app.callback...make_scatter_plot(option=_dropdown_value) which ends up with a million lines of code in my file and makes it hard to read even though everything is doing the same thing.
What am I missing? Thanks
from dash import Dash, dcc, html, Input, Output
import plotly.express as px
import pandas as pd
import numpy as np
app = Dash(__name__)
df = px.data.gapminder()
list_of_continents = ["Asia", "Africa", "Europe", 'Oceania', 'Americas']
app.layout = html.Div([
html.H4('Restaurant tips by day of week'),
dcc.Dropdown(
id="dropdown",
options=list_of_continents,
multi=False
),
dcc.Graph(id="graph"),
#dcc.Graph(id ='graph2') ##????
])
#app.callback(
Output("graph", "figure"),
Input("dropdown", "value")
)
def make_scatter_plot( value =[i for i in list_of_continents], df = df):
"""
"""
data = df[df['continent'].isin([value])]
fig = px.scatter(data, x="lifeExp", y="gdpPercap",
size="pop")
return fig
if __name__ == '__main__':
app.run_server(debug=True)

although plotly express can help you set up a graph with just one line of code it’s not very handy when it comes to customizing each trace. So, for that, you’ve to switch to graphs_objects.
In the following lines of code, the callback generates a Graph component for each trace and appends each graph component to a Div component. Hence you get multiple graphs using a single callback.
from dash import Dash, dcc, html, Input, Output
import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
import numpy as np
app = Dash(__name__)
df = px.data.gapminder()
app.layout = html.Div([
html.H4('Restaurant tips by day of week'),
html.Div(id='graphs',children=[])
])
#app.callback(
Output("graphs", "children"),
Input("graphs", "children")
)
def make_scatter_plot(child):
"""
"""
for continent in df['continent'].unique():
df_filtered = df[df['continent'] == continent]
fig = go.Figure()
fig.add_trace(
go.Scatter(x = df_filtered['lifeExp'],
y = df_filtered['gdpPercap'],
mode = 'markers',
marker = dict(size = 10 + (df_filtered['pop'] - df_filtered['pop'].min()) * 20
/ (df_filtered['pop'].max() - df_filtered['pop'].min())) # This is just to scale the marker size value between 10 and 20.
)
)
fig.update_layout(
title_text = continent
)
child.append(dcc.Graph(figure=fig))
return child
if __name__ == '__main__':
app.run_server(debug=True)
The output of the Code:
Click here

How to implement dropdown menu in Plotly Dash using Python?

