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View Poll Results: Which programs do you use day to day?
SAS 10 43.48%
Python 5 21.74%
R 8 34.78%
None of them because I have 42 other things to do 5 21.74%
Multiple Choice Poll. Voters: 23. You may not vote on this poll

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  #1  
Old 09-12-2019, 01:29 PM
Sheffey Sheffey is offline
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Default SAS, Python, and R

Which of these do you use in your day-to-day work? if any.
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Old 09-12-2019, 01:40 PM
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Some things require me to use SAS. Nothing really requires me to use R but I try to find opportunities to, especially if it means not having to use Access anymore.
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Old 09-12-2019, 01:47 PM
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I keep saying I'm going to learn R but then I look at the syntax and figure nah.

I have python but rarely think of anything to do with it.

I use SAS all the time.
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Old 09-12-2019, 01:54 PM
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I keep saying I'm going to learn R but then I look at the syntax and figure nah
What about R syntax turns you off to it? I really like R, especially when using the (dplyr) package--that has a lot of really intuitive formulas that are pretty useful.
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Old 09-12-2019, 01:57 PM
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Is this a fair representation?
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Old 09-12-2019, 02:24 PM
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Originally Posted by Childish Gambino View Post
Is this a fair representation?
Lol. I think using an example with non-english comments and ambiguous object names and regular expressions feels a bit like cheating. Also, without context / knowing what the person's trying to accomplish, it's hard to say "he could have done that easier / cleaner with method 'x' or formula 'y'".

ETA: That being said, that example sure does look confusing and annoying to learn if you have no background. That's why most people learn basics first and work their way up.
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Old 09-12-2019, 02:39 PM
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That's not a good way to code in R but unfortunately a lot of people teach that way. It's much better to keep everything in one dataset and not define separate vectors. Also, using 'dplyr' is much cleaner and is similar to SQL which most people are familiar with.

You can do things like
Code:
data %>% 
select (income, member_id, claims) %>% 
filter(income>50000) %>% 
group_by(member_id) %>% 
summarize(total_claims=sum(claims))
This will take a dataset, select 3 columns with names income, member_id, and claims then filter on the rows with income greater than 50k. Then, it will summarize the data by member_id with two columns of Member_ID and total claims.
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Old 09-12-2019, 02:41 PM
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Originally Posted by DjPim View Post
Lol. I think using an example with non-english comments and ambiguous object names and regular expressions feels a bit like cheating. Also, without context / knowing what the person's trying to accomplish, it's hard to say "he could have done that easier / cleaner with method 'x' or formula 'y'".

ETA: That being said, that example sure does look confusing and annoying to learn if you have no background. That's why most people learn basics first and work their way up.
I'm not trying to argue in bad faith, I was really asking. I didn't notice the comments.

But I guess even when I look at the basics, they seem bizarre and unnecessarily convoluted. I know you get used to things eventually. Maybe I'll try again.
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Old 09-12-2019, 02:48 PM
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Quote:
Originally Posted by Childish Gambino View Post
I'm not trying to argue in bad faith, I was really asking. I didn't notice the comments.

But I guess even when I look at the basics, they seem bizarre and unnecessarily convoluted. I know you get used to things eventually. Maybe I'll try again.
Compared to SAS, R is very convoluted. However, because of that you also have much more control over types of output by using R as well. That being said, I still prefer SAS. Possibly just because of my familiarity with it.
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Old 09-12-2019, 02:59 PM
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Quote:
Originally Posted by DjPim View Post
Some things require me to use SAS. Nothing really requires me to use R but I try to find opportunities to, especially if it means not having to use Access anymore.
Or SQL or SAS, just not access
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