Pandas : transform a column containing list of strings to new columns for each value

Question

I'm trying to transform a column containing a list of values to a new set of columns, one for each value over all rows of that column.

For example given :

index    cat
0       ['a','b']
1       ['c','a','d']
2       ['e','b','c']

I'd like to get :

index    a       b       c        d         e
0        1       1       0        0         0
1        1       0       1        1         0
2        0       1       1        0         1

Could you help me and point me in the right direction?Thanks

ansev · Accepted Answer · 2019-11-27 16:20:20Z

3

Use:

#df=df.set_index('index') #if index is a column
d=df.explode('cat')
new_df=pd.crosstab(d.index,d.cat)
print(new_df)

Output

cat    a  b  c  d  e
row_0               
0      1  1  0  0  0
1      1  0  1  1  0
2      0  1  1  0  1

print(df)
         cat
0     [a, b]
1  [c, a, d]
2  [e, b, c]

answered Nov 27, 2019 at 16:20

ansev

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4 Comments

MFranc Over a year ago

Thanks, but where is that row_0 coming from?

ansev Over a year ago

I think it's due to the name of the index, you can use: pd.crosstab(df.index,df.YEAR,rownames=['myrowname']) to change the name or new_df.rename_axis(index=None) to remove it! pandas.pydata.org/pandas-docs/stable/reference/api/…

MFranc Over a year ago

Yea, should have read the doc before typing :d Well thanks a lot. I saw that the question got downvoted and see you have quite some rep, any clue on how to improve the question?

ansev Over a year ago

You're welcome :) I really don't understand why this question was rejected, I think it's quite clear and simple to understand. I already upvote:)

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