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python - 如何使用stockstats查看MACD信号?

转载 作者:行者123 更新时间:2023-12-04 12:25:12 26 4
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我正在尝试绘制 Macd 指标。我正在使用 stockstats 来绘制它。但我只能看到 Macd 值。(如果你也帮我添加它,我会很高兴)我怎么能看到 MACD_EMA_SHORT、MACD_EMA_LONG、MACD_EMA_SIGNAL 与股票统计?
并试图像图片一样绘制它。

enter image description here

以下是我的尝试:

import matplotlib.pyplot as plt
from matplotlib import style
import matplotlib.dates as mdates
import pandas as pd
import requests
from stockstats import StockDataFrame as sdf

periods = '3600'
resp = requests.get('https://api.cryptowat.ch/markets/poloniex/ethusdt/ohlc', params={'periods': periods})
data=resp.json()
df = pd.DataFrame(data['result'][periods], columns=[
'CloseTime', 'Open', 'High', 'Low', 'Close', 'Volume','Adj Volume'])
df.to_csv('eth.csv')
df=pd.read_csv('eth.csv', parse_dates=True,index_col=0)
df.columns = df.columns.str.strip()
df['CloseTime'] = pd.to_datetime(df['CloseTime'], unit='s')
df = df.set_index('CloseTime')
#print(df.tail(6))


data=pd.read_csv('eth.csv')

stock=sdf.retype(data)
signal=stock['macd_ema_short']

df.dropna(inplace=True)
print(signal)

错误:

KeyError: 'macd_ema_short'

最佳答案

MACD_EMA_SHORT 只是一个类方法

  • 你无法得到它,除非你更新 class
  • 您需要返回 fast = df[ema_short]
  • MACD_EMA_SHORT 是用于 _get_macd 中的计算的参数
  • MACD_EMA_SHORT = 12
  • ema_short = 'close_{}_ema'.format(cls.MACD_EMA_SHORT)
  • ema_short = 'close_12_ema'

  • class StockDataFrame(pd.DataFrame):
    OPERATORS = ['le', 'ge', 'lt', 'gt', 'eq', 'ne']

    # Start of options.
    KDJ_PARAM = (2.0 / 3.0, 1.0 / 3.0)
    KDJ_WINDOW = 9

    BOLL_PERIOD = 20
    BOLL_STD_TIMES = 2

    MACD_EMA_SHORT = 12
    MACD_EMA_LONG = 26
    MACD_EMA_SIGNAL = 9

        @classmethod
    def _get_macd(cls, df):
    """ Moving Average Convergence Divergence
    This function will initialize all following columns.
    MACD Line (macd): (12-day EMA - 26-day EMA)
    Signal Line (macds): 9-day EMA of MACD Line
    MACD Histogram (macdh): MACD Line - Signal Line
    :param df: data
    :return: None
    """
    ema_short = 'close_{}_ema'.format(cls.MACD_EMA_SHORT)
    ema_long = 'close_{}_ema'.format(cls.MACD_EMA_LONG)
    ema_signal = 'macd_{}_ema'.format(cls.MACD_EMA_SIGNAL)
    fast = df[ema_short]
    slow = df[ema_long]
    df['macd'] = fast - slow
    df['macds'] = df[ema_signal]
    df['macdh'] = (df['macd'] - df['macds'])
    log.critical("NOTE: Behavior of MACDH calculation has changed as of "
    "July 2017 - it is now 1/2 of previous calculated values")
    cls._drop_columns(df, [ema_short, ema_long, ema_signal])

    更新:
  • 查找 stockstats.py ,然后在 def _get_macd(cls, df) , 注释掉 cls._drop_columns(df, [ema_short, ema_long, ema_signal]) (例如将 # 放在它前面)
  • 那么你可以做stock['close_12_ema']

  • 获取表的代码:

    periods = '3600'
    resp = requests.get('https://api.cryptowat.ch/markets/poloniex/ethusdt/ohlc', params={'periods': periods})
    data = resp.json()
    df = pd.DataFrame(data['result'][periods], columns=['date', 'open', 'high', 'low', 'close', 'volume', 'amount'])
    df['date'] = pd.to_datetime(df['date'], unit='s')

    stock = sdf.retype(df)
    print(stock['macds'])

    print(stock)
  • 除非您这样做 stock['macds'] 才会添加额外的列.

  • 输出:

                               open        high         low       close      volume        amount  close_12_ema  close_26_ema      macd  macd_9_ema     macds     macdh
    date
    2019-08-20 00:00:00 201.000000 203.379326 201.000000 202.138224 349.209128 70720.937575 202.138224 202.138224 0.000000 0.000000 0.000000 0.000000
    2019-08-20 01:00:00 202.187160 202.650000 200.701061 200.778709 329.485014 66411.899720 201.401820 201.432322 -0.030502 -0.016946 -0.016946 -0.013556
    2019-08-20 02:00:00 201.200000 201.558777 200.133667 200.338312 12.812929 2572.209909 200.986733 201.039255 -0.052522 -0.031526 -0.031526 -0.020996
    2019-08-20 03:00:00 200.915590 201.177018 200.396571 200.440000 21.910910 4395.692727 200.814151 200.871730 -0.057579 -0.040352 -0.040352 -0.017227
    2019-08-20 04:00:00 200.979999 200.979999 198.282603 198.644618 360.432424 71712.376256 200.224696 200.355253 -0.130557 -0.067186 -0.067186 -0.063371

    关于python - 如何使用stockstats查看MACD信号?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/57859416/

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