What I am trying to do is extract elevation data from a google maps API along a path specified by latitude and longitude coordinates as follows:
from urllib2
Optimization of the accepted answer:
The accepted answer has some functioning problems, so I want to share my code that does not rely on urllib2:
import requests
from pandas import json_normalize
url = 'https://www.energidataservice.dk/proxy/api/datastore_search?resource_id=nordpoolmarket&limit=5'
response = requests.get(url)
dictr = response.json()
recs = dictr['result']['records']
df = json_normalize(recs)
print(df)
Output:
_id HourUTC HourDK ... ElbasAveragePriceEUR ElbasMaxPriceEUR ElbasMinPriceEUR
0 264028 2019-01-01T00:00:00+00:00 2019-01-01T01:00:00 ... NaN NaN NaN
1 138428 2017-09-03T15:00:00+00:00 2017-09-03T17:00:00 ... 33.28 33.4 32.0
2 138429 2017-09-03T16:00:00+00:00 2017-09-03T18:00:00 ... 35.20 35.7 34.9
3 138430 2017-09-03T17:00:00+00:00 2017-09-03T19:00:00 ... 37.50 37.8 37.3
4 138431 2017-09-03T18:00:00+00:00 2017-09-03T20:00:00 ... 39.65 42.9 35.3
.. ... ... ... ... ... ... ...
995 139290 2017-10-09T13:00:00+00:00 2017-10-09T15:00:00 ... 38.40 38.4 38.4
996 139291 2017-10-09T14:00:00+00:00 2017-10-09T16:00:00 ... 41.90 44.3 33.9
997 139292 2017-10-09T15:00:00+00:00 2017-10-09T17:00:00 ... 46.26 49.5 41.4
998 139293 2017-10-09T16:00:00+00:00 2017-10-09T18:00:00 ... 56.22 58.5 49.1
999 139294 2017-10-09T17:00:00+00:00 2017-10-09T19:00:00 ... 56.71 65.4 42.2
PS: API is for Danish electricity prices