How do I correctly calculate EMA for a stock using Ta-lib or Pandas?

Question

Edit!

For anyone wondering this same thing, I figured it out. There is nothing wrong with the implementations below. Its just the fact that EMA requires more than 21 data points to count a 20 data point exponential moving average. The reason for this is that the earlier data points effect the datapoints you are trying to calculate. In simple terms you i tested and you need about 40-50 datapoints to get the same 20 day EMA as with 100+ datapoints.

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I'm trying to calculate the EMA (Exponential moving average) of a stock, but there is something wrong with my calculations. I have exported the last 22+ days of stock data for AAPL, and when I try to calculate the EMA for this there is something wrong every time.

Here is the data for my example: https://pastebin.com/raw/2MsgCeQx

Here are the solutions that I have tried to calculate the 20 day EMA.

#Imported the data as "data".
#With Ta-lib
data["EMA20Talib"] = talib.EMA(data.uClose, timeperiod = 20)

#And with pandas
data["EMA20Pandas"] = data["uClose"].ewm(span=20, adjust = False).mean()

I here is an image of the data and the results. https://i.imgur.com/pFtc7x8.png

As you can see the Real20EMA does not match the TA-lib or the pandas 20EMA. What am I doing wrong?

The uClose is the column Im calulating the EMA on, the "Real20EMA" is taken from tradingview (cross referenced with marketwatch to make sure its the correct one).

我注意到早些时候这里有一个类似的问题，同样的问题：熊猫的 EMA 与股票的 EMA 不匹配？. 当你对索引进行排序时，问题就在那里解决了，我已经确保我已经正确排序了，但是我仍然遇到同样的问题。

我想使用某种工具获得与其他金融网站相同的数字。奇怪的是，即使我尝试过的这两种方法也没有返回相同的结果。

Answer 1

我建议在Python中使用Pandas TA来计算技术指标。我发现它比 TA-Lib 更准确并且更容易安装。

使用 Pandas TA，20 周期指数移动平均线的计算如下：

import pandas_ta as ta

data["EMA20"] = ta.ema(data["uClose"], length=20)