Python 如何更有效地编写以下代码？

有没有有效的方法来编写下面的循环？dataPLprocessed是一个时间序列数据，我想根据滚动7天百分位值计算分数（更多解释请参见下面的循环）

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在每个if语句中，您可以将其分配给变量，而不是使用

dataPLprocessed['percentile'][i]

for i in range(len(dataPLprocessed)):
    x = dataPLprocessed['percentile'][i]

    if (x < .05) | ( x > .95):
        dataPLprocessed.loc[i, 'score'] = 10
    elif (x < .1) | ( x > .9):
        dataPLprocessed.loc[i, 'score'] = 9
    elif (x < .15) |( x > .85):
        dataPLprocessed.loc[i, 'score'] = 8
    elif (x < .2) |(x > .8):
        dataPLprocessed.loc[i, 'score'] = 7
    elif (x < .25) |( x > .75):
        dataPLprocessed.loc[i, 'score'] = 6
    elif (x < .3) |(x > .7):
        dataPLprocessed.loc[i, 'score'] = 5
    elif (x < .35) |( x > .65):
        dataPLprocessed.loc[i, 'score'] = 4
    elif (x < .4) |( x > .6):
        dataPLprocessed.loc[i, 'score'] = 3
    elif (x < .45) |( x > .55):
        dataPLprocessed.loc[i, 'score'] = 2
    elif (x < .5) |( x > .5):
        dataPLprocessed.loc[i, 'score'] = 1

范围内i的

（len（dataPLprocessed））：
x=dataPLprocessed['百分位][i]
如果（x<0.05）|（x>0.95）：
dataPLprocessed.loc[i，'得分']=10
elif（x<0.1）|（x>0.9）：
dataPLprocessed.loc[i，‘score']=9
elif（x<0.15）|（x>0.85）：
dataPLprocessed.loc[i，'得分']=8
elif（x<0.2）|（x>0.8）：
dataPLprocessed.loc[i，'得分']=7
elif（x<0.25）|（x>0.75）：
dataPLprocessed.loc[i，'得分']=6
elif（x<0.3）|（x>0.7）：
dataPLprocessed.loc[i，'得分']=5
elif（x<0.35）|（x>0.65）：
dataPLprocessed.loc[i，‘score']=4
elif（x<0.4）|（x>0.6）：
dataPLprocessed.loc[i，'得分']=3
elif（x<0.45）|（x>0.55）：
dataPLprocessed.loc[i，‘score']=2
elif（x<0.5）|（x>0.5）：
dataPLprocessed.loc[i，‘score']=1

一种可能性是动态生成百分位数，并检查补码，例如，

x不在0.05和0.95之间：

范围内i的
（len（dataPLprocessed））：
x=dataPLprocessed['百分位][i]
对于范围（10）内的k：
p=圆形（0.05+0.05*k，2）
如果不是（p
您可以首先使用分配给每个迭代的
dataPLprocessed['percentile'][i]
的临时变量，这样您就不会在每次迭代中重新访问同一元素多达20次。太好了！谢谢@Blorgony欢迎@UmangGarg。警告一下，我没有测试这段代码。有必要在这里使用吗？这不是非常必要的，没有。但是用这个等式生成百分位数会引入浮点算术错误，例如：
0.05+0.05*6=0.3500000000000003
。
{Timestamp('2020-05-17 23:30:00'): -0.18600000000000005, Timestamp('2020-05-17 23:45:00'): -0.18600000000000005, Timestamp('2020-05-18 00:00:00'): -0.18600000000000005, Timestamp('2020-05-18 00:15:00'): -0.18900000000000008, Timestamp('2020-05-18 00:30:00'): -0.18800000000000008, Timestamp('2020-05-18 00:45:00'): -0.18900000000000008, Timestamp('2020-05-18 01:00:00'): -0.18600000000000005, Timestamp('2020-05-18 01:15:00'): -0.18300000000000005, Timestamp('2020-05-18 01:30:00'): -0.18200000000000005, Timestamp('2020-05-18 01:45:00'): -0.18400000000000005, Timestamp('2020-05-18 02:00:00'): -0.18400000000000005, Timestamp('2020-05-18 02:15:00'): -0.18300000000000005, Timestamp('2020-05-18 02:30:00'): -0.18200000000000005, Timestamp('2020-05-18 02:45:00'): -0.18600000000000005, Timestamp('2020-05-18 03:00:00'): -0.18700000000000008, Timestamp('2020-05-18 03:15:00'): -0.19000000000000009, Timestamp('2020-05-18 03:30:00'): -0.18999999999999995, Timestamp('2020-05-18 03:45:00'): -0.18999999999999995, Timestamp('2020-05-18 04:00:00'): -0.18999999999999995, Timestamp('2020-05-18 04:30:00'): -0.18700000000000008}
{Timestamp('2020-05-17 23:30:00'): -0.18600000000000005, Timestamp('2020-05-17 23:45:00'): -0.18600000000000005, Timestamp('2020-05-18 00:00:00'): -0.18600000000000005, Timestamp('2020-05-18 00:15:00'): -0.18900000000000008, Timestamp('2020-05-18 00:30:00'): -0.18800000000000008, Timestamp('2020-05-18 00:45:00'): -0.18900000000000008, Timestamp('2020-05-18 01:00:00'): -0.18600000000000005, Timestamp('2020-05-18 01:15:00'): -0.18300000000000005, Timestamp('2020-05-18 01:30:00'): -0.18200000000000005, Timestamp('2020-05-18 01:45:00'): -0.18400000000000005, Timestamp('2020-05-18 02:00:00'): -0.18400000000000005, Timestamp('2020-05-18 02:15:00'): -0.18300000000000005, Timestamp('2020-05-18 02:30:00'): -0.18200000000000005, Timestamp('2020-05-18 02:45:00'): -0.18600000000000005, Timestamp('2020-05-18 03:00:00'): -0.18700000000000008, Timestamp('2020-05-18 03:15:00'): -0.19000000000000009, Timestamp('2020-05-18 03:30:00'): -0.18999999999999995, Timestamp('2020-05-18 03:45:00'): -0.18999999999999995, Timestamp('2020-05-18 04:00:00'): -0.18999999999999995, Timestamp('2020-05-18 04:30:00'): -0.18700000000000008}

for i in range(len(dataPLprocessed)):
    x = dataPLprocessed['percentile'][i]

    if (x < .05) | ( x > .95):
        dataPLprocessed.loc[i, 'score'] = 10
    elif (x < .1) | ( x > .9):
        dataPLprocessed.loc[i, 'score'] = 9
    elif (x < .15) |( x > .85):
        dataPLprocessed.loc[i, 'score'] = 8
    elif (x < .2) |(x > .8):
        dataPLprocessed.loc[i, 'score'] = 7
    elif (x < .25) |( x > .75):
        dataPLprocessed.loc[i, 'score'] = 6
    elif (x < .3) |(x > .7):
        dataPLprocessed.loc[i, 'score'] = 5
    elif (x < .35) |( x > .65):
        dataPLprocessed.loc[i, 'score'] = 4
    elif (x < .4) |( x > .6):
        dataPLprocessed.loc[i, 'score'] = 3
    elif (x < .45) |( x > .55):
        dataPLprocessed.loc[i, 'score'] = 2
    elif (x < .5) |( x > .5):
        dataPLprocessed.loc[i, 'score'] = 1