import pandas as pd
data = {'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 = pd.DataFrame(data, index = ['Cochice', 'Pima', 'Santa Cruz', 'Maricopa', 'Yuma'])
df
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 |
5 rows × 4 columns
df['name']
Cochice Jason Pima Molly Santa Cruz Tina Maricopa Jake Yuma Amy Name: name, dtype: object
df[['name', 'reports']]
name | reports | |
---|---|---|
Cochice | Jason | 4 |
Pima | Molly | 24 |
Santa Cruz | Tina | 31 |
Maricopa | Jake | 2 |
Yuma | Amy | 3 |
5 rows × 2 columns
df[:2]
coverage | name | reports | year | |
---|---|---|---|---|
Cochice | 25 | Jason | 4 | 2012 |
Pima | 94 | Molly | 24 | 2012 |
2 rows × 4 columns
df[df['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 |
4 rows × 4 columns
df.ix['Maricopa']
coverage 62 name Jake reports 2 year 2014 Name: Maricopa, dtype: object
df.ix[:, 'coverage']
Cochice 25 Pima 94 Santa Cruz 57 Maricopa 62 Yuma 70 Name: coverage, dtype: int64
df.ix['Yuma', 'coverage']
70