How to convert dataframe to dictionary in pandas WITHOUT index

Question

I have a dataframe df as follows:

| name  | coverage | |-------|----------| | Jason | 25.1     | 

I want to convert it to a dictionary. I used the following command in pandas :

dict=df.to_dict() 

The output of dict gave me the following:

{'coverage': {0: 25.1}, 'name': {0: 'Jason'}}  

I do not want the 0 in my output. I believe this is captured because of the column index in my dataframe df. What can I do to eliminate 0 in my output ( I do not want index to be captured.) expected output :

{'coverage': 25.1, 'name': 'Jason'}  

Answer 1

When I see your dataset with 2 columns I see a series and not a dataframe.

Try this: d = df.set_index('name')['coverage'].to_dict() which will convert your dataframe to a series and output that.

However, if your intent is to have more columns and not a common key you could store them in an array instead using 'records'. d = df.to_dict('r'). `

Runnable code:

import pandas as pd  df = pd.DataFrame({     'name': ['Jason'],     'coverage': [25.1] })  print(df.to_dict()) print(df.set_index('name')['coverage'].to_dict()) print(df.to_dict('r')) 

Returns:

{'name': {0: 'Jason'}, 'coverage': {0: 25.1}} {'Jason': 25.1} [{'name': 'Jason', 'coverage': 25.1}] 

And one more thing, try to avoid to use variable name dict as it is reserved.