with JS lightweight charts one can change how precise you want the price to be by:

priceFormat: { precision: 6, minMove: 0.000001 }

but I don't see that option here.

In the below example, 2 decimal points does not tell enough information

Hi, just started using this library and everything looks great! just wanted to know how I could add horizontal lines onto the chart to mark support and resistance zones programmatically. I already have the data for these zones, I just want to mark them. I tried to use the mark_line function to do so but is there a better way of marking the zones?

I made a basic candlestick chart with volume parameter but my volume histogram heights are huge. I tried to put them much lower places with bigger percentage values such as .9 from top but nothing changed. I need quick help please

hi, i can see the chart working in Colab, however in local environment, it's not showing. do you know the reason why? is this related to javascript execution permission?

When you try to add an annotations with this code:

DailyChart = DailyChart.mark_annotation(data=pd.DataFrame({'time':{1: 1656666900}, 'position':{1: 'belowBar'}, 'color': {1: '#2196F3'}, 'shape': {1:'arrowUp'}, 'text': {1:'TEST'}}))

You get this error:

AttributeError: 'Series' object has no attribute 'markers'

This is due to an typing error on _markers variable, you should replace on line 140 this line:

self.markers.append(markers)

by this:

self._markers.append(markers)

By the way when you change the variable name and test again you get this error:

TypeError: DataFrame.to_dict() got an unexpected keyword argument 'date_format'

This is because the argument date_format don't seems to exist in to_dict function.

You should change this line number 106 by removing this argument:

    } for marker in self._data.to_dict(orient='records')]

FYI: I'm not allow to create a Pull request on you repo, so I did a fork about this: https://github.com/electrotiti/pytvlwcharts

Hello,

Firstly, I would like to express my appreciation for the excellent work you've done with this project. I am very pleased with its functionality.

However, I am writing to inquire about a feature that I think could further enhance this project. I've been trying to generate multi-pane charts for use with various indicators like the Moving Average Convergence Divergence (MACD), but it seems the current version of the project does not support this directly.

The idea is that the main chart can contain OHLC and Volume information while the smaller panes can contain indicators like MACD, RSI, etc.

Before attempting to implement this myself or seeking an alternative solution, I wanted to check with you if this feature is on the roadmap. If it's not, could you consider adding it?

Please let me know your thoughts on this, and if there is a potential workaround I could use in the meantime.

Thanks

I found this code on the Jinja template which creates the price lines and sets the markers in the chart but I could not find any related function. How can I use this ability in this library?

   chart_series.setMarkers(
     {{ series.markers }}
   );
   {% for price_line in series.price_lines %}
   chart_series.createPriceLine({{ price_line }});
   chart.subscribeCrosshairMove(param => {
       if (param.time) console.log(param.seriesPrices.get(chart_series))
    });
   {% endfor %}

I would like to display graphs for multiple stocks each in pytvlwcharts. Is there a way?

Usually, the DataFrames have the "time" in the index. This means we always have to do something like:

df.reset_index().rename(columns={"Date": "time", "Open": 'open', "High": 'high', "Low": 'low', "Close": 'close'}),

I think some heuristics could help:

1. check if the index is of type Timestamp -> use as x
2. check if any other column is of type Timestamp -> use as x

Something similar should be used for the marks, i.e. use the first 4 columns for candles and the first one for a line.

At least as a user I should be able to conveniently declare my column names/index which should be used I think.

Nevertheless, I think using lightweight charts with python (notebooks) will greatly improve financial plots over mplf, plotly and others.

i tried the demo notebook
didnt render anything
python 3.10
mac m1

there's no chart showing in Jupyter currently. only "made by DrJuneMoone". I double checked, the data is correct.

Is there a way to add a series marker like this: https://tradingview.github.io/lightweight-charts/tutorials/how_to/series-markers#full-example

I don't see any example but I can see there is a mark_annotation function inside the Series call. Can you show an example of how to add markers?