How to extract a DataFrame to obtain a nested array?

Question

I have a sample DataFrame as below: First column consists of 2 years, for each year, 2 track exist and each track includes pairs of longitude and latitude coordinated. How can I extract every track for each year separately to obtain an array of tracks with lat and long?

df = pd.DataFrame(
    {'year':[0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1], 
    'track_number':[0,0,0,0,1,1,1,1,0,0,0,0,1,1,1,1], 
    'lat': [11.7,11.8,11.9,11.9,12.0,12.1,12.2,12.2,12.3,12.3,12.4,12.5,12.6,12.6,12.7,12.8], 
    'long':[-83.68,-83.69,-83.70,-83.71,-83.71,-83.73,-83.74,-83.75,-83.76,-83.77,-83.78,-83.79,-83.80,-83.81,-83.82,-83.83]})

What is your desired output?

Michael
– Michael

2021-04-21 19:44:13 +00:00
Commented Apr 21, 2021 at 19:44 — Michael
– Michael, Commented Apr 21, 2021 at 19:44
Can you please share what you have tried thus far?

DotPi
– DotPi

2021-04-21 20:11:57 +00:00
Commented Apr 21, 2021 at 20:11 — DotPi
– DotPi, Commented Apr 21, 2021 at 20:11

Camilo Martínez M. · Accepted Answer · 2021-04-21 19:59:20Z

You can groupby year and then extract a numpy.array from the created dataframes with .to_numpy().

>>> years = []
>>> for _, df2 in df.groupby(["year"]):
        years.append(df2.to_numpy()[:, 1:]) 
>>> years[0]
    array([[  0.  ,  11.7 , -83.68],
           [  0.  ,  11.8 , -83.69],
           [  0.  ,  11.9 , -83.7 ],
           [  0.  ,  11.9 , -83.71],
           [  1.  ,  12.  , -83.71],
           [  1.  ,  12.1 , -83.73],
           [  1.  ,  12.2 , -83.74],
           [  1.  ,  12.2 , -83.75]])
>>> years[1] 
    array([[  0.  ,  12.3 , -83.76],
           [  0.  ,  12.3 , -83.77],
           [  0.  ,  12.4 , -83.78],
           [  0.  ,  12.5 , -83.79],
           [  1.  ,  12.6 , -83.8 ],
           [  1.  ,  12.6 , -83.81],
           [  1.  ,  12.7 , -83.82],
           [  1.  ,  12.8 , -83.83]])

Where years[0] would have the desired information for the year 0. And so on. Inside the array, the positions of the original dataframe are preserved. That is, the first element is the track; the second, the latitude, and the third, the longitude.

If you wish to do the same for the track, i.e, have an array of only latitude and longitude, you can groupby(["year", "track_number"]) as well.

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