python - 移动平均线 Pandas

Question

我想在我的交易时间序列中添加移动平均计算。

来自 Quandl 的原始数据

Exchange = Quandl.get("BUNDESBANK/BBEX3_D_SEK_USD_CA_AC_000",
                      authtoken="xxxxxxx")

#               Value
# Date               
# 1989-01-02  6.10500
# 1989-01-03  6.07500
# 1989-01-04  6.10750
# 1989-01-05  6.15250
# 1989-01-09  6.25500
# 1989-01-10  6.24250
# 1989-01-11  6.26250
# 1989-01-12  6.23250
# 1989-01-13  6.27750
# 1989-01-16  6.31250

# Calculating Moving Avarage
MovingAverage = pd.rolling_mean(Exchange,5)

#               Value
# Date          
# 1989-01-02      NaN
# 1989-01-03      NaN
# 1989-01-04      NaN
# 1989-01-05      NaN
# 1989-01-09  6.13900
# 1989-01-10  6.16650
# 1989-01-11  6.20400
# 1989-01-12  6.22900
# 1989-01-13  6.25400
# 1989-01-16  6.26550

我想使用相同的索引 (Date) 在 Value 之后将计算出的移动平均线作为一个新列添加到右侧。最好我还想将计算出的移动平均线重命名为 MA。

Answer 1

滚动平均值返回一个 Series，您只需将其添加为 DataFrame (MA) 的新列，如下所述。

有关信息，rolling_mean 函数已在 pandas 较新版本中被弃用。我在示例中使用了新方法，请参阅下面来自 pandas documentation 的引用.

Warning Prior to version 0.18.0, pd.rolling_*, pd.expanding_*, and pd.ewm* were module level functions and are now deprecated. These are replaced by using the Rolling, Expanding and EWM. objects and a corresponding method call.

df['MA'] = df.rolling(window=5).mean()

print(df)
#             Value    MA
# Date                   
# 1989-01-02   6.11   NaN
# 1989-01-03   6.08   NaN
# 1989-01-04   6.11   NaN
# 1989-01-05   6.15   NaN
# 1989-01-09   6.25  6.14
# 1989-01-10   6.24  6.17
# 1989-01-11   6.26  6.20
# 1989-01-12   6.23  6.23
# 1989-01-13   6.28  6.25
# 1989-01-16   6.31  6.27