Getting Unique values from a column in Pandas dataframe

To get unique values from a column in a pandas DataFrame, you can use the unique() method.

Here's how you can do it:

Import Necessary Library:
First, make sure you've imported the pandas library:
```
import pandas as pd 
```

Sample DataFrame:

Let's consider a sample DataFrame:

data = { 'A': [1, 2, 3, 4, 5, 2, 4], 'B': ['a', 'b', 'c', 'a', 'b', 'b', 'd'] } df = pd.DataFrame(data)

Get Unique Values:

To get unique values from column 'A':

unique_A = df['A'].unique() print(unique_A) # Outputs: [1 2 3 4 5]

Similarly, for column 'B':

unique_B = df['B'].unique() print(unique_B) # Outputs: ['a' 'b' 'c' 'd']

If you want the number of unique values, you can use the nunique() method:

count_unique_A = df['A'].nunique() print(count_unique_A) # Outputs: 5

Additionally, if you want a Series of value counts, you can use the value_counts() method:

value_counts_A = df['A'].value_counts() print(value_counts_A)

This will return the frequency of each unique value in the column.