如何将其转换为数据框并将其另存为 csv？

这与 Pandas 关系不大，更多与将非结构化源解析为结构化数据有关。尝试这个：

from ast import literal_eval
from enum import IntEnum

class LineType(IntEnum):
    BakeryName = 1
    Address = 2
    Ingredients = 3

data = []
with open('data.txt') as fp:
    line_type = LineType.BakeryName
    for line in fp:
        line = line.strip()

        if line_type == LineType.BakeryName:
            name = line # the current line contains the Bakery Name
            line_type = LineType.Address # the next line is the Bakery Address
        elif line_type == LineType.Address:
            address = line # the current line contains the Bakery Address
            line_type = LineType.Ingredients # the next line contains the Ingredients
        elif line_type == LineType.Ingredients and line == 'data not available':
            data.append({
                'Name': name,
                'Address': address
            }) # no Ingredients info available
            line_type = LineType.BakeryName # next line is Bakery Name
        elif line_type == LineType.Ingredients:
            # if the line does not follow the ingredient's format, we
            # overstepped into the Bakery Name line. Then the next line
            # is Bakery Address
            try:
                bakery_type, ingredients = line.split(':')
                ingredients = literal_eval(ingredients.strip())
                data.append({
                    'Name': name,
                    'Address': address,
                    'type': bakery_type,
                    'salt': ingredients[0],
                    'sugar': ingredients[1],
                    'water': ingredients[2],
                    'flour': ingredients[3],
                })
            except:
                name = line
                line_type = LineType.Address

df = pd.DataFrame(data)

这假设您的数据文件采用所示格式。轻微的偏差（例如，空白线）就会将其抛之脑后。