Pandas - Replace int values in a list with string labels

Question

I have a dataframe with a column that includes a list of IDs. I've created a dictionary that associates the IDS with a string value. I'd like to replace the int values with the string.

Name       Label_ID  
Project1   [1]
Project2   [3,5]

label_map={1:'blue', 3:'green',5:'large'}

I want to get an output of:

Name       Label_ID  
Project1   [blue]
Project2   [green, large]

I've tried using:

test['Tags']=test['Label_ID'].map(label_map)

This code runs, but the resulting 'Tags' column is just NaNs. Any guidance would be appreciated.

Umar.H · Accepted Answer · 2020-02-25 23:08:33Z

1

IIUC, you can explode your df and then map the values then reapply an groupby along the index to get your values.

note your list may be a string so i've added the the literal eval method from the ast library.

the reason map won't work here is because your applying it a list, when you need to apply it series wise or element wise using apply.

from ast import literal_eval


df["Label_Map"] = (
    df["Label_ID"]
    .apply(literal_eval) # remove if not needed.
    .explode()
    .map(label_map)
    .groupby(level=0)
    .agg(list)
)

print(df)

       Name Label_ID       Label_Map
0  Project1      [1]          [blue]
1  Project2    [3,5]  [green, large]

edited Feb 25, 2020 at 23:08

answered Feb 25, 2020 at 22:42

Umar.H

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