1

I am new in python, so every tip will be helpful :)

I have a pandas dataframe with multiple columns and I need it converted to a new list of objects. Among all of dataframes columns I have two (lat, lon) that I want in my new object as attributes.

index city lat lon
0 London 42.33 55.44
1 Rome 92.44 88.11

My new list of object will need to look something like this:

[
  {'lat': 42.33, 'lon': 55.44}, 
  {'lat': 92.44, 'lon': 88.11}
]

More specifically I need this for Machine Learning with ML Studio.

Thanks!

Andrei Iovan
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2 Answers2

4

Use Pandas.DataFrame.to_dict(orient) to convert a DataFrame into a dictionary. There are multiple dictionary orientations; for your case use orient='records'

You also want to only select the lat & lon columns, like this:

df[['lat','lon']].to_dict(orient='records')

This will give you your result:

[{'lat': 42.33, 'lon': 55.44}, {'lat': 92.44, 'lon': 88.11}]

Here are some other orientations you could try out:

‘dict’ (default) : dict like {column -> {index -> value}}

‘list’ : dict like {column -> [values]}

‘series’ : dict like {column -> Series(values)}

‘split’ : dict like {‘index’ -> [index], ‘columns’ -> [columns], ‘data’ -> [values]}

‘records’ : list like [{column -> value}, … , {column -> value}]

‘index’ : dict like {index -> {column -> value}}
drew wood
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0

You can choose the columns you want and then use to_dict with orient='records' to get the required result

df[["lat", "lon"]].to_dict(orient='records')

Tom Ron
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  • Thanks @Tom Ron! I see it now in Pandas Documentation. https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_dict.html – Andrei Iovan Nov 29 '21 at 21:00