Assign binary value whether a column contains empty list

Question

I would like to assign a binary value (1 or 0) whether a column contains not empty/empty lists.

For example:

Country       Test
Germany        []
Italy         ['pizza']
United Kingdom ['queen', 'king','big']
France        ['Eiffel']
Spain         []

...

What I would expect is something like this:

Country       Test            Binary
Germany        []               0
Italy         ['pizza']         1
United Kingdom ['queen', 'king','big']    1
France        ['Eiffel']        1
Spain         []                0

...

I do not know how to use np.where or another to get these results.
I think to check if a column contains an empty list I should do something like this: df[df['Test'] != '[]']

getting this error: ValueError: Lengths must match to compare — user12092724
– user12092724, Commented Sep 28, 2020 at 1:44
Finally, a working solution: df['Test'].astype(bool).astype(int) — Marat
– Marat, Commented Sep 28, 2020 at 1:49
df['Binary'] = (df['Test'].str.len() != 0).astype(int) worked for me. — Joe Ferndz
– Joe Ferndz, Commented Sep 28, 2020 at 2:04

Joe Ferndz · Accepted Answer · 2020-09-28 02:07:49Z

1

You can do a simple check for length and based on the value, you can convert it to 0 or 1.

df['Binary'] = (df['Test'].str.len() != 0).astype(int)

While this is good, the most efficient way to do it was provided by @Marat.

df['Binary'] = df['Test'].astype(bool).astype(int)

The full code is here:

import pandas as pd
c = ['Country','Test']
d = [['Germany',[]],
['Italy',['pizza']],
['United Kingdom', ['queen', 'king','big']],
['France',['Eiffel']],
['Spain',[]]]

df = pd.DataFrame(data=d,columns=c)
df['Binary'] = df['Test'].astype(bool).astype(int)
print (df)

The output of this will be:

          Country                Test  Binary
0         Germany                  []       0
1           Italy             [pizza]       1
2  United Kingdom  [queen, king, big]       1
3          France            [Eiffel]       1
4           Spain                  []       0

edited Sep 28, 2020 at 2:07

answered Sep 28, 2020 at 1:59

Joe Ferndz

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Comments

Space Impact · Accepted Answer · 2020-09-28 01:47:37Z

0

Use str.len:

np.clip(df.Test.str.len(), 0, 1)
#or
(df.Test.str.len()==0).astype(int)

answered Sep 28, 2020 at 1:47

Space Impact

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