Python Pandas – Find unique values from a single column

To find unique values from a single column, use the unique() method. Let’s say you have Employee Records in your Pandas DataFrame, so the names can get repeated since two employees can have similar names. In that case, if you want unique Employee names, then use the unique() for DataFrame.

At first, import the required library. Here, we have set pd as an alias −

import pandas as pd

At first, create a DataFrame. Here, we have two columns −

dataFrame = pd.DataFrame(
   {
      "EmpName": ['John', 'Ted', 'Jacob', 'Scarlett', 'Ami', 'Ted', 'Scarlett'],"Zone": ['North', 'South', 'South', 'East', 'West', 'East', 'North']
   }
)

Fetch unique Employee Names from the DataFrame column “EmpName” −

dataFrame['EmpName'].unique()

Example

Following is the complete code −

import pandas as pd

# Create DataFrame
dataFrame = pd.DataFrame(
   {
      "EmpName": ['John', 'Ted', 'Jacob', 'Scarlett', 'Ami', 'Ted', 'Scarlett'],"Zone": ['North', 'South', 'South', 'East', 'West', 'East', 'North']
   }
)

print("DataFrame ...\n",dataFrame)

# Fetch unique value from a single column
print(f"\nUnique Name of Employees = {dataFrame['EmpName'].unique()}")

Output

This will produce the following output −

DataFrame1 ...
    EmpName   Zone
0      John  North
1       Ted  South
2     Jacob  South
3  Scarlett   East
4       Ami   West
5       Ted   East
6  Scarlett  North
Unique Name of Employees = ['John' 'Ted' 'Jacob' 'Scarlett' 'Ami']