使用python使用正则表达式在多个变量字段中拆分字符串

Question

I have a dataframe were each row of a certain column is a text that comes from some bad formatted form where each 'field' is after the the 'field title', an example is:

col
Name: Bob Surname: Ross Title: painter age:34
Surname: Isaac Name: Newton Title: coin checker age: 42
age:20 Title: pilot Name: jack
this is some trash text Name: John Surname: Doe

As from example, the fields can be in any order an some of them could not exist.

What I need to do is to parse the fields so that the second line becomes something like:

{'Name': 'Isaac','Surname': 'Newton',...}

While i can deal with the 'pythonic part' I believe that the parsing should be done using some regex (also due to the fact that the rows are thousands) but I have no idea on how to design it.

Answer 1

Try:

x = df["col"].str.extractall(r"([^\s:]+):\s*(.+?)\s*(?=[^\s:]+:|\Z)")
x = x.droplevel(level="match").pivot(columns=0, values=1)

print(x.apply(lambda x: x[x.notna()].to_dict(), axis=1).to_list())

Prints:

[
    {"Name": "Bob", "Surname": "Ross", "Title": "painter", "age": "34"},
    {
        "Name": "Newton",
        "Surname": "Isaac",
        "Title": "coin checker",
        "age": "42",
    },
    {"Name": "jack", "Title": "pilot", "age": "20"},
]