In this app, I'm trying to display a plot that changes when the value in the dropdown menu is changed. The values are the boroughs in London. The data can be found here. Below is the code for base plot.
import plotly.graph_objects as go
df = pd.read_excel('multi-year-station-entry-and-exit-figures.xls', sheet_name='2017 Entry & Exit', skiprows=6)
df = df.loc[df['Borough'] == 'Islington']
df['Sunday'] = df['Sunday'] + df['Sunday.1']
df['Saturday'] = df['Saturday'] + df['Saturday.1']
df = df[['Borough', 'Station', 'Saturday', 'Sunday']]
df.index = range(len(df))
print(df['Borough'])
fig = go.Figure(data=[
go.Bar(name='Saturday', x=df["Station"], y=df["Saturday"]),
go.Bar(name='Sunday', x=df["Station"], y=df["Sunday"])
])
fig.update_layout(title='Weekend entry and exit figures in 2017',
xaxis_tickfont_size=14,
yaxis=dict(
title='Entry and exit numbers',
titlefont_size=16,
tickfont_size=14,
)
, barmode='group', template='plotly_dark', bargap=0.3, bargroupgap=0.1)
fig.show()
I am able to change the the borough name manually to change the plot. I then created the Dash app with the the dropdown menu. However, I can't figure out how to change the plot when a dropdown option is selected. I created a version using conditional statements where I add an if-elif statement for each borough. I am still unable to change the plot itself however. Basically, I need to incorporate this piece of code df = df.loc[df['Borough'] == 'Islington'] to the Dash app. The Dash app code is shown below.
import dash_core_components as dcc
import dash_html_components as html
import plotly.express as px
import pandas as pd
import os
import plotly.io as pio
import plotly.graph_objects as go
import dash_bootstrap_components as dbc
df = pd.read_excel('multi-year-station-entry-and-exit-figures.xls', sheet_name='2017 Entry & Exit', skiprows=6)
df['Sunday'] = df['Sunday'] + df['Sunday.1']
df['Saturday'] = df['Saturday'] + df['Saturday.1']
df = df[['Borough', 'Station', 'Saturday', 'Sunday']]
df.index = range(len(df))
df = df[:-3]
app = dash.Dash()
fig_names = ['Islington', 'Camden']
fig_dropdown = html.Div([
dcc.Dropdown(
id='fig_dropdown',
options=[{'label': x, 'value': x} for x in fig_names],
value=None
)])
fig_plot = html.Div(id='fig_plot')
app.layout = html.Div([fig_dropdown, fig_plot])
#app.callback(
dash.dependencies.Output('fig_plot', 'children'),
[dash.dependencies.Input('fig_dropdown', 'value')])
def update_output(fig_name):
return name_to_figure(fig_name)
def name_to_figure(fig_name):
figure = go.Figure()
if fig_name == 'Islington':
figure = go.Figure(data=[
go.Bar(name='Saturday', x=df["Station"], y=df["Saturday"]),
go.Bar(name='Sunday', x=df["Station"], y=df["Sunday"])
])
elif fig_name == 'Camden':
figure = go.Figure(data=[
go.Bar(name='Saturday', x=df["Station"], y=df["Saturday"]),
go.Bar(name='Sunday', x=df["Station"], y=df["Sunday"])
])
return dcc.Graph(figure=figure)
app.run_server(debug=True, use_reloader=False)

You can create a copy of your data frame containing only the data corresponding to the dropdown selection, and then use this filtered data frame for generating the figure:
import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import plotly.graph_objects as go
app = dash.Dash()
# load the data
df = pd.read_excel('multi-year-station-entry-and-exit-figures.xls', sheet_name='2017 Entry & Exit', skiprows=6)
df['Sunday'] = df['Sunday'] + df['Sunday.1']
df['Saturday'] = df['Saturday'] + df['Saturday.1']
df = df[['Borough', 'Station', 'Saturday', 'Sunday']]
df.index = range(len(df))
df = df[:-3]
# extract the list of all boroughs
fig_names = df['Borough'].unique().tolist()
# generate the app layout
app.layout = html.Div([
# add a dropdown for selecting the borough
html.Div([
dcc.Dropdown(
id='fig_dropdown',
options=[{'label': x, 'value': x} for x in fig_names],
value=fig_names[0] # use the first borough as the initial selection
)]),
# add a container for the figure
html.Div(id='fig_plot'),
])
# define a callback for updating the figure
# based on the dropdown selection
#app.callback(dash.dependencies.Output('fig_plot', 'children'),
[dash.dependencies.Input('fig_dropdown', 'value')])
def update_output(fig_name):
# extract the data for the selected borough
df_fig = df[df['Borough'] == fig_name]
# plot the data for the selected borough
figure = go.Figure(data=[
go.Bar(name='Saturday', x=df_fig['Station'], y=df_fig['Saturday']),
go.Bar(name='Sunday', x=df_fig['Station'], y=df_fig['Sunday'])
])
return dcc.Graph(figure=figure)
if __name__ == '__main__':
app.run_server(debug=True, host='0.0.0.0', port=1234)

Plotly Dash dropdown menu python

I would like to add a dropdown menu to show only one figure. I mean, if I select fig the dash must show me only the fig and if I select fig2 the dash must show me the fig 2. Is it possible?
My code is an example, I have more than 500 figs.
import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure()
fig2 = go.Figure()
fig.add_trace(go.Scatter(y=[4, 2, 1], mode="lines"))
fig2.add_trace(go.Bar(y=[2, 1, 3]))
figs = [fig, fig2]
div = []
for item in figs:
div.append(dcc.Graph(figure=item))
app = dash.Dash()
app.layout = html.Div(div)
"""
add a dropdown to show only one fig
"""
app.run_server(debug=True, use_reloader=False)

