import pandas as pd
import numpy as np
brushFireRisk = pd.Series([34, 23, 12, 23], index = ['Bisbee', 'Douglas', 'Sierra Vista', 'Tombstone'])
brushFireRisk
Bisbee 34 Douglas 23 Sierra Vista 12 Tombstone 23 dtype: int64
brushFireRiskReindexed = brushFireRisk.reindex(['Tombstone', 'Douglas', 'Bisbee', 'Sierra Vista', 'Barley', 'Tucson'])
brushFireRiskReindexed
Tombstone 23 Douglas 23 Bisbee 34 Sierra Vista 12 Barley NaN Tucson NaN dtype: float64
brushFireRiskReindexed = brushFireRisk.reindex(['Tombstone', 'Douglas', 'Bisbee', 'Sierra Vista', 'Barley', 'Tucson'], fill_value = 0)
brushFireRiskReindexed
Tombstone 23 Douglas 23 Bisbee 34 Sierra Vista 12 Barley 0 Tucson 0 dtype: int64
data = {'county': ['Cochice', 'Pima', 'Santa Cruz', 'Maricopa', 'Yuma'],
'year': [2012, 2012, 2013, 2014, 2014],
'reports': [4, 24, 31, 2, 3]}
df = pd.DataFrame(data)
df
county | reports | year | |
---|---|---|---|
0 | Cochice | 4 | 2012 |
1 | Pima | 24 | 2012 |
2 | Santa Cruz | 31 | 2013 |
3 | Maricopa | 2 | 2014 |
4 | Yuma | 3 | 2014 |
5 rows × 3 columns
df.reindex([4, 3, 2, 1, 0])
county | reports | year | |
---|---|---|---|
4 | Yuma | 3 | 2014 |
3 | Maricopa | 2 | 2014 |
2 | Santa Cruz | 31 | 2013 |
1 | Pima | 24 | 2012 |
0 | Cochice | 4 | 2012 |
5 rows × 3 columns
columnsTitles = ['year', 'reports', 'county']
df.reindex(columns=columnsTitles)
year | reports | county | |
---|---|---|---|
0 | 2012 | 4 | Cochice |
1 | 2012 | 24 | Pima |
2 | 2013 | 31 | Santa Cruz |
3 | 2014 | 2 | Maricopa |
4 | 2014 | 3 | Yuma |
5 rows × 3 columns