Pandas dataframe reset index

Question


from decimal import Decimal
import pandas as pd

df = pd.DataFrame([
    ["1000123797207765", 0, 129.26, 0, 29.26],
], columns=pd.MultiIndex.from_tuples(
    [
        ("", "ID"),
        ("2022-09-01", "origin"),
        ("2022-09-01", "checked"),
        ("2022-09-02", "origin"),
        ("2022-09-02", "checked"),
    ]
))



                         2022-09-01         2022-09-02        
                 ID     origin checked     origin checked
0  1000123797207765          0  129.26          0   29.26

As above codes showed, I get a dataframe. Now I want to reset index to get a dataframe with below format

                         2022-09-01         2022-09-02        
                ID     origin checked     origin checked
  1000123797207765          0  129.26          0   29.26

How can I make it? Great thanks.

Asked By: jia Jimmy

||

Source

Answer 1

In pandas reset index mean set to default value, if need 'remove' first 0 is possible convert first column to index.

Reason is pandas DataFrame always has index.

print (df.index)
RangeIndex(start=0, stop=1, step=1)
    
df = df.set_index([('','ID')]).rename_axis('ID')
print (df)
                 2022-09-01         2022-09-02        
                     origin checked     origin checked
ID                                                    
1000123797207765          0  129.26          0   29.26

print (df.index)
Index(['1000123797207765'], dtype='object', name='ID')

Answered By: jezrael

Answer 2

What you want to do is to use the column "ID" as the index of the DataFrame. This can be done by the following line of code:

df = df.set_index('ID')

Answered By: Adrien Pavao

Pandas dataframe reset index

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