Convert string to already existing variable (pandas)

Question

If I have a dataframe df and want to access the unique values of ID, I can do something like this.

UniqueFactor = df.ID.unique()

But how can I convert this into a function in order to access different variables? I tried this, but it doesn't work

def separate_by_factor(df, factor):

    # Separating the readings by given factor
    UniqueFactor = df.factor.unique()

separate_by_factor('ID')

And it shouldn't, because I'm passing a string as a variable name. How can I get around this?

I don't know how I can better word the question, sorry for being too vague.

You can access columns through string using [] operator like such df[factor].unique() — xxMrPHDxx
– xxMrPHDxx, Commented Jan 28, 2021 at 12:29

crissal · Accepted Answer · 2021-01-28 12:29:37Z

1

When you create a DataFrame, every column that is a valid identifier it's treated as an attribute. To access a column based on its name (like in your example), you need to use df[factor].unique().

answered Jan 28, 2021 at 12:29

crissal

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5 Comments

João Dionísio Over a year ago

This works, thank you :) However, do you know how I can do what I was trying to do? Actually passing an unknown variable like that? It could be useful in other situations

crissal Over a year ago

Actually, there are no scenarios where it's useful (it's useful only when if you already know your column name and access it, like df.ID)

João Dionísio Over a year ago

I believe it could be, if you are expecting a user input. Not for this particular situation, but reading a string and associating it to a variable seems like it could be of use

crissal Over a year ago

Then I suggest you to check out this thread and this too; my suggestion is to use dictionaries to do this with variables, and square-brackets access with dataframes

João Dionísio Over a year ago

thank you for the links! getattr function seems to do the trick as well!

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