windows事件日志消息转换为字典然后转换为pandas列

时间:2017-03-27 03:19:38

标签: python python-3.x pandas elasticsearch

我有一个pandas列,其中包含windows事件日志的消息字段,如下所示。我如何通过并删除所有非键值样式对?

消息列包含类似的数据,但可能包含更多键:值类型,而不是显示,因为这只是一个事件ID。

message
['subject':'none','security id':'s-1-5-12','account name':'myaccountname','account domain':'domain', 'logon id':'0x3e6',    ' process information':'none', 'new process id':'0x1a53', 'new process name':'c:\windows\system32\ipconfig.exe', 'token elevation type':'%%1932','creator process id':'0x1b33', 'process command line':'none',  '  token elevation type indicates the type of token that was assigned to the new process in accordance with user account control policy.',' type 1 is a full token with no privileges removed or groups disabled.  a full token is only used if user account control is disabled or if the user is the built-in administrator account or a service account.', ' type 2 is an elevated token with no privileges removed or groups disabled.  an elevated token is used when user account control is enabled and the user chooses to start the program using run as administrator.  an elevated token is also used when an application is configured to always require administrative privilege or to always require maximum privilege', ' and the user is a member of the administrators group.',' type 3 is a limited token with administrative privileges removed and administrative groups disabled.  the limited token is used when user account control is enabled', ' the application does not require administrative privilege', ' and the user does not choose to start the program using run as administrator.']
['subject':'none','security id':'s-1-5-13','account name':'myaccountname','account domain':'domain', 'logon id':'0x3e6',    ' process information':'none', 'new process id':'0x1a53', 'new process name':'c:\windows\system32\net.exe', 'token elevation type':'%%1932','creator process id':'0x1b33', 'process command line':'none',   '  token elevation type indicates the type of token that was assigned to the new process in accordance with user account control policy.',' type 1 is a full token with no privileges removed or groups disabled.  a full token is only used if user account control is disabled or if the user is the built-in administrator account or a service account.', ' type 2 is an elevated token with no privileges removed or groups disabled.  an elevated token is used when user account control is enabled and the user chooses to start the program using run as administrator.  an elevated token is also used when an application is configured to always require administrative privilege or to always require maximum privilege', ' and the user is a member of the administrators group.',' type 3 is a limited token with administrative privileges removed and administrative groups disabled.  the limited token is used when user account control is enabled', ' the application does not require administrative privilege', ' and the user does not choose to start the program using run as administrator.']

预期产出:

subject  security id   account name  logon id  process information  new processs id                  new process name  token elevation type  creator process id   process command line
   none     s-1-5-12  myaccountname     0x3e6                 none           0x1a53  c:\windows\system32\ipconfig.exe                %%1932              0x1b33                   none

如果我能从我的数据中得到非关键:值对,我知道我可以使用这种方法。

pandas list of dictionary to separate columns

1 个答案:

答案 0 :(得分:1)

您可以使用yaml,如果在None中丢失value,则会添加dict个值,然后移除所有None对:

print (df)
                                       message
0  {'a':'none','b':'2', '  token.', ' type 1'}

import yaml

print (df.message.apply(yaml.load))
0    {'  token.': None, ' type 1': None, 'b': '2', ...
Name: message, dtype: object

df.message = df.message.apply(lambda x: {k: v for k, v in yaml.load(x).items() if v})
print (df)
                   message
0  {'b': '2', 'a': 'none'}

使用您的数据:

df = pd.DataFrame({'message':["{'subject':'none', 'security id':'s-1-5-12', 'account name':'myaccountname','account domain':'domain', 'logon id':'0x3e6', ' process information':'none', 'new process id':'0x1a53', 'new process name':'c:\windows\system32\ipconfig.exe', 'token elevation type':'%%1932', 'creator process id':'0x1b33','process command line':'none', '  token elevation type indicates the type of token that was assigned to the new process in accordance with user account control policy.', ' type 1 is a full token with no privileges removed or groups disabled.  a full token is only used if user account control is disabled or if the user is the built-in administrator account or a service account.', ' type 2 is an elevated token with no privileges removed or groups disabled.  an elevated token is used when user account control is enabled and the user chooses to start the program using run as administrator.  an elevated token is also used when an application is configured to always require administrative privilege or to always require maimum privilege', ' and the user is a member of the administrators group.',' type 3 is a limited token with administrative privileges removed and administrative groups disabled.  the limited token is used when user account control is enabled', ' the application does not require administrative privilege', ' and the user does not choose to start the program using run as administrator.'}"]})
import yaml
df.message = df.message.apply(lambda x: {k: v for k, v in yaml.load(x).items() if v})

df1 = pd.DataFrame(df.pop('message').values.tolist(), index=df.index)
print (df1)
   process information account domain   account name creator process id  \
0                 none         domain  myaccountname             0x1b33   

  logon id new process id                  new process name  \
0    0x3e6         0x1a53  c:\windows\system32\ipconfig.exe   

  process command line security id subject token elevation type  
0                 none    s-1-5-12    none               %%1932  

编辑:

import yaml
df.message=df.message.str[0].apply(lambda x:{k:v for k,v in yaml.load('{'+x+'}').items() if v})

df1 = pd.DataFrame(df.pop('message').values.tolist(), index=df.index)
print (df1)
   process information account domain   account name creator process id  \
0                 none         domain  myaccountname             0x1b33   

  logon id new process id                  new process name  \
0    0x3e6         0x1a53  c:\windows\system32\ipconfig.exe   

  process command line security id subject token elevation type  
0                 none    s-1-5-12    none               %%1932