how to use map in index of pandas dataframe [duplicate]

Question

I want to create a new column on a pandas dataframe using values on the index and a dictionary that translates these values into something more meaningful. My initial idea was to use map. I arrived to a solution but it is very convoluted and there must be a more elegant way to do it. Suggestions?

#dataframe and dict definition
df=pd.DataFrame({'foo':[1,2,3],'boo':[3,4,5]},index=['a','b','c'])
d={'a':'aa','b':'bb','c':'cc'}

df['new column']=df.reset_index().set_index('index',drop=False)['index'].map(d)

Umm... df['new column'] = df.index.to_series().map(d) is one way... — Jon Clements
– Jon Clements, Commented Mar 1, 2018 at 19:30

Mike Müller · Accepted Answer · 2018-03-01 19:28:55Z

1

Creating a new series explicitly is a bit shorter:

df['new column'] = pd.Series(df.index, index=df.index).map(d)

answered Mar 1, 2018 at 19:28

Mike Müller

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BENY · Accepted Answer · 2018-03-01 19:39:48Z

0

After to_series, you can using map or replace

df.index=df.index.to_series().map(d)
df
Out[806]: 
    boo  foo
aa    3    1
bb    4    2
cc    5    3

Or we think about another way

df['New']=pd.Series(d).get(df.index)
df
Out[818]: 
   boo  foo New
a    3    1  aa
b    4    2  bb
c    5    3  cc

edited Mar 1, 2018 at 19:39

answered Mar 1, 2018 at 19:30

BENY

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