How to to remove a double/nested for-loop? String to float transformation in python

I have the following polygon of a geographic area that I fetch via a request in CAP/XML format from an API

The raw data looks like this:

I store the requested items in a dictionary and then work through them to transform to a GeoJSON list object that is suitable for ingestion into Elasticsearch according to the schema I'm working with. I've removed irrelevant code here for ease of reading.

# fetches and store data in a dictionary
r = requests.get("https://alerts.weather.gov/cap/ny.php?x=0")
xpars = xmltodict.parse(r.text)
json_entry = json.dumps(xpars['feed']['entry'])
dict_entry = json.loads(json_entry)

# transform items if necessary
for entry in dict_entry:

    if entry['cap:polygon']:
        polygon = entry['cap:polygon']
        polygon = polygon.split(" ") 
        coordinates = []
        # take the split list items swap their positions and enclose them in their own arrays
        for p in polygon:
            p = p.split(",")
            p[0], p[1] = float(p[1]), float(p[0]) # swap lon/lat
            coordinates += [p]

        # more code adding fields to new dict object, not relevant to the question

The output of the p in polygon loop looks like:

[ [113.8659, 22.3243], [113.8691, 22.3333], [113.8691, 22.4288], [113.8742, 22.4316], [113.9478, 22.4724], [113.9951, 22.5101], [113.9985, 22.5099], [114.0017, 22.508], [114.0051, 22.5046], [114.0085, 22.5018], [114.0112, 22.5007], [114.0125, 22.5007], [114.0166, 22.502], [114.0204, 22.5038], [114.0245, 22.5066], [114.0281, 22.5067], [114.0371, 22.5057], [114.0409, 22.5051], [114.0453, 22.5041], [114.0494, 22.5025], [114.0511, 22.5023], [114.0549, 22.5035], [114.0564, 22.5047], [114.057, 22.5059], [114.0576, 22.5104], [114.0584, 22.512], [114.0608, 22.5144], [114.0637, 22.5163], [114.0657, 22.517], [114.0683, 22.5172], [114.0717, 22.5181], [114.0739, 22.5173] ]

Is there a way to do this that is better than O(N^2)? Thank you for taking the time to read.

Solution

O(KxNxM)

This process involves three obvious loops. These are:

Checking each entry (K)
Splitting valid entries into points (MxN) and iterating through those points (N)
Splitting those points into respective coordinates (M)

The amount of letters in a polygon string is ~MxN because there are N points each roughly M letters long, so it iterates through MxN characters.

Now that we know all of this, let's pinpoint where each occurs.

ENTRIES (K):
    IF:
        SPLIT (MxN)
        POINTS (N):
            COORDS(M)

So, we can finally conclude that this is O(K(MxN + MxN)) which is just O(KxNxM).