我有一个解决方案……只需要花点时间在笔记本电脑上写下来。我会尝试过一段时间再发布。

我认为您必须手动完成此操作。如果您检查 Pandas 的 I/O API（ https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html ），则无法定义自定义读取过程。

这是一个糟糕的（不完整/无用的）答案，因为有很多方法可以实现这一点。是的，pandas 是一个优秀的工具，但不是唯一的工具。这需要一些外部（低级）思考。

我的看法。再次作为我学习熊猫的一部分。

import pandas as pd
from io import StringIO

data = '''\
name: hello_world
rating: 5
description: basic program

name: python
rating: 10
description: programming language

name: foo
rating: 20
description: bar
'''
buffer = StringIO()
buffer.write('field: value\n')  # add column headers
buffer.write(data)
buffer.seek(0)

df = pd.read_csv(buffer, delimiter=':')

transposed = df.T

_, col_count = transposed.shape

x = []
for i in range(0, col_count, 3):
    tmp = transposed[[i, i + 1, i + 2]]
    columns = tmp.iloc[0]
    tmp = tmp[1:]
    tmp.columns = columns
    x.append(tmp)

out = pd.concat(x)
print(out.to_string(index=False))

我真的很感激有饲养熊猫经验的人能告诉我更好的方法。

数据.txt：

name: hello_world
rating: 5
description: basic program

name: python
rating: 10
description: programming language

代码：

import pandas as pd
with open('data.txt', 'rt') as fin:
    lst = [line[:-1] for line in fin if line[:-1]]
print(lst)

# Soln 1
d = dict()
d['name'] = [ele.split(':')[1] for ele in lst if ele.startswith('name:')]
d['rating'] = [ele.split(':')[1] for ele in lst if ele.startswith('rating:')]
d['description'] = [ele.split(':')[1] for ele in lst if ele.startswith('description:')]
df = pd.DataFrame(data=d)
print(df)

＃或者

data_tuples_lst = [(lst[i].split(':')[1], lst[i+1].split(':')[1], lst[i+2].split(':')[1]) for  i in range(0, len(lst), 3) ]
df1 = pd.DataFrame(data=data_tuples_lst, columns = ['name', 'rating', 'description'])
print(df1)

输出：

['name: hello_world', 'rating: 5', 'description: basic program', 'name: python', 'rating: 10', 'description: programming language']
           name rating            description
0   hello_world      5          basic program
1        python     10   programming language
           name rating            description
0   hello_world      5          basic program
1        python     10   programming language

在第一个解决方案中，您可以避免使用字典。我添加了第三个解决方案的答案，即在获得您的列表之后。

这是处理“横向”数据集的一种方法。此代码已针对上一个答案进行了编辑以提高效率。

示例代码：

import pandas as pd
from collections import defaultdict

# Read the text file into a list.
with open('prog.txt') as f:
    text = [i.strip() for i in f]

# Split the list into lists of key, value pairs.
d = [i.split(':') for i in text if i]
# Create a data container.
data = defaultdict(list)
# Store the data in a DataFrame-ready dict.
for k, v in d:
    data[k].append(v.strip())

# Load the DataFrame.
df = pd.DataFrame(data)

输出：

          name rating           description
0  hello_world      5         basic program
1       python     10  programming language

以防有人稍后来这里，这就是我所做的。我只是将输入文件转换为 csv（除了我使用“|”作为分隔符，因为数据集包含字符串）。感谢大家的意见，但我忘了提到这是一个 2GB 的数据文件，所以我不想对我那可怜的过度工作的笔记本电脑做任何过于密集的事情。

import pandas as pd


ofile = open("out_file.csv", 'w')
ifile = open("in_file.txt", 'r', encoding='cp1252')

for l in ifile:
  if l == '\n':
    ofile.write('\n')
  else:
    ofile.write(l.split(':')[1][:-1] + '|')

ofile.close()
ifile.close()

然后我使用以下方法打开数据框：

import pandas as pd
df =pd.read_csv('out_file.csv', sep="|", skipinitialspace=True, index_col=False)

在获得@aaj-kaal 提出的包含以下代码的列表后：

import pandas as pd
with open('data.txt', 'rt') as fin:
    lst = [line[:-1] for line in fin if line[:-1]]

您可以通过以下方式直接获取数据框：

dict_df=pd.DataFrame()
dict_df['name'] = [ele.split(':')[1] for ele in lst if ele.startswith('name:')]
dict_df['rating'] = [ele.split(':')[1] for ele in lst if \
                    ele.startswith('rating:')]
dict_df['description'] = [ele.split(':')[1] for ele in lst\
                         if ele.startswith('description:')]
dict_df

输出

name    rating          description
0       hello_world 5   basic program
1       python  10      programming language

通用建议：

import pandas as pd
def from_txt_transposed_to_pandas(file):
    """
    take a txt file like this:

    "
    name: hello_world
    rating: 5
    description: basic program

    name: python
    rating: 10
    description: programming language 
    "

    -of any length- and returns a dataframe.
    """
    tabla = pd.read_table(file)
    cols = list(set([x.split(":")[0] for x in tabla.iloc[::,0]]))
    tabla_df= pd.DataFrame(columns = cols)
    elem = list(tabla[tabla.columns[0]])+[tabla.columns[0]]
    for n in range(len(cols)):  
        tabla_df[cols[n]]= [x.split(":")[1] for x in elem if\ 
        x.startswith(cols[n])]
    return tabla_df