Matplotlib Bollinger sample

Matplotlib Bollinger

def Bollinger(df, window=25):
    df1 = df.copy()
    df1["ma"] = df1.close.rolling(window=window).mean()
    df1["sigma"] =  df1.close.rolling(window=window).std()
    df1["ma+2sigma"] = df1.ma + 2*df1.sigma
    df1["ma-2sigma"] = df1.ma - 2*df1.sigma
    df1["diffplus"] = df1.close - df1["ma+2sigma"] 
    df1["diffminus"] = df1["ma-2sigma"] - df1.close
    s_up = df1[df1["diffplus"] > 0]["close"]
    s_down = df1[df1["diffminus"] > 0]["close"]

    xdate = [x.date() for x in df1.index]
    plt.figure(figsize=(15,5))
    plt.grid()
    plt.xlim(xdate[0], xdate[-1])
    plt.scatter(s_up.index, s_up.values,marker="x", s=100, color="blue")
    plt.scatter(s_down.index, s_down.values,marker="x", s=100, color="red")
    plt.plot(xdate, df1.close.values, label="original", color="b", alpha=0.9)
    plt.plot(xdate, df1.ma.values, label="{}ma".format(window))
    plt.fill_between(xdate, df1.ma-df1.sigma, df1.ma+df1.sigma, color="red", alpha=0.7, label="$1\sigma$")
    plt.fill_between(xdate, df1.ma-2*df1.sigma, df1.ma+2*df1.sigma, color="red", alpha=0.3, label="$2\sigma$")
    plt.fill_between(xdate, df1.ma-3*df1.sigma, df1.ma+3*df1.sigma, color="red", alpha=0.1, label="$3\sigma$") 
    plt.legend()

Bollinger(df, window=25)