Python: Pandas Dataframe select row by given index [duplicate]

Question

I have a pandas dataframe of this kind:

data = {'Index':[1a,2a,3a,4a], 'col1':[20.1,20.2,20.3,20.4], 'col2': [30.2,30.5,30.7,30.5]}
df1 = pd.DataFrame(data)
df1 = df1.set_index('Index')
print(df1)

output:

        col1  col2
Index            
1a      20.1  30.2
2a      20.2  30.5
3a      20.3  30.7
4a      20.4  30.5

Now my aim is to select the row with a specific index, say 2a, so the output should be:

        col1  col2
Index            
2a      20.2  30.5

I tried it with following command (see e.g. this tutorial):

df1.loc[df1['Index'] == 2]

but for some reason it does not work, why?

If you want the row with index 18, which can have any other location in the df, just do df.iloc[df.index == 18] — lukasgartmair
– lukasgartmair, Commented Jan 28, 2024 at 17:45

user17242583 · Accepted Answer · 2021-12-21 19:11:35Z

2

Just use .loc:

>>> df.loc['2a']
col1    20.2
col2    30.5
Name: 2a, dtype: float64

>>> df.loc['2a', 'col1']
20.2

answered Dec 21, 2021 at 19:11

user17242583

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