如何从 Python DataFrame 列中的字符串中删除不需要的部分答案

【问题标题】：How do I remove unwanted parts from strings in a Python DataFrame column如何从 Python DataFrame 列中的字符串中删除不需要的部分
【发布时间】：2022-12-01 05:48:27
【问题描述】：

基于最初由 u/commandlineluser 在 reddit 上建议的脚本，我（作为 Python 新手）试图修改原始代码以删除不需要的部分，这些部分因列值而异。 Python 脚本涉及创建一个包含键和值的字典，并使用带有 str.replace 的列表理解。

（reddit 上 u/commandlineluser 的原始脚本的一部分）

extensions = "dat", "ssp", "dta", "v9", "xlsx"

（下一行是我对上面部分的修改，下面是完整的代码块）

extensions = "dat", "ssp", "dta", "20dta", "u20dta", "f1dta", "f2dta", "v9", "xlsx"

有些结果与我想要的不同。请看下面（我试过的）。

import pandas as pd
import re
data = {"full_url": ['https://meps.ahrq.gov/data_files/pufs/h225/h225dat.zip',
                     'https://meps.ahrq.gov/data_files/pufs/h51bdat.zip',
                     'https://meps.ahrq.gov/data_files/pufs/h47f1dat.zip',
                     'https://meps.ahrq.gov/data_files/pufs/h225/h225ssp.zip',
                     'https://meps.ahrq.gov/data_files/pufs/h220i/h220if1dta.zip',
                     'https://meps.ahrq.gov/data_files/pufs/h220h/h220hv9.zip',
                     'https://meps.ahrq.gov/data_files/pufs/h220e/h220exlsx.zip',
                     'https://meps.ahrq.gov/data_files/pufs/h224/h224xlsx.zip',
                     'https://meps.ahrq.gov/data_files/pufs/h036brr/h36brr20dta.zip',
                     'https://meps.ahrq.gov/data_files/pufs/h036/h36u20dta.zip',
                     'https://meps.ahrq.gov/data_files/pufs/h197i/h197if1dta.zip',
                     'https://meps.ahrq.gov/data_files/pufs/h197i/h197if2dta.zip']}
df = pd.DataFrame(data)
extensions = ["dat", "ssp", "dta", "20dta", "u20dta", "f1dta", "f2dta", "v9", "xlsx"]
replacements = dict.fromkeys((f"{ext}[.]zip$" for ext in extensions), "")
df["file_id"] = df["full_url"].str.split("/").str[-1].replace(replacements, regex=True)
print(df["file_id"])

注释输出

0         h225 (looks good)
1         h51b (looks good)
2        h47f1 (h47 -> desired)
3         h225 (looks good)
4      h220if1 (h220i -> desired)
5        h220h  (looks good)
6        h220e  (looks good)
7         h224 (looks good)
8     h36brr20 (h36brr -> desired)
9       h36u20 (h36 -> desired)
10     h197if1 (h197i -> desired)
11     h197if2 (h197i -> desired)

【问题讨论】：

标签： python regex

【解决方案1】：

我希望我已经理解你的问题了：

extensions = (
    "dat",
    "ssp",
    "dta",
    "v9",
    "xlsx",
)

df["file_id"] = df["full_url"].str.extract(
    "/([^/]+?)(?:20|f1|f2|(?<!r)r20|u20)?(?:" + "|".join(extensions) + r").zip"
)

print(df)

印刷：

                                                         full_url file_id
0          https://meps.ahrq.gov/data_files/pufs/h225/h225dat.zip    h225
1               https://meps.ahrq.gov/data_files/pufs/h51bdat.zip    h51b
2              https://meps.ahrq.gov/data_files/pufs/h47f1dat.zip     h47
3          https://meps.ahrq.gov/data_files/pufs/h225/h225ssp.zip    h225
4      https://meps.ahrq.gov/data_files/pufs/h220i/h220if1dta.zip   h220i
5         https://meps.ahrq.gov/data_files/pufs/h220h/h220hv9.zip   h220h
6       https://meps.ahrq.gov/data_files/pufs/h220e/h220exlsx.zip   h220e
7         https://meps.ahrq.gov/data_files/pufs/h224/h224xlsx.zip    h224
8   https://meps.ahrq.gov/data_files/pufs/h036brr/h36brr20dta.zip  h36brr
9        https://meps.ahrq.gov/data_files/pufs/h036/h36u20dta.zip     h36
10     https://meps.ahrq.gov/data_files/pufs/h197i/h197if1dta.zip   h197i
11     https://meps.ahrq.gov/data_files/pufs/h197i/h197if2dta.zip   h197i

【讨论】：