I have DataFrame df = pd.DataFrame({'col1': ["a","b","c","d","e"], 'col2': [1,3,3,2,6]}) that looks like
Input:
col1 col2
0 a 1
1 b 3
2 c 3
3 d 2
4 e 6
I would like to remove rows from "col1" that share a common value in "col2". The expected output would look something like...
Output:
col1 col2
0 a 1
3 d 2
4 e 6
What would be the process of doing this?
using this short code should do the trick
df.drop_duplicates(subset=['col2'], keep=False)
Explanation
we use drop_duplicates to (ovbiously) drop the duplicates, and we set the column(s) we want to drop from to be col2 as you requested, In order to drop all occurences (and not keep the first occurence of each duplicate for example) we use keep=False.
This will do the trick
from collections import Counter
df = pd.DataFrame({'col1': ["a","b","c","d","e"], 'col2': [1,3,3,2,6]})
c = Counter(df['col2'])
ls = [k for k,v in c.items() if v==1]
_fltr = df['col2'].isin(ls)
df.loc[_fltr,:]