Plotly：如何向烛台图表添加交易量

问题描述 投票：0回答：5

代码：

from plotly.offline import init_notebook_mode, iplot, iplot_mpl
    
def plot_train_test(train, test, date_split):
    data = [Candlestick(x=train.index, open=train['open'], high=train['high'], low=train['low'], close=train['close'],name='train'),
           Candlestick(x=test.index, open=test['open'], high=test['high'], low=test['low'], close=test['close'],name='test')
            ]
            layout = {
                'shapes': [
                    {'x0': date_split, 'x1': date_split, 'y0': 0, 'y1': 1, 'xref': 'x', 'yref': 'paper',
                     'line': {'color': 'rgb(0,0,0)', 'width': 1}}],
                'annotations': [{'x': date_split, 'y': 1.0, 'xref': 'x', 'yref': 'paper', 'showarrow': False, 'xanchor': 'left','text': ' test data'},
                    {'x': date_split, 'y': 1.0, 'xref': 'x', 'yref': 'paper', 'showarrow': False, 'xanchor': 'right', 'text': 'train data '}] }
            figure = Figure(data=data, layout=layout)
            iplot(figure)

上面的代码没问题。但现在我想在这个烛台图表中“成交量”

代码：

from plotly.offline import init_notebook_mode, iplot, iplot_mpl
        
def plot_train_test(train, test, date_split):
    data = [Candlestick(x=train.index, open=train['open'], high=train['high'], low=train['low'], close=train['close'],volume=train['volume'],name='train'),
           Candlestick(x=test.index, open=test['open'], high=test['high'], low=test['low'],close=test['close'],volume=test['volume'],name='test')]
            layout = {
                'shapes': [
                    {'x0': date_split, 'x1': date_split, 'y0': 0, 'y1': 1, 'xref': 'x', 'yref': 'paper',
                     'line': {'color': 'rgb(0,0,0)', 'width': 1}}
                ],
                'annotations': [
                    {'x': date_split, 'y': 1.0, 'xref': 'x', 'yref': 'paper', 'showarrow': False, 'xanchor': 'left',
                     'text': ' test data'},
                    {'x': date_split, 'y': 1.0, 'xref': 'x', 'yref': 'paper', 'showarrow': False, 'xanchor': 'right',
                     'text': 'train data '}
                ]
            }
            figure = Figure(data=data, layout=layout)
            iplot(figure)

错误：

ValueError：为类型对象指定的属性无效 plotly.graph_objs.Candlestick：'体积'

python matplotlib plot plotly
5个回答
30
投票

如果您想在 OHLC 图表下方添加较小的交易量子图，您可以使用：

    rows
  1. 和 
    cols
    指定子图的网格。
    2. shared_xaxes=True
  2.  用于相同的缩放和过滤
    3. row_width=[0.2, 0.7]
  3.  更改图表的高度比例。 IE。体积图表比 OHLC 更小
    

剧情：


import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots

# data
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')


# Create subplots and mention plot grid size
fig = make_subplots(rows=2, cols=1, shared_xaxes=True, 
               vertical_spacing=0.03, subplot_titles=('OHLC', 'Volume'), 
               row_width=[0.2, 0.7])

# Plot OHLC on 1st row
fig.add_trace(go.Candlestick(x=df["Date"], open=df["AAPL.Open"], high=df["AAPL.High"],
                low=df["AAPL.Low"], close=df["AAPL.Close"], name="OHLC"), 
                row=1, col=1
)

# Bar trace for volumes on 2nd row without legend
fig.add_trace(go.Bar(x=df['Date'], y=df['AAPL.Volume'], showlegend=False), row=2, col=1)

# Do not show OHLC's rangeslider plot 
fig.update(layout_xaxis_rangeslider_visible=False)
fig.show()


    



    

    
    
    

    

        

            

                

                    
26
投票

                    

                

            

        

        
此处
。
无论如何，您收到该错误消息只是因为 
go.Candlestick
 没有 
Volume
 属性。一开始可能看起来并非如此，但您可以轻松地将 
go.Candlestick
 设置为单独的跟踪，然后使用以下方法为卷添加单独的 
go.Bar()
 跟踪：


    fig = make_subplots(specs=[[{"secondary_y": True}]])
    2. fig.add_traces(go.Candlestick(...), secondary_y=True)
    3. fig.add_traces(go.Bar(...), secondary_y=False)
  3. 

    4. 剧情：



完整代码：


import plotly.graph_objects as go
from plotly.subplots import make_subplots
import pandas as pd

# data
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')

# Create figure with secondary y-axis
fig = make_subplots(specs=[[{"secondary_y": True}]])

# include candlestick with rangeselector
fig.add_trace(go.Candlestick(x=df['Date'],
                open=df['AAPL.Open'], high=df['AAPL.High'],
                low=df['AAPL.Low'], close=df['AAPL.Close']),
               secondary_y=True)

# include a go.Bar trace for volumes
fig.add_trace(go.Bar(x=df['Date'], y=df['AAPL.Volume']),
               secondary_y=False)

fig.layout.yaxis2.showgrid=False
fig.show()


    



    

    
    
    

    

        

            

                

                    
3
投票

                    
                

            

        

