X-axis rangeslider does not update correctly

đź“Š Plotly Python
1

So I have been trying to get a hang of plotly and the x-axis range slider works until I use a workaround to create a graphic with a secondary y-axis via “make_subplots”.
However now the data that was attached to the secondary y-axis sticks in the range-slider preview. I cannot find a way to force it to be redrawn/refresh, see image attached. Once I refresh my browser it is fixed too, until I go to “both” again.
The code below yields this behavior. Is this itended and did I forget to clean something up?

For reproducibility I can share the data I used if needed.

2025-04-18_172228
2025-04-18_1722281591Ă—1435 169 KB

from dash import Dash, dcc, html, Input, Output, callback
import plotly.express as px
import pandas as pd
from plotly.subplots import make_subplots

df = pd.read_csv(r"D:\t.txt",parse_dates=["Date"])
header = df.columns.values
date_column_name = header[0]
temp_column_name = header[1]
humd_column_name = header[2]

def Populate_Layout(application_handle):
    application_handle.layout = html.Div([
        html.H3(children='Monitoring', style={'textAlign': 'center'}),
        html.Div([

                             html.Div([
                                 dcc.RadioItems(
                                     ['Temperature', 'rel. Humidity', "Both"],
                                     'Temperature',
                                     id='crossfilter-data-shown',
                                     labelStyle={'display': 'inline-block', 'marginTop': '5px'}
                                 )
                             ], style={'width': '49%', 'float': 'right', 'display': 'inline-block'})
                         ], style={
                             'padding': '10px 5px'
                         }),
        html.Div([
            dcc.Graph(id='value_over_time_plot')
        ],style={'width': '50%', 'display': 'inline-block', 'padding': '0 20'}),
        html.Div([
            dcc.Graph(id='value_over_time_plot1')
        ], style={'width': '50%', 'display': 'inline-block', 'padding': '0 20'})
    ])

@callback(
    Output('value_over_time_plot', 'figure'),
    Input('crossfilter-data-shown', 'value'),
    Input('value_over_time_plot', 'figure'),
)
def update_graph(date_type,lineplot=None):#,start_date,end_date):
    start_date = df[date_column_name].min()
    end_date =  df[date_column_name].max()
    dff = df[(df[date_column_name]>start_date) & (df[date_column_name]<end_date)]
    if lineplot is not None:
        lineplot["data"] = []
    if date_type == "Temperature":

        lineplot = px.line(dff, x=date_column_name, y=temp_column_name,render_mode='webg1')
        lineplot["data"][0]["line"]["color"]="#ff0000"
        lineplot.update_traces()
    elif date_type == "Both":
        lineplot = make_subplots(specs=[[{"secondary_y": True}]])
        #lineplot.update_yaxes(title_text="<b>secondary</b> yaxis title", secondary_y=True)
        plot_container = px.line(dff, x=date_column_name, y=humd_column_name,render_mode='webg1')
        for trace in plot_container.select_traces():
            lineplot.add_trace(trace,secondary_y=False)
        plot_container = px.line(dff, x=date_column_name, y=temp_column_name,render_mode='webg1')
        plot_container["data"][0]["line"]["color"]="#ff0000"
        for trace in plot_container.select_traces():
            lineplot.add_trace(trace,secondary_y=True)
    else:
        lineplot = px.line(dff, x=date_column_name, y=humd_column_name,render_mode='webg1')
    lineplot.update_layout(xaxis_rangeslider_visible=True)
    return (lineplot)


if __name__ == "__main__":
    PORT = 8080
    ADDRESS = "127.0.0.84"

    app = Dash(__name__)

    Populate_Layout(application_handle=app)
    app.run(host=ADDRESS,port=PORT,debug=True)
    app.show()