Python Pandas：代码针对单个值运行，但不针对循环运行。错误：索引必须是单调递增或递减的

当我尝试为值列表运行以下代码时，我得到错误：

->3088 raise VALUE ERROR（'索引必须是单调递增或递减'）

但是，当我为单个值运行此代码时。它执行

不运行：

def block(host):
    time_values = failedIP_df.ix[[host]].set_index(keys='index')['timestamp']
    if (return_seconds(time_values[2:3].values[0]) \
      - return_seconds(time_values[0:1].values[0]))<=20:
        blocked_host.append(time_values[3:].index.tolist())

list(map(block, failedIP_list))

样本数据：

FailedIP_df:

                             timestamp               index
    host        
    199.72.81.55              01/Jul/1995:00:00:01   0
    unicomp6.unicomp.net      01/Jul/1995:00:00:06   1
    freenet.edmonton.ab.ca  01/Jul/1995:00:00:12     12
    burger.letters.com      01/Jul/1995:00:00:12     14
    205.212.115.106         01/Jul/1995:00:00:12     15
    129.94.144.152          01/Jul/1995:00:00:13     21
    unicomp6.unicomp.net      01/Jul/1995:00:00:07   415
    unicomp6.unicomp.net      01/Jul/1995:00:00:08   226
    unicomp6.unicomp.net      01/Jul/1995:00:00:21   99
    129.94.144.152          01/Jul/1995:00:00:14     41
    129.94.144.152          01/Jul/1995:00:00:15     52
    129.94.144.152          01/Jul/1995:00:00:17     55
    129.94.144.152          01/Jul/1995:00:00:18     75
    129.94.144.152          01/Jul/1995:00:00:21     84

---

示例输出：三次尝试后在20秒内未成功登录的所有主机的索引

blocked_list=[99, 55, 75, 84]

我希望我的代码针对列表中的所有值（即IP地址列表）运行。我真的很感谢你在这方面的帮助。谢谢。

打印（df）
print (df)
                                   timestamp  index
host                                               
199.72.81.55            01/Jul/1995:00:00:01      0
unicomp6.unicomp.net    01/Jul/1995:00:00:06      1
freenet.edmonton.ab.ca  01/Jul/1995:00:00:12     12
burger.letters.com      01/Jul/1995:00:00:12     14
205.212.115.106         01/Jul/1995:00:00:12     15
129.94.144.152          01/Jul/1995:00:00:13     21
unicomp6.unicomp.net    01/Jul/1995:00:00:07    415
unicomp6.unicomp.net    01/Jul/1995:00:00:08    226
unicomp6.unicomp.net    01/Jul/1995:00:00:33     99 <-change time for matching
129.94.144.152          01/Jul/1995:00:00:14     41
129.94.144.152          01/Jul/1995:00:00:15     52
129.94.144.152          01/Jul/1995:00:00:17     55
129.94.144.152          01/Jul/1995:00:00:18     75
129.94.144.152          01/Jul/1995:00:00:21     84

#convert to datetimes
df.timestamp = pd.to_datetime(df.timestamp, format='%d/%b/%Y:%H:%M:%S')
failedIP_list = ['199.72.81.55', '129.94.144.152', 'unicomp6.unicomp.net']

#filter rows by failedIP_list
df = df[df.index.isin(failedIP_list)]

#get difference and count for all values in index
g = df.groupby(level=0)['timestamp']
DIFF = pd.to_timedelta(g.transform(pd.Series.diff)).dt.total_seconds()
COUNT = g.cumcount()

#filter rows
mask = (DIFF > 20) | (COUNT >= 3)
L = df.loc[mask, 'index'].tolist()
print (L)
[99, 55, 75, 84]

时间戳索引
主办
199.72.81.55 01/Jul/1995:00:00:01 0
unicomp6.unicomp.net 01/Jul/1995:00:00:06 1
freenet.edmonton.ab.ca 01/Jul/1995:00:00:12
burger.letters.com 01/Jul/1995:00:00:12 14
205.212.115.106 01/Jul/1995:00:00:12 15
129.94.144.152 01/Jul/1995:00:00:13 21
unicomp6.unicomp.net 01/Jul/1995:00:00:07 415
unicomp6.unicomp.net 01/Jul/1995:00:00:08 226
unicomp6.unicomp.net 01/Jul/1995:00:00:33 99 20）|（计数>=3）
L=df.loc[掩码，'索引'].tolist（）
印刷品（L）
[99, 55, 75, 84]

您能添加样本数据和所需输出吗？@jezrael:我已经添加了样本数据和输出。谢谢。@耶斯雷尔：从昨晚起我就被困在这件事上了。如果你能帮忙，我将不胜感激。我对问题进行了编辑，使其易于理解。如果还有什么，我会尽力解释的。我想我需要一些小的修正，但是我不确定是什么。@DYZ:你能帮我一下吗。

blocked_list=[99, 55, 75, 84]

print (df)
                                   timestamp  index
host                                               
199.72.81.55            01/Jul/1995:00:00:01      0
unicomp6.unicomp.net    01/Jul/1995:00:00:06      1
freenet.edmonton.ab.ca  01/Jul/1995:00:00:12     12
burger.letters.com      01/Jul/1995:00:00:12     14
205.212.115.106         01/Jul/1995:00:00:12     15
129.94.144.152          01/Jul/1995:00:00:13     21
unicomp6.unicomp.net    01/Jul/1995:00:00:07    415
unicomp6.unicomp.net    01/Jul/1995:00:00:08    226
unicomp6.unicomp.net    01/Jul/1995:00:00:33     99 <-change time for matching
129.94.144.152          01/Jul/1995:00:00:14     41
129.94.144.152          01/Jul/1995:00:00:15     52
129.94.144.152          01/Jul/1995:00:00:17     55
129.94.144.152          01/Jul/1995:00:00:18     75
129.94.144.152          01/Jul/1995:00:00:21     84

#convert to datetimes
df.timestamp = pd.to_datetime(df.timestamp, format='%d/%b/%Y:%H:%M:%S')
failedIP_list = ['199.72.81.55', '129.94.144.152', 'unicomp6.unicomp.net']

#filter rows by failedIP_list
df = df[df.index.isin(failedIP_list)]

#get difference and count for all values in index
g = df.groupby(level=0)['timestamp']
DIFF = pd.to_timedelta(g.transform(pd.Series.diff)).dt.total_seconds()
COUNT = g.cumcount()

#filter rows
mask = (DIFF > 20) | (COUNT >= 3)
L = df.loc[mask, 'index'].tolist()
print (L)
[99, 55, 75, 84]