python - 具有公共、时间对齐的共享轴的 mplfinance 堆叠图

Question

我正在绘制 5、15、30 和 60 分钟蜡烛的堆叠图。

我想请：

1. 让所有价格图表都右对齐（y_on_right=True似乎没有使用）
2. 对于 5 分钟图表上的时间/网格，每小时每 60 分钟
3. 对于所有其他图表使用与上述相同的，每 60 分钟，全部对齐
4. 如果可能的话，可以选择删除左侧和右侧的空间（因此第一个栏靠左边缘，最后一个栏靠右边缘）

到目前为止，这是我的输出：

代码如下：

import mplfinance as mpf
import pandas as pd
from polygon import RESTClient

def main():
    key = "key"

    with RESTClient(key) as client:
        start = "2019-02-01"
        end = "2019-02-02"
        ticker = "TVIX"
        resp5 = client.stocks_equities_aggregates(ticker, 5, "minute", start, end, unadjusted=False)
        resp15 = client.stocks_equities_aggregates(ticker, 15, "minute", start, end, unadjusted=False)
        resp30 = client.stocks_equities_aggregates(ticker, 30, "minute", start, end, unadjusted=False)
        resp60 = client.stocks_equities_aggregates(ticker, 60, "minute", start, end, unadjusted=False)
        print(f'5 min data is {len(resp5.results)} long')
        print(f'15 min data is {len(resp15.results)} long')
        print(f'30 min data is {len(resp30.results)} long')
        print(f'60 min data is {len(resp60.results)} long')
        
        df5 = pd.DataFrame(resp5.results)
        df5.index = pd.DatetimeIndex( pd.to_datetime(df5['t']/1000, unit='s') )

        df15 = pd.DataFrame(resp15.results)
        df15.index = pd.DatetimeIndex( pd.to_datetime(df15['t']/1000, unit='s') )

        df30 = pd.DataFrame(resp30.results)
        df30.index = pd.DatetimeIndex( pd.to_datetime(df30['t']/1000, unit='s') )

        df60 = pd.DataFrame(resp60.results)
        df60.index = pd.DatetimeIndex( pd.to_datetime(df60['t']/1000, unit='s') )
        
        df60.index.name = df30.index.name = df15.index.name = df5.index.name = 'Timestamp'   
        # mpf expects a dataframe containing Open, High, Low, and Close data with a Pandas TimetimeIndex
        df60.columns = df30.columns = df15.columns = df5.columns = ['Volume', 'Volume Weighted', 'Open', 'Close', 'High', 'Low', 'Time', 'Num Items']
        
        fig = mpf.figure(figsize=(32, 32))
        ax1 = fig.add_subplot(4, 1, 1)
        ax2 = fig.add_subplot(4, 1, 2)
        ax3 = fig.add_subplot(4, 1, 3)
        ax4 = fig.add_subplot(4, 1, 4)
        
        ap = [
                mpf.make_addplot(df15, type='candle', ax=ax2, y_on_right=True),
                mpf.make_addplot(df30, type='candle', ax=ax3, y_on_right=True),
                mpf.make_addplot(df60, type='candle', ax=ax4, y_on_right=True)
            ]
        
        s = mpf.make_mpf_style(base_mpf_style='default',y_on_right=True)
        mpf.plot(df5, style=s, ax=ax1, addplot=ap, xrotation=0, datetime_format='%H:%M', type='candlestick')              

if __name__ == '__main__':
    main()

Answer 1

我没有对应的 API 密钥，所以我使用了雅虎财经的股票价格。至于将价格放在右侧的问题，您可以更改样式来实现这一点。此外，这似乎y_on_right只对第一张图有效。从这个信息。要删除第一个和最后一个边距，请使用tight_layout=True，并将 x 轴与小时对齐，您需要检查 mpl 时间序列格式化程序可以走多远。

import yfinance as yf
import pandas as pd
import mplfinance as mpf
import numpy as np
import datetime
import matplotlib.dates as mdates

start = '2021-12-22'
end = '2021-12-23'
intervals = [5,15,30,60]

for i in intervals:
    vars()[f'df{i}'] = yf.download("AAPL", start=start, end=end, period='1d', interval=str(i)+'m')

for df in [df5,df15,df30,df60]:    
    df.index = pd.to_datetime(df.index)
    df.index = df.index.tz_localize(None)

df5 = df5[df5.index.date == datetime.date(2021,12,21)]
df15 = df15[df15.index.date == datetime.date(2021,12,21)]
df30 = df30[df30.index.date == datetime.date(2021,12,21)]
df60 = df60[df60.index.date == datetime.date(2021,12,21)]

fig = mpf.figure(style='yahoo', figsize=(12,9))
ax1 = fig.add_subplot(4,1,1)
ax2 = fig.add_subplot(4,1,2)
ax3 = fig.add_subplot(4,1,3)
ax4 = fig.add_subplot(4,1,4)

mpf.plot(df5, type='candle', ax=ax1, xrotation=0, datetime_format='%H:%M', tight_layout=True)
mpf.plot(df15, type='candle', ax=ax2, xrotation=0, datetime_format='%H:%M', tight_layout=True)
mpf.plot(df30, type='candle', ax=ax3, xrotation=0, datetime_format='%H:%M', tight_layout=True)
mpf.plot(df60, type='candle', ax=ax4, xrotation=0, datetime_format='%H:%M', tight_layout=True)

ax3_ticks = ax3.get_xticks()
print(ax3_ticks)