How to Extract Rows with Distinct Values in a Pandas DataFrame?

Distinct Values Row Retrieval

To extract rows based on distinct values within a column, specifically COL2, the following methods can be employed:

1. drop_duplicates with Keep First:

   df = df.drop_duplicates('COL2', keep='first')

   This retains the first occurrence of each unique value in COL2.

2. drop_duplicates with Keep Last:

   df = df.drop_duplicates('COL2', keep='last')

   This maintains the last occurrence of each unique value in COL2.

3. drop_duplicates with No Keep:

   df = df.drop_duplicates('COL2', keep=False)

   This removes all duplicate rows, resulting in only unique values in COL2.

Example:

Consider the following dataframe:

COL1	COL2
a.com	22
b.com	45
c.com	34
e.com	45
f.com	56
g.com	22
h.com	45

Using the keep_first method produces:

COL1	COL2
a.com	22
b.com	45
c.com	34
f.com	56

The keep_last method yields:

COL1	COL2
c.com	34
f.com	56
g.com	22
h.com	45

Lastly, using the keep_false method produces:

COL1	COL2
c.com	34
f.com	56

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