Plotly：如何將交易量添加到燭台圖表

Question

代碼：

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)

上面的代碼沒問題。但現在我想在此燭台圖表中“交易量”

代碼：

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) 

錯誤：

ValueError：為 plotly.graph_objs.Candlestick 類型的 object 指定的無效屬性：'volume'

Answer 1

您還沒有提供一個完整的代碼段與數據樣本，所以我不得不認為，建立在一個示例的解決方案在這里。

在任何情況下，您都會收到該錯誤消息，因為go.Candlestick沒有Volume屬性。 乍一看似乎並非如此，但您可以輕松地將go.Candlestick設置為單獨的跟蹤，然后使用以下方法為 Volumes 包含單獨的go.Bar()跟蹤：

1. 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)

陰謀：

完整代碼：

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()

Answer 2

如果您想在 OHLC 圖表下方添加較小的體積子圖，您可以使用：

1. rows和cols指定次要情節電網。
2. shared_xaxes=True用於相同的縮放和過濾
3. row_width=[0.2, 0.7]改變圖表的高度比例。 IE。 體積圖比 OHLC 小

陰謀：

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()

Answer 3

這是我根據 Vestland 之前的回答進行的改進實施，其中包含一些標簽和着色改進。

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 after Uniswap v3 deployment", height=800)
fig.update_yaxes(title="Price $", secondary_y=True, showgrid=True)
fig.update_yaxes(title="Volume $", secondary_y=False, showgrid=False)
fig.show()

您可以在這個開源筆記本中找到完整的源代碼。

Answer 4

如果您想為買/賣添加不同的顏色，例如“綠色”/“紅色”，您可以使用一些庫（例如 mplfinance）自動執行這些操作，但是這些圖是非交互式的。 要獲得具有不同顏色的買/賣顏色的交互式繪圖，需要為每個數據點添加跟蹤。 這是代碼：

    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()

Answer 5

我在 colors 的不同子圖中的 Plotting Volume 上的兩分錢，它只是使 @user6397960 響應更短而無需黑客獲得正確的顏色，只需使用marker_color 。 想一想，是什么讓蠟燭變綠？ 收盤價高於開盤價的事實，紅色蠟燭呢？ 好吧，收盤價低於開盤價，所以有了這個基礎知識：

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)

參考

• https://plotly.com/python/subplots/
• https://plotly.com/python/燭台圖表/