Get rows based on distinct values from one column

pandas, python

Solution

Use `drop_duplicates` with specifying column `COL2` for check duplicates:

df = df.drop_duplicates('COL2')
#same as
#df = df.drop_duplicates('COL2', keep='first')
print (df)
    COL1  COL2
0  a.com    22
1  b.com    45
2  c.com    34
4  f.com    56

You can also keep only last values:

df = df.drop_duplicates('COL2', keep='last')
print (df)
    COL1  COL2
2  c.com    34
4  f.com    56
5  g.com    22
6  h.com    45

Or remove all duplicates:

df = df.drop_duplicates('COL2', keep=False)
print (df)
    COL1  COL2
2  c.com    34
4  f.com    56

Problem

How can I get the rows by distinct values in `COL2`? For example, I have the dataframe below: ``` COL1 COL2 a.com 22 b.com 45 c.com 34 e.com 45 f.com 56 g.com 22 h.com 45 ``` I want to get the rows based on unique values in `COL2`: ``` COL1 COL2 a.com 22 b.com 45 c.com 34 f.com 56 ``` So, how can I get that? I would appreciate it very much if anyone can provide any help.

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