Python TA-Lib RSI错误结果

Question

我试图在python中使用TA-Lib获得股票的RSI，它一直给我错误的数字。

import talib
import pandas as pd
from td.client import TDClient
ticker = 'GOOG'
data = TDSession.get_price_history(
symbol = ticker,
period_type = 'month',
frequency_type = 'daily',
frequency = 1,
period = 1,
)
df = pd.DataFrame(data['candles'])
close = df['close']
# Gets the RSI of the ticker 
rsi = str(talib.RSI(close, timeperiod=14))
current = float(rsi[len(rsi)-40:len(rsi)-33])

是否有解决这个问题的方法?

Answer 1

这是一种自己计算RSI的方法。代码可以优化，但我更喜欢让它易于理解，并让您优化。

您应该将其与Ta-Lib进行比较。

在本例中，我们假设您有一个名为df的DataFrame，其中包含一个名为"Close"的列，用于收盘价。顺便说一下，请注意，如果您将RSI的结果与站点进行比较，例如，您应该确保比较的是相同的值。例如，如果在车站，你已经得到了买入价，而你自己在中间或要价上计算，结果是不一样的。

让我们看看代码:

def rsi(df,_window=14,_plot=0,_start=None,_end=None):
"""[RS functionI]
Args:
df ([DataFrame]): [DataFrame with a column 'Close' for the close price]
_window ([int]): [The lookback window.](default : {14})
_plot ([int]): [1 if you want to see the plot](default : {0})
_start ([Date]):[if _plot=1, start of plot](default : {None})
_end ([Date]):[if _plot=1, end of plot](default : {None})
"""    
##### Diff for the différences between last close and now
df['Diff'] = df['Close'].transform(lambda x: x.diff())
##### In 'Up', just keep the positive values
df['Up'] = df['Diff']
df.loc[(df['Up']<0), 'Up'] = 0
##### Diff for the différences between last close and now
df['Down'] = df['Diff']
##### In 'Down', just keep the negative values
df.loc[(df['Down']>0), 'Down'] = 0 
df['Down'] = abs(df['Down'])
##### Moving average on Up & Down
df['avg_up'+str(_window)] = df['Up'].transform(lambda x: x.rolling(window=_window).mean())
df['avg_down'+str(_window)] = df['Down'].transform(lambda x: x.rolling(window=_window).mean())
##### RS is the ratio of the means of Up & Down
df['RS_'+str(_window)] = df['avg_up'+str(_window)] / df['avg_down'+str(_window)]
##### RSI Calculation
##### 100 - (100/(1 + RS))
df['RSI_'+str(_window)] = 100 - (100/(1+df['RS_'+str(_fast)]))
##### Drop useless columns
df = df.drop(['Diff','Up','Down','avg_up'+str(_window),'avg_down'+str(_window),'RS_'+str(_window)],axis=1)
##### If asked, plot it!
if _plot == 1:
sns.set()
fig = plt.figure(facecolor = 'white', figsize = (30,5))
ax0 = plt.subplot2grid((6,4), (1,0), rowspan=4, colspan=4)
ax0.plot(df[(df.index<=end)&(df.index>=start)&(df.Symbol==_ticker.replace('/',''))]['Close'])
ax0.set_facecolor('ghostwhite')
ax0.legend(['Close'],ncol=3, loc = 'upper left', fontsize = 15)
plt.title(_ticker+" Close from "+str(start)+' to '+str(end), fontsize = 20)
ax1 = plt.subplot2grid((6,4), (5,0), rowspan=1, colspan=4, sharex = ax0)
ax1.plot(df[(df.index<=end)&(df.index>=start)&(df.Symbol==_ticker.replace('/',''))]['RSI_'+str(_window)], color = 'blue')
ax1.legend(['RSI_'+str(_window)],ncol=3, loc = 'upper left', fontsize = 12)
ax1.set_facecolor('silver')
plt.subplots_adjust(left=.09, bottom=.09, right=1, top=.95, wspace=.20, hspace=0)
plt.show()
return(df)

要调用该函数，只需键入

df = rsi(df)

如果你保持默认值，或者改变_window和/或_plot的参数。请注意，如果输入_plot=1，则需要用字符串或日期时间提供plot的开始和结束。