pandas 用熊猫计算指数移动平均线
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calculate Exponential Moving Average with pandas
提问by john
I try to calculate ema with pandas but the result is not good. I try 2 techniques to calculate :
我尝试用Pandas计算 ema 但结果不好。我尝试两种技术来计算：
The first technique is the panda's function ewn:
第一种技术是Pandas的功能ewn：
window = 100
c = 2 / float(window + 1)
df['100ema'] = df['close'].ewm(com=c).mean()
But the last result of this function gives. 2695.4but the real result is 2656.2
但是这个函数的最后一个结果给出了。2695.4但真正的结果是2656.2
The second technique is
第二种技术是
window = 100
c = 2 / float(window + 1)
df['100sma'] = df['close'].rolling(window).mean()
df['100ema'] = (c * df['close']) + ((1 - c) * df['100sma'])
The result is 2649.1it's closer than first technique but is always not good
结果是2649.1它比第一种技术更接近，但总是不好
The sma function give the good result
sma 函数给出了很好的结果
** EDIT **
** 编辑 **
The response is
回应是
df['100ema'] = pd.Series.ewm(df['close'], span=window).mean()
采纳答案by john
回答by Brahmaiahchowdary
expwighted_avg = ts_log.ewm(halflife=12).mean()
where 'ts_log' is dataframe or series of Time Series
其中“ts_log”是数据帧或时间序列系列
