DataFrame: Filter rows and columns

"""
Python 3.6
2018.07.27
"""

"""
DataFrame
"""

import pandas as pd

""" Filter rows or columns, 2018.07.27 """
data_1 = {'name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'], 
        'year': [2012, 2012, 2013, 2014, 2014], 
        'reports': [4, 24, 31, 2, 3],
        'coverage': [25, 94, 57, 62, 70]}
df_1 = pd.DataFrame(data_1, index = ['Cochice', 'Pima', 'Santa Cruz', 
                                 'Maricopa', 'Yuma'])
#            coverage   name  reports  year
#Cochice           25  Jason        4  2012
#Pima              94  Molly       24  2012
#Santa Cruz        57   Tina       31  2013
#Maricopa          62   Jake        2  2014
#Yuma              70    Amy        3  2014

# View a column:
a = df_1['name']
#Cochice       Jason
#Pima          Molly
#Santa Cruz     Tina
#Maricopa       Jake
#Yuma            Amy
#Name: name, dtype: object
# View two columns:
b = df_1[['name', 'reports']]
#             name  reports
#Cochice     Jason        4
#Pima        Molly       24
#Santa Cruz   Tina       31
#Maricopa     Jake        2
#Yuma          Amy        3

# View first two rows:
df_1[:2]
#         coverage   name  reports  year
#Cochice        25  Jason        4  2012
#Pima           94  Molly       24  2012

# View rows where coverage is greater than 50:
df_1[df_1['coverage']>50]
#            coverage   name  reports  year
#Pima              94  Molly       24  2012
#Santa Cruz        57   Tina       31  2013
#Maricopa          62   Jake        2  2014
#Yuma              70    Amy        3  2014
# View rows where coverage is greater than 50 and reports less than 4:
df_1[(df_1['coverage']>50) & (df_1['reports']<4)]
#          coverage  name  reports  year
#Maricopa        62  Jake        2  2014
#Yuma            70   Amy        3  2014