Data Wrangling in Python – How to Reindexing pandas Series And Dataframes

Reindexing pandas Series And Dataframes


/* Import Modules */
import pandas as pd
import numpy as np
/* Create a pandas series of the risk of fire in Southern Arizona */
brushFireRisk = pd.Series([34, 23, 12, 23], index = ['Bisbee', 'Douglas', 'Sierra Vista', 'Tombstone'])
Bisbee          34
Douglas         23
Sierra Vista    12
Tombstone       23
dtype: int64
/* Reindex the series and create a new series variable */
brushFireRiskReindexed = brushFireRisk.reindex(['Tombstone', 'Douglas', 'Bisbee', 'Sierra Vista', 'Barley', 'Tucson'])
Tombstone       23.0
Douglas         23.0
Bisbee          34.0
Sierra Vista    12.0
Barley           NaN
Tucson           NaN
dtype: float64
/*  Reindex the series and fill in any missing indexes as 0 */
brushFireRiskReindexed = brushFireRisk.reindex(['Tombstone', 'Douglas', 'Bisbee', 'Sierra Vista', 'Barley', 'Tucson'], fill_value = 0)
Tombstone       23
Douglas         23
Bisbee          34
Sierra Vista    12
Barley           0
Tucson           0
dtype: int64


/* Create a dataframe */
data = {'county': ['Cochice', 'Pima', 'Santa Cruz', 'Maricopa', 'Yuma'], 
        'year': [2012, 2012, 2013, 2014, 2014], 
        'reports': [4, 24, 31, 2, 3]}

df = pd.DataFrame(data)
county reports year
0 Cochice 4 2012
1 Pima 24 2012
2 Santa Cruz 31 2013
3 Maricopa 2 2014
4 Yuma 3 2014
/* Change the order (the index) of the rows */
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
/* Change the order (the index) of the columns */
columnsTitles = ['year', 'reports', 'county']
year reports county
0 2012 4 Cochice
1 2012 24 Pima
2 2013 31 Santa Cruz
3 2014 2 Maricopa
4 2014 3 Yuma

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