I am looking to try to set up a list with specific dictionaries. I would like the structure to be something similar to the following:
[{'label': 'Abdelnaby, Alaa', 'value': '76001'},
{'label': 'Abdul-Aziz, Zaid', 'value': '76002'},
{'label': 'Abdul-Jabbar, Kareem', 'value': '76003'}]
Currently, the data that I am pulling from is in a pandas dataframe. Example below...
PlayerID Name Current Player First Season Last Season
76001 Abdelnaby, Alaa 0 1990 1994
76002 Abdul-Aziz, Zaid 0 1968 1977
76003 Abdul-Jabbar, Kareem 0 1969 1988
51 Abdul-Rauf, Mahmoud 0 1990 2000
1505 Abdul-Wahad, Tariq 0 1997 2003
Please let me know if this is sufficient. Thanks so much for the help!
Select your columns, rename them and call to_dict
with orient='records'
to get a list of dicts,
(df.reindex(['Name', 'PlayerID'], axis=1)
.set_axis(['label', 'value'], axis=1, inplace=False)
.to_dict('r'))
# [{'label': 'Abdelnaby, Alaa', 'value': 76001},
# {'label': 'Abdul-Aziz, Zaid', 'value': 76002},
# {'label': 'Abdul-Jabbar, Kareem', 'value': 76003},
# {'label': 'Abdul-Rauf, Mahmoud', 'value': 51},
# {'label': 'Abdul-Wahad, Tariq', 'value': 1505}]
You can output JSON by changing .to_dict('r')
to .to_json(orient='records')
.
If performance matters, here is an optimised solution with list comprehension construction.
[dict(zip(('label', 'value'), r)) for r in df[['Name', 'PlayerID']].values]
# [{'label': 'Abdelnaby, Alaa', 'value': 76001},
# {'label': 'Abdul-Aziz, Zaid', 'value': 76002},
# {'label': 'Abdul-Jabbar, Kareem', 'value': 76003},
# {'label': 'Abdul-Rauf, Mahmoud', 'value': 51},
# {'label': 'Abdul-Wahad, Tariq', 'value': 1505}]
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