With panda, when I print a dataframe, my result is
Description Test
0 Some 3
1 Thing e
2 Test NaN
For my front end I need to things, one is an object array of headers, and one an object array of rows. The first is not a problem, I made that with columns and a function. The rows however are trickier. I need this result:
[
{'id': 0, 'description':'some', 'test':'3'},
{'id': 1, 'description':'Thing', 'test':'e'},
{'id': 2, 'description':'Test', 'test':'NaN'},
]
The NaN is an empty, I forgot to pass a value for it. I could make a funtion and use pydash with some loops maybe, but is there a faster way to do this?
>Solution :
Reset current numeric index to a named column id and convert dataframe into list of records, with a single line:
df.reset_index(names='id').to_dict('records')
[{'id': 0, 'Description': 'Some', 'Test': '3'},
{'id': 1, 'Description': 'Thing', 'Test': 'e'},
{'id': 2, 'Description': 'Test', 'Test': nan}]