量化分析（9）——借助talib库来直接获得MACD、动量、rsi、移动均线

talib库有超多现成的方法，不用辛辛苦苦造轮子。上面几篇博客写了MACD、动量、rsi、移动均线的方法，但用起来还是不爽。刚好talib都有这些函数。

比较懒，就直接放代码吧

先看10日的移动均线：

import tushare as ts
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import talib

df=ts.get_k_data('600600')
df['MA10_rolling'] = pd.rolling_mean(df['close'],10)
close = [float(x) for x in df['close']]
# 调用talib计算10日移动平均线的值
df['MA10_talib'] = talib.MA(np.array(close), timeperiod=10) 
df.tail(12)

再来看指数移动均线和MACD

import matplotlib.pyplot as plt
import numpy as np
import talib

df=ts.get_k_data('600600')
close = [float(x) for x in df['close']]
# 调用talib计算指数移动平均线的值
df['EMA12'] = talib.EMA(np.array(close), timeperiod=6)  
df['EMA26'] = talib.EMA(np.array(close), timeperiod=12)   
 # 调用talib计算MACD指标
df['MACD'],df['MACDsignal'],df['MACDhist'] = talib.MACD(np.array(close),
                            fastperiod=6, slowperiod=12, signalperiod=9)   
df.tail(12)

最后来看动量和RSI的函数

import tushare as ts
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import talib

df=ts.get_k_data('600600')
close = [float(x) for x in df['close']]
df['RSI']=talib.RSI(np.array(close), timeperiod=12)     #RSI的天数一般是6、12、24
df['MOM']=talib.MOM(np.array(close), timeperiod=5)
df.tail(12)