        


import plotly.graph_objects as go
from plotly.subplots import make_subplots

candlesticks = go.Candlestick(
    x=candles.index,
    open=candles['open'],
    high=candles['high'],
    low=candles['low'],
    close=candles['close'],
    showlegend=False
)

volume_bars = go.Bar(
    x=candles.index,
    y=candles['volume'],
    showlegend=False,
    marker={
        "color": "rgba(128,128,128,0.5)",
    }
)

fig = go.Figure(candlesticks)
fig = make_subplots(specs=[[{"secondary_y": True}]])
fig.add_trace(candlesticks, secondary_y=True)
fig.add_trace(volume_bars, secondary_y=False)
fig.update_layout(
    title="ETH/USDC pool price data at the very beginning of Uniswap v3",
    height=800,
    # Hide Plotly scrolling minimap below the price chart
    xaxis={"rangeslider": {"visible": False}},
)
fig.update_yaxes(title="Price $", secondary_y=True, showgrid=True)
fig.update_yaxes(title="Volume $", secondary_y=False, showgrid=False)


fig.show()





您可以在此开源笔记本中找到完整的源代码
。
    




    

    
    
    

    

        

            

                

                    
1
投票

                    
                

            

        

        


    import plotly.graph_objects as go
    from plotly.subplots import make_subplots
    import pandas as pd
    # Create subplots and mention plot grid size
    title=df.symbol.unique()[0]

    fig = make_subplots(rows=2, cols=1, shared_xaxes=True, 
               vertical_spacing=0.02, 
               row_width=[0.25, 0.75])

    # Plot OHLC on 1st row
    fig.add_trace(go.Candlestick(x=df.index,
                    open=df['open'], high=df['high'],
                    low=df['low'], close=df['close'],showlegend=False),row=1, col=1,)

    # Bar trace for volumes on 2nd row without legend
    # fig.add_trace(go.Bar(x=df.index, y=df['volume'], showlegend=False), row=2, col=1)

    df['color']=''
    df['color']=['red' if (x>y) else t for x,y,t in zip(df['open'],df['close'],df['color'])]
    df['color']=['green' if (x<y) else t for x,y,t in zip(df['open'],df['close'],df['color'])]
    colors=df.color.tolist()
    df['prev_color']=[colors[0]]+colors[:(len(colors)-1)]
    df.loc[((df.open==df.close) & (df.color=='')),'color']=[z for x,y,z,t in zip(df['open'],df['close'],df['prev_color'],df['color']) if (x==y and t=='')]
    colors=df.color.tolist()
    df['prev_color']=[colors[0]]+colors[:(len(colors)-1)]
    df.loc[((df.open==df.close) & (df.color=='')),'color']=[z for x,y,z,t in zip(df['open'],df['close'],df['prev_color'],df['color']) if (x==y and t=='')]
    
    markers=['green','red']

    for t in markers:
        df_tmp=df.loc[~(df.color==t)] ## somehow the color it takes is opposite so take negation to 
        fig.add_trace(go.Bar(x=df_tmp.index, y=df_tmp['volume'], showlegend=False), row=2, col=1)

    # Do not show OHLC's rangeslider plot 
    fig.update(layout_xaxis_rangeslider_visible=False)
    fig.layout.yaxis2.showgrid=False
    fig.update_layout(title_text=title,title_x=0.45)

    fig.show()


    



    

    
    
    

    

        

            

                

                    
0
投票

                    
                

            

        

        
marker_color
。想想看，是什么让蜡烛变成绿色的？收盘价高于开盘价这一事实，以及红色蜡烛又如何呢？好吧，收盘价低于开盘价，所以有了这个基础知识：
import plotly.graph_objects as go
from plotly.subplots import make_subplots

# Create a Figure with 2 subplots, one will contain the candles
# the other will contain the Volume bars
figure = make_subplots(rows=2, cols=1, shared_xaxes=True, row_heights=[0.7, 0.3])

# Plot the candles in the first subplot
figure.add_trace(go.Candlestick(x=df.index, open=df.open, high=df.high, low=df.low, close=df.close, name='price',
                                increasing_line_color='#26a69a', decreasing_line_color='#ef5350'),
                 row=1, col=1)

# From our Dataframe take only the rows where the Close > Open
# save it in different Dataframe, these should be green
green_volume_df = df[df['close'] > df['open']]
# Same for Close < Open, these are red candles/bars
red_volume_df = df[df['close'] < df['open']]

# Plot the red bars and green bars in the second subplot
figure.add_trace(go.Bar(x=red_volume_df.index, y=red_volume_df.volume, showlegend=False, marker_color='#ef5350'), row=2,
                 col=1)
figure.add_trace(go.Bar(x=green_volume_df.index, y=green_volume_df.volume, showlegend=False, marker_color='#26a69a'),
                 row=2, col=1)

# Hide the Range Slider
figure.update(layout_xaxis_rangeslider_visible=False)
figure.update_layout(title=f'BTC/USDT', yaxis_title=f'Price')
figure.update_yaxes(title_text=f'Volume', row=2, col=1)
figure.update_xaxes(title_text='Date', row=2)



参考文献




    https://plotly.com/python/subplots/
  • 

    • https://plotly.com/python/candlestick-charts/
  • 

    
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