problem in setting index in pandas DataFrame

Question

I'm setting index for the given code as countries name but by using dataframe.set_index(index_name). I'm unable to update the index of the dataframe. I'm currently working on Python 3.7, why this code is not setting up the index?

import pandas as pd import numpy as np df1 = pd.DataFrame({'Country':['Nigeria','Bangladesh','China'], 'population':[89765,98744,654520], 'Birth_Rate':[23.54,34.43,20.3], 'Update_Date':['2016-01-18','2016-02-15','2016-02-03']}, columns = ['Country','population','Birth_Rate','Update_Date']) df2 = pd.DataFrame({'Country':['India','Sri Lanka','Dubai'], 'population':[98343,2453,57432], 'Birth_Rate':[33.54,44.44,23.3], 'Update_Date':['2016-01-18','2016-02-15','2016-02-03']}, columns =['Country','population','Birth_Rate','Update_Date']) df3 = df2.append(df1) df3.set_index('Country') print(df3)

I'm expecting this as output:

 Country population Birth_Rate Update_Date 0 India 98343 33.54 2016-01-18 1 Sri Lanka 2453 44.44 2016-02-15 2 Dubai 57432 23.30 2016-02-03 0 Nigeria 89765 23.54 2016-01-18 1 Bangladesh 98744 34.43 2016-02-15 2 China 654520 20.30 2016-02-03 but actual output is: population Birth_Rate Update_Date Country India 98343 33.54 2016-01-18 Sri Lanka 2453 44.44 2016-02-15 Dubai 57432 23.30 2016-02-03 Nigeria 89765 23.54 2016-01-18 Bangladesh 98744 34.43 2016-02-15 China 654520 20.30 2016-02-03

@SandeepKadapa No, it didn't work. The same output I'm getting as there is no change. — ishan
– ishan, Commented Jan 1, 2019 at 7:42
@SandeepKadapa thank you sir df3.set_index('Country',inplace = True) worked thank you sir for the instant help :). — ishan
– ishan, Commented Jan 1, 2019 at 7:48

DirtyBit · Accepted Answer · 2019-01-01 08:04:52Z

To set the DataFrame index (row labels) using one or more existing columns.

You can use the DataFrame.set_index(keys, drop=True, append=False, inplace=False, verify_integrity=False)

Where the parameters define:

keys : column label or list of column labels / arrays drop : boolean, default True

Delete columns to be used as the new index

append : boolean, default False

Whether to append columns to existing index

inplace : boolean, default False

Modify the DataFrame in place (do not create a new object)

verify_integrity : boolean, default False

Check the new index for duplicates. Otherwise defer the check until necessary. Setting to False will improve the performance of this method

import pandas as pd import numpy as np df1 = pd.DataFrame({'Country':['Nigeria','Bangladesh','China'], 'population':[89765,98744,654520], 'Birth_Rate':[23.54,34.43,20.3], 'Update_Date':['2016-01-18','2016-02-15','2016-02-03']}, columns = ['Country','population','Birth_Rate','Update_Date']) df2 = pd.DataFrame({'Country':['India','Sri Lanka','Dubai'], 'population':[98343,2453,57432], 'Birth_Rate':[33.54,44.44,23.3], 'Update_Date':['2016-01-18','2016-02-15','2016-02-03']}, columns =['Country','population','Birth_Rate','Update_Date']) df3 = df2.append(df1) df3.set_index('Country', inplace = True, append = True, drop = True) print(df3)

OUTPUT:

@HakunaMaData first of all that's a cheesy name! ;-) secondly, I used a online fiddler, pyfiddle.io cheers!

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