列的加权移动平均线

Question

当我想计算 2771 行的加权移动平均值并且我的 n = 3 ，我得到 77783.446664 2771 行（相同的答案）。我的代码有问题。我需要改变什么？

我的数据如下：

Date,      Open,      High,      Low,       Close, Adj Close, Volume
11/16/2007,228.259995,229.570007,222.570007,225.25,196.770523,10083400
11/19/2007,223.520004,228.399994,216.619995,220.539993,192.656067,11007900
11/20/2007,220.399994,226.229996,213.5,217.479996,189.982925,13433000
11/21/2007,213.410004,215.270004,206.440002,209.5,183.011887,14874300
11/23/2007,212.520004,216.479996,211.800003,216.479996,189.109329,4737100
11/26/2007,214.649994,217.449997,205.419998,207.449997,181.221085,9815200
11/27/2007,210,213.979996,206.190002,213.330002,186.357651,11946400
11/28/2007,217.580002,227.860001,217.080002,227.520004,198.753555,15710600
11/29/2007,226.020004,228.309998,222.5,224.380005,196.010559,9774200
11/30/2007,232.649994,234.220001,224.770004,226.639999,197.984848,11878600
12/3/2007,226.089996,229.350006,223.600006,226.889999,198.203201,6800300

我的代码是：

import pandas as pd

#WMA = ( Price n + Price(1) n-1 + ...+Price( n-1 ) 1) / ( n ( n + 1 ) / 2 ), (n = time period).

def wma(data, n):
    for i in range(n, 0, -1):
        data[abs(n-i)] = i * data[abs(n-i)]
        print(data[i])
    return sum(data) / ((n * (n + 1)) / 2)

data_pd = pd.read_csv('GS.csv')
format = '%m/%d/%Y'
data_pd['Date'] = pd.to_datetime(data_pd['Date'], format=format)
data_pd = data_pd.set_index(data_pd['Date'])
data_pd = data_pd.drop(columns=['Date'])

n1 = 3

data_pd['wma'] = wma(data_pd['Close'].values, n1)

Answer 1

IIUC，假设您需要加权 3 倍的行，前一个 2x 和之前的一个，那么您可以试试这个；

weights = np.array([1,2,3])

data_pd['wma'] = data_pd['       Close'].rolling(len(weights)).apply(lambda column: np.correlate(column,weights/sum(weights)))

data_pd.head()

                  Open        High         Low         Close   Adj Close  \
Date                                                                       
2007-11-16  228.259995  229.570007  222.570007   2027.250000  196.770523   
2007-11-19  223.520004  228.399994  216.619995    882.159972  192.656067   
2007-11-20  220.399994  226.229996  213.500000    217.479996  189.982925   
2007-11-21  213.410004  215.270004  206.440002    209.500000  183.011887   
2007-11-23  212.520004  216.479996  211.800003    216.479996  189.109329   

              Volume         wma  
Date                              
2007-11-16  10083400         NaN  
2007-11-19  11007900         NaN  
2007-11-20  13433000  740.668322  
2007-11-21  14874300  324.269994  
2007-11-23   4737100  214.319997