Plotly Weekly & Monthly Range selector buttons not working on time series data
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Description
Hi,
I am having last 1 year time series financial data. I removed weekends as no data is present.
I created plotly viz, 2w,1m range selector buttons are not showing correct time range. While YTD,6m,all showing correct data.
2w button showing 2 week forward days but there is no data, want to see last two week and 1m data.
Reproducable Code-
# !pip install investpy
import pandas as pd
import investpy
import plotly.graph_objects as go
import plotly.figure_factory as ff
import plotly.express as px
today = datetime.now() #Today Datetime
today_fut = today.strftime("%Y,%m,%d") #Converting today date to string format "%Y,%m,%d"
today_fut = datetime. strptime(today_fut, '%Y,%m,%d').date() #Converting today's date to "date" format for NSE Tools library
today = today.strftime("%d/%m/%Y") #Converting today date to string format "%d/%m/%Y"
one_year= datetime.today() - timedelta(days=370) #Subrtracting todays date with 370 Days
one_year = one_year.strftime("%d/%m/%Y") #Converting into string format "%d/%m/%Y"
df = investpy.get_index_historical_data(index="Nifty 50",country="India",from_date=str(one_year),to_date= str(today))
print("Investpy NF Dataframe",df.tail())
bnf = investpy.get_index_historical_data(index="Nifty Bank",country="India",from_date=str(one_year),to_date= str(today))
print("Investpy BNF Dataframe",bnf.tail())
fig = go.Figure(data = [ go.Scatter(x = df.index,y = df['Close'],line=dict(color = 'Steelblue',width=2),mode='lines+markers',name = 'NIFTY'),
go.Scatter(x = bnf.index,y = bnf['Close'],line=dict(color = 'yellowgreen',width=2),mode='lines+markers',name = 'BANK NIFTY'),
])
fig.update_layout(
title='NF and BNF',template = 'plotly_dark',xaxis_tickformat = ' %d %B (%a)<br> %Y',
yaxis_title='NF & BNF',yaxis_tickformat= "000",yaxis_side = 'right',xaxis_title='Date',legend = dict(bgcolor = 'rgba(0,0,0,0)'))
layout = go.Layout(showlegend=True)
##https://plotly.com/python/legend/
fig.update_layout(legend=dict(
yanchor="top",
y=0.99,
xanchor="left",
x=0.01 ))
#hide weekends
fig.update_xaxes( rangeslider_visible=True, rangebreaks=[
dict(bounds=["sat", "mon"]) ])
##https://plotly.com/python/legend/
fig.update_layout(legend=dict(
orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1
))
config = dict({'scrollZoom': False})
fig.update_layout(
xaxis=dict(rangeselector=dict(buttons=list([
dict(count=14,label="2w",step="day",stepmode="todate"),
dict(count=1,label="1m",step="month",stepmode="backward"),
dict(count=3,label="3m",step="month",stepmode="backward"),
dict(count=6,label="6m",step="month",stepmode="backward"),
dict(count=1,label="YTD",step="year",stepmode="todate"),
dict(step="all") ])),rangeslider=dict(visible=True),type="date"))
fig.update_layout(
xaxis_rangeselector_font_color='white',
xaxis_rangeselector_activecolor='red',
xaxis_rangeselector_bgcolor='green',
)
fig.show()
pio.write_html(fig, file='wrong_range_selecor_for-2w&1m_button.html', auto_open=True)
Pls let me know , if there is any bug in plotly range selector or I am doing something wrong in
xaxis=dict(rangeselector=dict(buttons=list([xaxis=dict(rangeselector=dict(buttons=list([ code.
I tried dict(count=14,label="2w",step="day",stepmode="backward") but still same issue.
Snaps-
When I click on 2w but it show future dates, where no data is present in dataframe.

1m button snap-

Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by running the reproducible Python example with the xaxis.rangeselector buttons and rangebreaks configuration shown in the issue. Compare the todate and backward behaviors for the 2w and 1m buttons on the trading-day index; done means the selected ranges end at the latest available data and show the intended historical period.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- plotly, python
- Domain
- data-visualization
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100