如何将 python 中的字典列表拆分为具有值名称的列？

Question

I'm trying to build some custom reporting on Asana tasks using their API / Python 3.9.

The API has parameters to call 'custom_fields' but returns these custom fields as a nested list.

Specifically, when I parse the result into a pandas data frame, the column with the custom fields looks like this:

[
{'gid': '123', 'name': 'Priority', 'display_value': 'abc'}, 
{'gid': '456', 'name': 'Estimated Minutes', 'display_value': 'abc'}, 
{'gid': '789', 'name': 'Status 1', 'display_value': 'abc'}, 
{'gid': 'a12', 'name': 'Status 2', 'display_value': 'abc'}, 
{'gid': 'b24', 'name': 'Status 3', 'display_value': 'abc'}, 
{'gid': '745', 'name': 'Status', 'display_value': 'abc'}
]

I'd like to split this into columns such that:

• the column names are the 'name' attribute
• the column values are the 'display_value' attribute

Note that different rows in the data frame may have different varieties of the list / dict above. eg, some may have all the columns, some may have more, some may have fewer. Ultimately I'd like the end-state data frame to have columns that correspond to all the unique attributes in the whole data frame.

Thanks!

Answer 1

It's not clear what you're asking... is this what you want?

data = [
{'gid': '123', 'name': 'Priority', 'display_value': 'abc'}, 
{'gid': '456', 'name': 'Estimated Minutes', 'display_value': 'abc'}, 
{'gid': '789', 'name': 'Status 1', 'display_value': 'abc'}, 
{'gid': 'a12', 'name': 'Status 2', 'display_value': 'abc'}, 
{'gid': 'b24', 'name': 'Status 3', 'display_value': 'abc'}, 
{'gid': '745', 'name': 'Status', 'display_value': 'abc'}
]

df = pd.DataFrame(data)
df = df.set_index('name').T
print(df)

Output:

name          Priority Estimated Minutes Status 1 Status 2 Status 3 Status
gid                123               456      789      a12      b24    745
display_value      abc               abc      abc      abc      abc    abc