plotting stock data in plot.ly

Question

I am trying to plot candlestick and simple moving average data using plot.ly as you see in the chart, there is empty value line plotted where there is no date/price data available actually. the data for this chart is also shown.

So in chart, you can see that the non-trading hours are also plotted. How to avoid this?

stock chart

stock data in pandas dataframe

Please show data and code as text, not image. The graph is fine — Mad Physicist, Jul 27 '18 at 04:48
i was not able to properly post the dataframe output data. it was not readable. so posted an image of the table. i will keep this in mind. thanks — Shivaprashanth Hiremath, Jul 28 '18 at 09:49
You posted a picture of console output. Copy it and format it as code. If I want to create a test on my machine, I can't copy the image. — Mad Physicist, Jul 28 '18 at 14:42

score 0 · Answer 1 · answered Jul 27 '18 at 03:35

0

Plotly doesn't seem to support just hidding gaps with no data, as you can see from this discussion in the plotly community

The answer on this SO removes the gap by entering explicit null values for every index where the data is empty.

answered Jul 27 '18 at 03:35

PabTorre

2,878
21
30

in my case the input data is from historical candle data and unfortunately i can not add null values or modify the input data in any way. as a work around to insert null values, i will have to first capture the historical candle data into a csv and add null values and then read that csv back into dataframes before plotting. – Shivaprashanth Hiremath Jul 28 '18 at 10:49
1

@Shivaprashanth. That doesn't make sense. Dataframes are writable. If yours isn't, make a copy that it. Do the operation in memory. – Mad Physicist Jul 28 '18 at 14:44
i guess thats what i have to do. will try that. Thanks @MadPhysicist – Shivaprashanth Hiremath Jul 28 '18 at 16:39

score 0 · Answer 2 · answered Mar 31 '21 at 22:53

you can use the following code that helped me

fig = go.Figure(data=[go.Candlestick(
x=dataset_5.index,
open=dataset_5['open'], 
high=dataset_5['high'],
low=dataset_5['low'], 
close=dataset_5['close'])])
fig.update_xaxes(rangeslider_visible=True,
    rangebreaks=[
        # NOTE: Below values are bound (not single values), ie. hide x to y
        dict(bounds=["sat", "mon"]),  # hide weekends, eg. hide sat to before mon
        dict(bounds=[18, 9.0], pattern="hour"),  # hide hours outside of 9.30am-4pm
        # dict(values=["2019-12-25", "2020-12-24"])  # hide holidays (Christmas and 
        New Year's, etc)
     ]
  )
  fig.update_layout(xaxis_rangeslider_visible=True)
  fig.show()

plotting stock data in plot.ly

2 Answers2