我有一个破折号的仪表板,我似乎无法重新缩放我的辅助y轴。有办法吗? 我试图弄乱go.Layout中的domain参数和range参数。 我需要将音量条形图缩小并占据图表高度的10%,以便它不与我的烛台重叠。
非常感谢。 任何帮助表示赞赏。
import pandas as pd
import pandas_datareader.data as web
import plotly.offline as pyo
import plotly.graph_objs as go
stock_ticker='AAPL'
start_date='2019-04-01'
end_date='2019-05-22'
data=[]
hist_stock_df = web.DataReader(stock_ticker,'iex',start_date, end_date)
data.append(go.Candlestick(x=hist_stock_df.index,
open=hist_stock_df['open'],
high=hist_stock_df['high'],
low=hist_stock_df['low'],
close=hist_stock_df['close'],
name='AAPL'))
data.append(go.Bar(x=hist_stock_df.index,
y=hist_stock_df['volume'].values,
yaxis='y2'))
#y0=1000000
layout=go.Layout(title= 'Candestick Chart of AAPL',
xaxis=dict(title='Date',rangeslider=dict(visible=False)),
yaxis=dict(title='Price'),
plot_bgcolor='#9b9b9b',
paper_bgcolor='#9b9b9b',
font=dict(color='#c4c4c4'),
yaxis2=dict(title='Volume',
overlaying='y',
side='right'))
#scaleanchor='y'))
#scaleratio=0.00000001,
#rangemode='tozero',
#constraintoward='bottom',
#domain=[0,0.1]))
fig = go.Figure(data=data, layout=layout)
pyo.iplot(fig)
我尝试弄乱注释的参数
更新
使用这种布局参数组合,我设法重新调整了条形图的比例,但是现在有两个x轴,试图找出如何使中间的x轴向下。
layout=go.Layout(title= 'Candestick Chart of AAPL',
xaxis=dict(title='Date',rangeslider=dict(visible=False)),
yaxis=dict(title='Price'),
plot_bgcolor='#9b9b9b',
paper_bgcolor='#9b9b9b',
font=dict(color='#c4c4c4'),
yaxis2=dict(title='Volume',
overlaying='y',
side='right',
scaleanchor='y',
scaleratio=0.0000001))
答案 0 :(得分:1)
在secondary_y=Boolean
中使用fig.update_yaxes()
指定要调整的轴。
图1: 没有手动调整
图2: 具有手动调整
代码:
from plotly.subplots import make_subplots
import plotly.graph_objects as go
import pandas as pd
import numpy as np
import datetime
# data
np.random.seed(1234)
numdays=20
dates = pd.date_range('1/1/2020', periods=numdays)
A = (np.random.randint(low=-10, high=10, size=numdays).cumsum()+100).tolist()
B = (np.random.randint(low=0, high=100, size=numdays).tolist())
df = pd.DataFrame({'A': A,'B':B}, index=dates)
# plotly figure setup
fig = make_subplots(specs=[[{"secondary_y": True}]])
fig.add_trace(go.Scatter(name='A', x=df.index, y=df['A'].values))
fig.add_trace(go.Bar(name='B', x=df.index, y=df['B'].values), secondary_y=True)
# plotly manual axis adjustments
fig.update_yaxes(range=[50,160], secondary_y=False)
fig.update_yaxes(range=[-10,200], secondary_y=True)
fig.show()