在 Pandas 中為大型數(shù)據(jù)幀（1500682 行）調(diào)用 groupby 以及滾動和應(yīng)用函數(shù)時，我的性能非常緩慢。我正在嘗試獲得具有不同權(quán)重的滾動移動平均線。運行緩慢的代碼部分是：df['rolling'] = df.groupby('i2')['x'].rolling(3).apply(lambda x: x[-3]*0.1+x[-2]*0.9).reset_index(level=0, drop=True).reindex(df.index)完整的代碼（帶有數(shù)據(jù)）是：import pandas as pdfrom random import randint# data (it takes some time to create [less than 1 minute in my computer])data1   = [[[[randint(0, 100) for i in range(randint(1, 2))] for i in range(randint(1, 3))] for i in range(5000)] for i in range(100)]data2   = pd.DataFrame(    [        (i1, i2, i3, i4, x4)        for (i1, x1) in enumerate(data1)        for (i2, x2) in enumerate(x1)        for (i3, x3) in enumerate(x2)        for (i4, x4) in enumerate(x3)    ],    columns = ['i1', 'i2', 'i3', 'i4', 'x'])data2.drop(['i3', 'i4'], axis=1, inplace = True)df   = data2.set_index(['i1', 'i2']).sort_index()## conflicting part of the code ##df['rolling'] = df.groupby('i2')['x'].rolling(3).apply(lambda x: x[-3]*0.1+x[-2]*0.9).reset_index(level=0, drop=True).reindex(df.index)如果您能詳細(xì)說明代碼以使其更高效并更快地執(zhí)行，我將不勝感激。