Pandas如何将列表内容转为DataFrame两列并清洗冗余信息

处理逻辑如下：

• 先过滤掉所有行首尾去空格后以-开头的注释行，这类内容都是取值说明类的冗余信息
• 对剩下的有效行，先去除首尾的空格、换行符
• 按第一个出现的冒号:将字符串拆分为序号部分和指标部分，指标部分再做去空格、移除末尾问号的处理
• 最后将处理好的两列数据转为DataFrame即可

import pandas as pd

# 原始列表
sorted_info = ['  1:  surgery?\n', '  2:  Age\n', '  3:  Hospital Number\n', '  4:  rectal temperature\n', '  5:  pulse\n', '          - is a reflection of the heart condition: 30 -40 is normal for adults\n', '  6:  respiratory rate\n', '  7:  temperature of extremities\n', '          - possible values:\n', '  8:  peripheral pulse\n', '          - possible values are:\n', '  9:  mucous membranes\n', '          - possible values are:\n', ' 10: capillary refill time\n', " 11: pain - a subjective judgement of the horse's pain level\n", '          - possible values:\n', ' 12: peristalsis\n', '          - possible values:\n', ' 13: abdominal distension\n', ' 14: nasogastric tube\n', '          - possible values:\n', ' 15: nasogastric reflux\n', ' 16: nasogastric reflux PH\n', ' 17: rectal examination - feces\n', ' 18: abdomen\n', ' 19: packed cell volume\n', ' 20: total protein\n', ' 21: abdominocentesis appearance\n', '          - possible values:\n', ' 22: abdomcentesis total protein\n', ' 23: outcome\n', '          - possible values:\n', ' 24: surgical lesion?\n', '          - possible values:\n', ' 25, 26, 27: type of lesion\n', ' 28: cp_data\n']

processed_data = []
for line in sorted_info:
    clean_line = line.strip()
    # 过滤冗余注释行
    if clean_line.startswith('-'):
        continue
    # 拆分序号和指标
    colon_pos = clean_line.find(':')
    col1 = clean_line[:colon_pos + 1]
    col2 = clean_line[colon_pos + 1:].strip().rstrip('?')
    processed_data.append([col1, col2])

# 生成符合要求的DataFrame
df = pd.DataFrame(processed_data, columns=['Col1', 'Col2'])
print(df)

运行代码后输出的DataFrame完全匹配你期望的结构，所有冗余信息都会被清理，指标内容会按要求拆分。

内容的提问来源于stack exchange，提问作者This_guy