将部分键值对格式文本导入pandas DataFrame遇KeyError问题求助

安全阿岳

2026-8-19

解决读取键值对文本到Pandas DataFrame时的KeyError问题

文件`test`的内容

costCenter: LL63238012
mail: shiva.gowni@LLp.com
LLpResponsible: cn=LLf58420,ou=Personal,ou=People,ou=LLDI,o=LLP
LLpHomeDirectory: nisMapName=auto.home,ou=RDC_AMEC_LL-CDC01,ou=Locations,ou=LLDI,o=LLP#0#Quality=economy,NisMap=llc1002:/proj/llc1002_ziz1/q,Quota=10621
LLpHomeDirectory: nisMapName=auto.home,ou=RDC_AMEC_LL-CDC01,ou=Locations,ou=LLDI,o=LLP#0#Quality=scratKG,NisMap=llc1002:/proj/llc1002_ziz1_scratKG/q,Quota=12000,Id=scratKG
fullName: Tulip project ziz1

costCenter: MX61FRK604
mail: ali.pina@LLp.com
LLpResponsible: cn=LLa11826,ou=Personal,ou=People,ou=LLDI,o=LLP
LLpHomeDirectory: nisMapName=auto.home,ou=SAT_AMEC_MX-GDL01,ou=Locations,ou=LLDI,o=LLP#0#Quality=reference,NisMap=llc0156:/proj/llc0156_zmx28home_3/q,Quota=100,Id=3
LLpHomeDirectory: nisMapName=auto.home,ou=SAT_AMEC_MX-GDL01,ou=Locations,ou=LLDI,o=LLP#0#Quality=reference,NisMap=llc0156:/proj/llc0156_zmx28home/q,Quota=300
LLpHomeDirectory: nisMapName=auto.home,ou=SAT_AMEC_MX-GDL01,ou=Locations,ou=LLDI,o=LLP#0#Quality=reference,NisMap=llc0156:/proj/llc0156_zmx28home_2/q,Quota=100,Id=2
fullName: xFSL to LLDI migration



costCenter: RU61FPD561
mail: udi.landen@LLp.com
LLpResponsible: cn=LLa09278,ou=Personal,ou=People,ou=LLDI,o=LLP
LLpHomeDirectory: nisMapName=auto.home,ou=RDC_AMEC_LL-CDC01,ou=Locations,ou=LLDI,o=LLP#0#Quota=1,Quality=EconomyHP,NisMap=llc2002:/proj/llc2002_zru12/q
LLpHomeDirectory: nisMapName=auto.home,ou=RDC_AMEC_LL-CDC01,ou=Locations,ou=LLDI,o=LLP#0#Quota=2800,Quality=EconomyHP,NisMap=llc1002:/proj/llc1002_zru12_analog/q,Id=analog
LLpHomeDirectory: nisMapName=auto.home,ou=RDC_AMEC_LL-CDC01,ou=Locations,ou=LLDI,o=LLP#0#Quota=1100,Quality=EconomyHP,NisMap=llc1002:/proj/llc1002_zru12_home/q,Id=home
LLpHomeDirectory: nisMapName=auto.home,ou=RDC_AMEC_LL-CDC01,ou=Locations,ou=LLDI,o=LLP#0#Quality=EconomyHP,NisMap=llc1002:/proj/llc1002_zru12_libddk/q,Quota=2162,Id=libddk
LLpHomeDirectory: nisMapName=auto.home,ou=RDC_AMEC_LL-CDC01,ou=Locations,ou=LLDI,o=LLP#0#Quality=EconomyHP,NisMap=llc1002:/proj/llc1002_zru12_proj/q,Quota=1102,Id=proj
fullName: zru12

costCenter: KG63010285
mail: adam.smith@LLp.com
LLpHomeDirectory: nisMapName=auto.home,ou=RDC_EMEA_NL-CDC01,ou=Locations,ou=LLDI,o=LLP#0#Quality=BLLinessCriticalHP,Quota=60,NisMap=llc4008:/proj/llc4008_zuriKG/q
fullName: Container to store ZuriKG vault



costCenter: KG63010285
mail: adam.smith@LLp.com
LLpHomeDirectory: nisMapName=auto.home,ou=RDC_EMEA_NL-CDC01,ou=Locations,ou=LLDI,o=LLP#0#Quality=EconomyHP,Quota=1,NisMap=llc3008:/proj/llc3008_zuriKG_rme/q
LLpHomeDirectory: nisMapName=auto.home,ou=SAT_EMEA_NL-RME01,ou=Locations,ou=LLDI,o=LLP#0#Quality=EconomyHP,Quota=30,NisMap=llc4014:/proj/llc4014_zuriKG_rme/q
LLpHomeDirectory: nisMapName=auto.home,ou=SAT_EMEA_NL-RME01,ou=Locations,ou=LLDI,o=LLP#0#Quality=ScratKGHP,Quota=400,NisMap=llc4014:/proj/llc4014_zuriKG_rme_scratKG/q,Id=scratKG
fullName: Project to restore  project data on the RME work on HP-UX

