Use from datetime import date today = date.today()
day = today.strftime("%d/%m/%Y")
print(day)
to get today's date.
cast it to sting testday = str(day)
Compare ==
day == df_date
True or False
use loc to get row text
test_str = test.loc[1][0]
String = list in python soo
test_str[2]
'1'
ons. 13. jul. 2022 kl. 08:25 skrev Sid <flinkbyhe...@gmail.com>:
> Hi Team,
>
> I have a dataset like the below one in .dat file:
>
> 13/07/2022abc
> PWJ PWJABC 513213217ABC GM20 05.0000 6/20/39
> #01000count
>
> Now I want to extract the header and tail records which I was able to do
> it. Now, from the header, I need to extract the date and match it with the
> current system date. Also, for the tail records, I need to match the number
> of actual rows i.e 1 in my case with the values mentioned in the last row.
> That is a kind of pattern matching so that I can find '1' in the last row
> and say that the actual records and the value in the tail record matches
> with each other.
>
> How can I do this? Any links would be helpful. I think regex pattern
> matching should help.
>
> Also, I will be getting 3 formats for now i.e CSV, .DAT file and .TXT
> file.
>
> So, as per me I could do validation for all these 3 file formats using
> spark.read.text().rdd and performing intended operations on Rdds. Just the
> validation part.
>
> Therefore, wanted to understand is there any better way to achieve this?
>
> Thanks,
> Sid
>
--
Bjørn Jørgensen
Vestre Aspehaug 4, 6010 Ålesund
Norge
+47 480 94 297
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