如何使用pandas或dask并行化此for循环（或使其更快）

Question

我想使此循环明显更快。它正在为每个壮举者连续计算移动。此处的功能仅适用于一列。稍后，我遍历每个功能（df.columns）并应用此功能。

def move_iar(df, feature):

    lst=[]
    prev_move_iar = 0

    for move in df[feature]:
        if np.isnan(move):
            move_iar = 0
            lst.append(move_iar)
            prev_move_iar = move_iar
        else:
            if move == 0:
                move_iar = prev_move_iar
                lst.append(move_iar)
                prev_move_iar = move_iar
            elif (move >= 0 and prev_move_iar >= 0) or (move <= 0 and prev_move_iar <= 0):
                move_iar = move + prev_move_iar
                lst.append(move_iar)
                prev_move_iar = move_iar
            elif (move < 0 and prev_move_iar >= 0) or (move > 0 and prev_move_iar <= 0):
                move_iar = move
                lst.append(move_iar)
                prev_move_iar = move_iar

    return pd.DataFrame(lst, index=df.index, columns=[feature]).rename(columns={feature : feature + 'IAR'})