在同一图形上绘制直方图和折线图

问题描述 投票:1回答:1

您好,我试图在同一图上绘制直方图和折线图以创建MACD图表。但是,直方图数据需要按比例缩小,因此它不会超过线条。有没有办法缩小直方图而不缩小数据框中的数据? enter image description here

t.head()

            Date    macd    macds   macdh
index               
0   2020-03-02  0.000000    0.000000    0.000000
1   2020-02-28  0.005048    0.002804    0.002244
2   2020-02-27  -0.000080   0.001622    -0.001702
3   2020-02-26  0.016184    0.006555    0.009629
4   2020-02-25  0.023089    0.011473    0.011615



fig = go.Figure()
fig.add_trace(go.Histogram(
            x=t['Date'],
            y=t['macdh'],

           ))

fig.add_trace(go.Scatter(
            x=t['Date'],
            y=t['macd'],

            line_color='dimgray',
            opacity=0.8))

fig.add_trace(go.Scatter(
            x=t['Date'],
            y=t['macds'],
            line_color='deepskyblue',
            opacity=0.8
            ))

fig.show()
python plotly
1个回答
1
投票

为了确保绝对确保不同的数据类别不会互相干扰,我更喜欢使用单个子图来设置它们,而不是使用混合的y轴图来设置它们。这是一个例子:

enter image description here

完整代码:

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

pio.templates.default = "plotly_white"
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')

fig = make_subplots(vertical_spacing = 0, rows=3, cols=1, row_heights=[0.6, 0.2, 0.2])

fig.add_trace(go.Candlestick(x=df['Date'],
                              open=df['AAPL.Open'],
                              high=df['AAPL.High'],
                              low=df['AAPL.Low'],
                              close=df['AAPL.Close']))

fig.add_trace(go.Scatter(x=df['Date'], y = df['mavg']), row=2, col=1)
fig.add_trace(go.Scatter(x=df['Date'], y = df['mavg']*1.1), row=2, col=1)
fig.add_trace(go.Bar(x=df['Date'], y = df['AAPL.Volume']), row=3, col=1)

fig.update_layout(xaxis_rangeslider_visible=False,
                  xaxis=dict(zerolinecolor='black', showticklabels=False),
                  xaxis2=dict(showticklabels=False))

fig.update_xaxes(showline=True, linewidth=1, linecolor='black', mirror=False)

fig.show()
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