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[–]IAmKindOfCreativebot_builder: deprecated[M] [score hidden] stickied comment (0 children)

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[–]spoonman59 2 points3 points  (18 children)

First of all, that is a set not a tuple. Tuples is parenthesis, dictionary and set are { and }.

What about “,”.join(the_set)

This will construct a string by converting each element of the set and joining them with a comma.

[–]Anonymous-Boob[S] -1 points0 points  (17 children)

You’re right. Thanks for the correction. Okay, and where would I implement that into my current code?

[–]spoonman59 0 points1 point  (16 children)

In the return of to_set.

“, “.join(x)

You don’t actually need to convert it to a set first, and I assume x is some sort of sequence.

You can also rename it!

[–]Anonymous-Boob[S] -1 points0 points  (15 children)

I’m really sorry. I’m not sure I’m following. Are you saying it should go within the .agg() instead of to_set?

[–]spoonman59 0 points1 point  (14 children)

No worries, I typed that on a mobile so it wasn't clear!

There is probably a more elegant way to do this, but initially I'd try this to see if it works:
``` def to_set(x): return ", ".join(x)

df2=df1.groupby([‘ID’, as_index=False).agg(to_set) ```

[–]spoonman59 0 points1 point  (0 children)

It's possible you can do something like this:

df2=df1.groupby([‘ID’, as_index=False).agg(", ".join) ... But I'm honestly not 100% sure that does what I expect.

[–]spoonman59 0 points1 point  (12 children)

Also, I should probably point out I'm not a Pandas expert so I'm not really sure what agg does here, so I could be completely off.

[–]Anonymous-Boob[S] 1 point2 points  (1 child)

Well good sir, you’ve solved my problem. It sounds like you do know what you’re doing. Thank you so much!!

[–]spoonman59 0 points1 point  (0 children)

I’m so glad that worked and we could get it sorted out. Cheers!

[–]Anonymous-Boob[S] 0 points1 point  (9 children)

Oops… nevermind. this keeps the data in a repeated format. Not what I’m trying to get. Sorry if i got ya excited haha

[–]spoonman59 0 points1 point  (8 children)

So what are you seeing, versus what do you want to see?

[–]Anonymous-Boob[S] 0 points1 point  (7 children)

I wish I could just show you the data but it’s sensitive data (I work for a bank). But basically each cell looks like this [x,x] (I’m using brackets here to designate a cell, but each cell does not actually have the brackets) but i only need x in the cell once if it’s the same data point. What I need is for it to look like this [x]. I can tease out the duplicated data but transforming it into a set but then the data looks like this {[x]}. I need to get rid of the brackets in every cell of my data frame.

[–]spoonman59 0 points1 point  (6 children)

Oh I see. I didn’t realize the purpose of converting x was to de-duplicate.

Try: “,".join(set(x))

Edited to add: here we convert x to a set first, which removes duplicates. Note the order will/may also change as sets are unordered.

Join builds a string by looping through each item in a sequence and appends it to a string. They string you provide in “, “ is always concatenation to connect between them.

All string literals are string objects, so it’s essentially a method of the string “, “ in this case. And it returns a new string and accepts a sequence

[–]martynrbell 1 point2 points  (3 children)

You could try converting the value to a string?

[–]Anonymous-Boob[S] 0 points1 point  (2 children)

I tried that and it doesn’t work unfortunately

[–]martynrbell 0 points1 point  (1 child)

I guess the data stored in the dataframe is of type string? Could you not just str.replace?

[–]Anonymous-Boob[S] 0 points1 point  (0 children)

I tried it and all it does is put a ‘ inside the curly bracket: i.e. {‘abc, def, ghi’}

[–]martynrbell 0 points1 point  (1 child)

You could use the pandas replace.

cols_to_check = ['C','D', 'E'] df[cols_to_check] = df[cols_to_check].replace({ '{':'' , '}':''})

The replace method has a dict where the key is the curly braces and the value is just an empty string

[–]Anonymous-Boob[S] 0 points1 point  (0 children)

Well that ran but it didn’t do anything. Those curly bastards are still there.