使用python从文本列中提取有意义的信息

Question

I have a table with the two columns. I have to extract the meaningful information out of it from the Notes column. ie I need to extract the date in one column and the information after the date in one column and then ID

Notes, ID
Movie Date 05-28-2018 Passed, 1010
MTD loan slip dated 8-10-14 the Issued, 1111
Max over date 10-2-15 and repaired, 11232

output-

Notes                               ID      Date        Status
Movie Date 05-28-2018 Passed        1010    5/28/2018   Passed
loan slip dated 8-10-14 Issued      1111    8/10/2014   Issued
Max over date 10-2-15 and repaired  11232   10/2/2015   repaired

Here is my code-

df = pd.read_sql('select * from <table>', engine)
searchfor = [' dated', ' date', ' Date', ' Dated']
df2 = df[df['Notes'] .str.contains('|'.join(searchfor), na = False)]
..................

Appreciate your help on this. Thank you.

Answer 1

I would some some loops for that.

---

Example :

import pandas as pd

df = pd.read_csv("data.csv")

searchforstatus = [' Passed', ' Issued', ' repaired']

for idx, row in df.iterrows():
    for c in searchforstatus:
        if c in row['Notes']:
            df.loc[idx, 'Status'] = c

---

Result

                                    Notes     ID     Status
0            Movie Date 05-28-2018 Passed   1010     Passed
1  MTD loan slip dated 8-10-14 the Issued   1111     Issued
2      Max over date 10-2-15 and repaired  11232   repaired

---

The data that I used can be found here: https://files.fm/u/npaceyd6#_

Answer 2

Regex after getting the rows from iterrows() can also extract information, if there can be many possibilities

  s = 'Movie Date 05-28-2018 Passed'
  p = re.search(r'Dated?\s(\d+-\d+-\d+)\s([a-zA-Z]+)',s)

p.group(1) will have the date value and p.group(2) will have the value 'Passed'. Hope this helps..