Basic ways to select rows from a pandas dataframe:

import pandas as pd

employees = pd.DataFrame({
    'EmpCode': ['Emp001', 'Emp002', 'Emp003', 'Emp004', 'Emp005'],
    'Name': ['John', 'Doe', 'William', 'Spark', 'Mark'],
    'Occupation': ['Chemist', 'Statistician', 'Statistician',
                   'Statistician', 'Programmer'],
    'Date Of Join': ['2018-01-25', '2018-01-26', '2018-01-26', '2018-02-26',
                     '2018-03-16'],
    'Age': [23, 24, 34, 29, 40]})

print("\nUse == operator\n")
print(employees.loc[employees['Age'] == 23])

print("\nUse < operator\n")
print(employees.loc[employees['Age'] < 30])

print("\nUse != operator\n")
print(employees.loc[employees['Occupation'] != 'Statistician'])

print("\nMultiple Conditions\n")
print(employees.loc[(employees['Occupation'] != 'Statistician') &
                    (employees['Name'] == 'John')])

C:\python\pandas examples>pycodestyle --first example5.py
 
C:\python\pandas examples>python example5.py
 
Use == operator
 
   Age Date Of Join EmpCode  Name Occupation
0   23   2018-01-25  Emp001  John    Chemist
 
Use < operator
 
   Age Date Of Join EmpCode   Name    Occupation
0   23   2018-01-25  Emp001   John       Chemist
1   24   2018-01-26  Emp002    Doe  Statistician
3   29   2018-02-26  Emp004  Spark  Statistician
 
Use != operator
 
   Age Date Of Join EmpCode  Name  Occupation
0   23   2018-01-25  Emp001  John     Chemist
4   40   2018-03-16  Emp005  Mark  Programmer
 
Multiple Conditions
 
   Age Date Of Join EmpCode  Name Occupation
0   23   2018-01-25  Emp001  John    Chemist
 
C:\python\pandas examples>