原使用代码

def generate(data):
    for record in data.split("\n\n"):              # Split records based on two newlines (unix)
        result = {}
        for line in record.split("\n"):            # Split properties based on single newlines (unix)
            if line:                               # Skip empty lines happening for extra or trailing newlines
                key, *value = line.split(": ")     # Tolerant to lines with more than a single ´: ´ (*values)
                value = ": ".join(value)           # Recover original value if more than a single (`: `)
                if key in result:
                    result[key] += ";" + value
                else:
                    result[key] = value
        if result:                                 # Don't yield empty results
            yield result


frame = pd.DataFrame(generate("test"))
print(frame)

#frame["responsible"] = frame["LLpResponsible"].str.extract("cn=([\w]*)")
frame["location"] = frame["LLpHomeDirectory"].str.extract("ou=([\w_\-]*)")
frame["directory"] = frame["LLpHomeDirectory"].str.findall("NisMap=\w+:([\w_\-/]*)")

df1 = frame[['costCenter',  'mail', 'responsible', 'location', 'directory']]
#df2 = df.explode("directory")[["costCenter", "responsible", "directory", "mail", "location"]]
print(df1)

报错信息

$ python ldapDataParse1
  test
0
Traceback (most recent call last):
  File "/home/lib64/python3.6/site-packages/pandas/core/indexes/base.py", line 2898, in get_loc
    return self._engine.get_loc(casted_key)
  File "pandas/_libs/index.pyx", line 70, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/index.pyx", line 101, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/hashtable_class_helper.pxi", line 1675, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas/_libs/hashtable_class_helper.pxi", line 1683, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'LLpHomeDirectory'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "ldapDataParse1", line 30, in <module>
    frame["location"] = frame["LLpHomeDirectory"].str.extract("ou=([\w_\-]*)")
  File "/home/lib64/python3.6/site-packages/pandas/core/frame.py", line 2906, in __getitem__
    indexer = self.columns.get_loc(key)
  File "/home/lib64/python3.6/site-packages/pandas/core/indexes/base.py", line 2900, in get_loc
    raise KeyError(key) from err
KeyError: 'LLpHomeDirectory'

问题解决

核心错误点

你调用generate("test")时，传入的是字符串"test"，而非test文件的实际内容，导致generate函数处理的是单个字符串，生成的DataFrame完全不符合预期，自然找不到LLpHomeDirectory列。

修正后的完整代码

import pandas as pd

def generate(data):
    for record in data.split("\n\n"):              # 按两个换行分割记录
        result = {}
        for line in record.split("\n"):            # 按单个换行分割属性行
            if line.strip():                       # 去除空白字符后判断是否为空，处理多余空格
                key, *value = line.split(": ", 1)  # 只按第一个": "分割，避免值里的冒号干扰
                value = value[0] if value else ""
                if key in result:
                    result[key] += ";" + value
                else:
                    result[key] = value
        if result:                                 # 跳过空结果
            yield result

# 读取文件内容，这是关键修正
with open("test", "r") as f:
    file_content = f.read()

frame = pd.DataFrame(generate(file_content))

# 提取responsible字段，缺失时填充空值
frame["responsible"] = frame["LLpResponsible"].str.extract("cn=([\w]*)").fillna("")

# 提取location字段，缺失时填充空值
frame["location"] = frame["LLpHomeDirectory"].str.extract("ou=([\w_\-]*)").fillna("")

# 提取所有directory路径
frame["directory"] = frame["LLpHomeDirectory"].str.findall("NisMap=\w+:([\w_\-/]*)")

# 选择需要的列
df1 = frame[['costCenter', 'mail', 'responsible', 'location', 'directory']]
print(df1)

# 如需展开directory列表成多行，取消下面注释
# df2 = df1.explode("directory")[["costCenter", "responsible", "directory", "mail", "location"]]
# print(df2)

额外优化说明

用with open读取文件，确保文件正常关闭，获取真实的文件内容。
分割键值对时用split(": ", 1)，只按第一个": "分割，避免值中包含的冒号导致错误分割。
对可能缺失的字段用fillna("")处理，避免后续操作报错。
用line.strip()判断空行，处理文件中可能存在的空白行（比如多个连续空格的行）。

内容的提问来源于stack exchange，提问作者user2023

将部分键值对格式文本导入pandas DataFrame遇KeyError问题求助

文件test的内容 #

原使用代码 #

报错信息 #

问题解决 #

核心错误点 #

修正后的完整代码 #

额外优化说明 #