Yes, it is possible.
First you need to create the dropdown containing the figure-names / filenames or the identifier you wish, just keep the {'label': x, 'value': x} structure for the option parameter. label is what you will see in the dropdown, and value will be passed to the callback (s. below).
fig_names = ['fig1', 'fig2']
fig_dropdown = html.Div([
dcc.Dropdown(
id='fig_dropdown',
options=[{'label': x, 'value': x} for x in fig_names],
value=None
)])
Next you need a blank div (with an id) where the plot will appear:
fig_plot = html.Div(id='fig_plot')
Now create a callback. When an input with the id='fig_dropdown' is changed, the value parameter will be passed to the update_output function. The output of this function will be passed to passed to the children parameter of the id='fig_plot' div.
#app.callback(
dash.dependencies.Output('fig_plot', 'children'),
[dash.dependencies.Input('fig_dropdown', 'value')])
def update_output(fig_name):
return name_to_figure(fig_name)
The name_to_figure(fig_name) function returns a dcc.Graph() objects, containing your figure, depending on the fig_name value of the dropdown.
Full example:
import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objects as go # or plotly.express as px
app = dash.Dash()
fig_names = ['fig1', 'fig2']
fig_dropdown = html.Div([
dcc.Dropdown(
id='fig_dropdown',
options=[{'label': x, 'value': x} for x in fig_names],
value=None
)])
fig_plot = html.Div(id='fig_plot')
app.layout = html.Div([fig_dropdown, fig_plot])
#app.callback(
dash.dependencies.Output('fig_plot', 'children'),
[dash.dependencies.Input('fig_dropdown', 'value')])
def update_output(fig_name):
return name_to_figure(fig_name)
def name_to_figure(fig_name):
figure = go.Figure()
if fig_name == 'fig1':
figure.add_trace(go.Scatter(y=[4, 2, 1]))
elif fig_name == 'fig2':
figure.add_trace(go.Bar(y=[2, 1, 3]))
return dcc.Graph(figure=figure)
app.run_server(debug=True, use_reloader=False)

Incase you have so many fig to choose from in your Drop Down box, the following changes to the code may be necessary to implement:
#app.callback(Output('fig_plot', 'figure'), [Input('fig_dropdown', 'value')])
def cb(plot_type):
plot_type = plot_type if plot_type else 'fig1'
df_year = head_db.copy()
if plot_type:
return px.bar(df_year, x='Week #', y=str(plot_type), color='Name')

#Libraries/Imports
from dash import Dash, html, dcc, Input, Output
import plotly.graph_objects as go
fig = go.Figure()
fig2 = go.Figure()
fig.add_trace(go.Scatter(y=[4, 2, 1], mode="lines"))
fig2.add_trace(go.Bar(y=2, 1, 3]))
figs = ['fig', 'fig2']
#Your HTML to display the graph
#Disables the multiple dropdown values attributes
app.layout = html.Div([
html.Div(children=[
html.label('Dropdown'),
dcc.Dropdown(id='dropdown', options=(figs), multi=False
html.div(id='show-my-graph')
])
])
#Your callback; is used to display the graph when the dropdown values are selected or updated
#app.callback(
Output(component_id='show-my-graph'), component_property='children'),
Input(component_id='dropdown', component_property='value')
)
#Defines the Function used to display the graph when an option is selected or updated
def update_graph(dropdown_value):
"Returns the appropriate graph component to display when a dropdown is selected or updated"
if(dropdown_value == 'fig'):
ret_val = dcc.Graph(id='scatter-plot-graph', figure=fig)
return ret_val
if (dropdown_value == 'fig2'):
ret_val = dcc.Graph(id='bar-graph', figure=fig2)
return ret_val
app.run_server(debug=True, use_reloader=False)