Create new dataframe with minor changes

New to Julia
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Hi ,
I tried to create a new data frame with theminor changes from my original dataframe. But whenever i tried to change something in new dataframe, it gets changed in original as well. Can some one help me to solve this . here is the code i tried.

df1 = DataFrame(ID = (1:10), A = (11:20))
df2 = df1

df2[!,:A] = @. ifelse(df2.ID > 5, 30,df2.A)
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You should make a copy of value bound to df1 variable:

df2 = copy(df1)

df2 = df1 does not copy value. It just adds binding to the df2 name of a value bound to df1 name. This is discussed in Types · The Julia Language and additionally explained in chapter 2 of Julia for Data Analysis (the content should be available for you to view for free in the preview of the book).

A similar question is posted today for a second time so I also have written a post Values’ mutability in Julia | Blog by Bogumił Kamiński related to the issue of mutability (it covers a bit different aspect than = operator but I hope it will help you to understand the whole concept of mutable values better).

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Are you sure you’re not paying people to ask questions on here which are answered in your new book? :smiley:

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This was also astonishing to me. The issue of “binding vs copying” of value by assignment operator = is AFAICT not clearly explained in The Julia Manual. But maybe I missed the place where it is clearly laid out (in this case please let me know :smile:). It is mentioned eg in. bullet 2 of Noteworthy Differences from other Languages · The Julia Language, but I think it is not a general exposition of the topic.

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I think the traditional link given to people asking questions about why = sometimes seems to mutate and sometimes not was

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Nice - I have never seen this, I need to add it to my list of references.

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Also, note that if any of the elements of the columns are mutable themselves, and you may be mutate them, then maybe it is best to use deepcopy instead of copy.

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copy for data frame makes copy of columns (but not deepcopy).

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Yes? This is what I said. If you need to deepcopy the columns then call deepcopy over the DataFrame instead of copy.

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Ah - right. I misread it first.

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It seems to be covered in Base > Essentials section?

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That list really shows how poor = is given too much overwork by language designers, XD.