Answered by : wideeyed-wombat-j8eoy9er89v7

for col in df: print(df[col].unique())

Source : https://stackoverflow.com/questions/27241253/print-the-unique-values-in-every-column-in-a-pandas-dataframe | Last Update : Thu, 27 Aug 20

Answered by : luluisco

# get the unique values (rows)
df.drop_duplicates()

Source : http://www.datasciencemadesimple.com/get-unique-values-rows-dataframe-python-pandas/ | Last Update : Wed, 10 Jun 20

Answered by : fantastic-fish-wg87ug7a0dn5

1
# get the unique values (rows) by retaining last row
2
df.drop_duplicates(keep='last')

Source : https://www.datasciencemadesimple.com/get-unique-values-rows-dataframe-python-pandas/ | Last Update : Mon, 05 Oct 20

Answered by : vinayak-sharma

In [33]: df[df.columns[df.apply(lambda s: len(s.unique()) > 1)]]
Out[33]: A B
0 0 a
1 1 b
2 2 c
3 3 d
4 4 e

Source : https://stackoverflow.com/questions/16533421/comparing-rows-of-pandas-dataframe-rows-have-some-overlapping-values | Last Update : Thu, 27 May 21

Answered by : you

# Assuming the dataframe is already created and named 'df'
unique_values = df['Column'].unique()
print(unique_values)

Source : | Last Update : Tue, 19 Sep 23