绘制烛台更新并在循环中动态显示

发布于 2025-01-31 16:27:51 字数 852 浏览 3 评论 0原文

我想从plotly中动态更新candlestick图表：

import time
import plotly.graph_objects as go

while True:
  candle_df = candle_handler.get_dataframe()
  candlestick = go.Candlestick(x=candle_df['Time'], open=candle_df['Open'], high=candle_df['High'], low=candle_df['Low'], close=candle_df['Close'])  
  fig = go.Figure(data=[candlestick])
  fig.show()
  time.sleep(3)

其中candle_handler.get_dataframe（）从API中提取数据并在candle_df pandas dataframe。

但是，在循环的每次迭代中，图表仅显示非常简短（比3秒钟少得多）。

我找到了一个适用于散点图的片段：

import time
import plotly.graph_objects as go

data = [1,3,2,4,3,3,2,3]

fig = go.FigureWidget()
fig.add_scatter()

for i in range(len(data)):
  time.sleep(3)
  fig.data[0].y = data[:i]
  fig.show()

我想为Candlestick图表做类似的事情。

原文

I would like to dynamically update a Candlestick chart from plotly:

import time
import plotly.graph_objects as go

while True:
  candle_df = candle_handler.get_dataframe()
  candlestick = go.Candlestick(x=candle_df['Time'], open=candle_df['Open'], high=candle_df['High'], low=candle_df['Low'], close=candle_df['Close'])  
  fig = go.Figure(data=[candlestick])
  fig.show()
  time.sleep(3)

where candle_handler.get_dataframe() pull the data from an API and updates the data in the candle_df pandas dataframe.

However, the chart is shown only very briefly at every iteration of the loop (much less than for 3 seconds).

I have found a snippet that works for a scatter plot:

import time
import plotly.graph_objects as go

data = [1,3,2,4,3,3,2,3]

fig = go.FigureWidget()
fig.add_scatter()

for i in range(len(data)):
  time.sleep(3)
  fig.data[0].y = data[:i]
  fig.show()

and I would like to do something similar for the Candlestick chart.

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我偏爱纯白色 2025-02-07 16:27:51

您的代码对我来说很好。顺便说一句，我嘲笑您的系列数据 - 当提出这样的问题提供一些示例数据时，

    import time
    
    import numpy as np
    import pandas as pd
    import plotly.graph_objects as go
    import datetime
    
    class Handler:
      def get_dataframe(self):
        start = datetime.datetime(2011, 1, 1)
        tim_col = pd.date_range(start, periods=500, freq="D")
        tim_col.name = "Time"
        prices_df = pd.DataFrame(data=np.random.rand(500,4), columns=['Open','High','Low','Close'], index=tim_col).reset_index()
        prices_df['Open'] = prices_df['Open']+ prices_df['Low']
        prices_df['Close'] = prices_df['Close']+ prices_df['Low']
        prices_df['High'] = prices_df['High']+ prices_df[['Open','Close']].max(axis=1)
        return prices_df
    
    candle_handler = Handler()
    
    while True:
      candle_df = candle_handler.get_dataframe()
      candlestick = go.Candlestick(x=candle_df['Time'], open=candle_df['Open'], high=candle_df['High'], low=candle_df['Low'], close=candle_df['Close'])
      fig = go.Figure(data=[candlestick])
      fig.show()
      time.sleep(3)

这确实是每3秒钟的绘制数据。确切的行为将取决于您的图形渲染器。如果您在终端中运行它，它可能会在浏览器中弹出一个选项卡，查看每个循环中的Localhost，可能不是您想要的。如果您在jupyter笔记本中运行它，它将动态更改一个数字，这可能更接近您想要的东西。

如果要动态更新浏览器中的数字，则可以考虑查看 dash

Your code worked perfectly fine for me. As an aside, I mocked up some data for your series - it's good practice when asking a question like this to provide some sample data

    import time
    
    import numpy as np
    import pandas as pd
    import plotly.graph_objects as go
    import datetime
    
    class Handler:
      def get_dataframe(self):
        start = datetime.datetime(2011, 1, 1)
        tim_col = pd.date_range(start, periods=500, freq="D")
        tim_col.name = "Time"
        prices_df = pd.DataFrame(data=np.random.rand(500,4), columns=['Open','High','Low','Close'], index=tim_col).reset_index()
        prices_df['Open'] = prices_df['Open']+ prices_df['Low']
        prices_df['Close'] = prices_df['Close']+ prices_df['Low']
        prices_df['High'] = prices_df['High']+ prices_df[['Open','Close']].max(axis=1)
        return prices_df
    
    candle_handler = Handler()
    
    while True:
      candle_df = candle_handler.get_dataframe()
      candlestick = go.Candlestick(x=candle_df['Time'], open=candle_df['Open'], high=candle_df['High'], low=candle_df['Low'], close=candle_df['Close'])
      fig = go.Figure(data=[candlestick])
      fig.show()
      time.sleep(3)

This does indeed ahow a graph every 3 seconds. Exact behaviour is going to depend on your graph renderer. If you run it in the terminal, it will probably pop up a tab in your browser looking at localhost on every loop - probably not what you want. If you run it in a Jupyter Notebook, it will change a figure dynamically, which might be closer to what you want.

If you want to dynamically update a figure in the browser, you might consider looking at dash

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