Python 从文本文件中提取数据并将其转换为df

有一个包含如下值的txt文件。如何将其转换为数据帧

尝试了几种删除空白并将其排列在数据框中的方法。整个数据可以

str

格式存储，包括日期

cn No:    9991
PUEN:    S55D
Date :    05/01/2017
Development Name:   
Status: Active
Development Location:   
Address: 3 ADAM PARK #3-3 
Contact No.: 
Name Agent: 
Managing  No.: 5648123
cn No:    4671
PUEN:    T11F
Date :    16/07/2019
Development Name:   MEGA
Status: Active
Development Location:   
Address: 39 WOODLANDS CLOSE,  #01-64, 
Contact No.: 6258 6944
Name  Agent: 
Managing  No.:

尝试将文本文件转换为数据帧

f = open('outs.txt', 'w')
sys.stdout = f
with concurrent.futures.ThreadPoolExecutor(max_workers=4) as e:
    for hostinfo in e.map(lambda x: get_certificate(x[0], x[1]), HOSTS):
        basic_info(hostinfo)

sys.stdout = orig_stdout
f.close()           
f = open("outs.txt", "r")
a=(f.read())
data = a
a=(pd.read_csv(StringIO(data),
              header=None,

              sep="/",
              names=['string'])
     #limit number of splits to 1
  .string.str.split(':',n=1,expand=True)
  .rename({0:'Name',1:'temp'},axis=1)
  .assign(temp = lambda x: np.where(x.Name.str.strip()
                             #look for string that ends 
                             #with a bracket
                              .str.match(r'(.*[)]$)'),
                              x.cn No,
                              x.temp),
          Name = lambda x: x.Name.str.replace(r'(.*[)]$)','cn No.')
          )
   #remove whitespace
 .assign(cn No. = lambda x: x.Name.str.strip())
 .pivot(columns='Name',values='temp')
 .ffill()
 .dropna(how='any')
 .reset_index(drop=True)
 .rename_axis(None,axis=1)
 .filter(['cn No','PUEN','Date','Development Name','status','Development Location','Address','Contact No.','Name Agent','Managing No.'])      
  )

---

所以我们有一个文本文件，上面有这样的内容

import pandas as pd

# Dictionary to store the header and values
my_dict = dict()

# Open the file
with open("./temp.txt", 'r') as file_object: 

    # Read the content
    content = file_object.readlines() 

    # For every row 
    for row in content:

    # Get the header and data
    header, data = row.split(":") 

    # Check if the header is not in dict keys
    if header not in my_dict.keys(): 

        # We add the data with corresponding key
        my_dict[header.strip()] = data.strip()


# Returns a dataframe with the values
pd.DataFrame.from_dict(my_dict, orient='index')

---

如果有几百行呢

import pandas as pd

# Dictionary to store the header and values
my_dict = dict()

# Open the file
with open("./temp.txt", 'r') as file_object: 

    # Read the content
    content = file_object.readlines() 

    # For every row 
    for row in content:

    # Get the header and data
    header, data = row.split(":") 

    # Check if the header is not in dict keys
    if header not in my_dict.keys(): 

        # We add the data with corresponding key
        my_dict[header.strip()] = data.strip()


# Returns a dataframe with the values
pd.DataFrame.from_dict(my_dict, orient='index')