{"id":8,"date":"2025-08-07T21:37:59","date_gmt":"2025-08-07T11:37:59","guid":{"rendered":"https:\/\/maxcoding.imaxim.org\/?p=8"},"modified":"2025-08-07T21:58:06","modified_gmt":"2025-08-07T11:58:06","slug":"create-a-weather-map-using-openweather-api-in-python","status":"publish","type":"post","link":"https:\/\/maxcoding.imaxim.org\/?p=8","title":{"rendered":"Create a weather map using OpenWeather API in\u00a0Python"},"content":{"rendered":"\n

Current weather data<\/a> provided by Open Weather API allows you to get weather information for free for any location on our planet. All you need is to register and get an API key to make requests.<\/p>\n\n\n\n

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In this post, I would like to show you how to generate a weather map for a list of cities showing the city name, temperature and weather type icon.<\/p>\n\n\n\n

Following libraries will be used to load and process data:<\/p>\n\n\n\n

For example, let\u2019s use the following locations:<\/p>\n\n\n

\nimport requests\nimport pandas as pd\nfrom geopy.geocoders import Nominatim\nfrom geopy.extra.rate_limiter import RateLimiter\n<\/pre><\/div>\n\n\n
For example, let\u2019s use the following locations:<\/p>\n\n\n
\ncities = [\n    ["Kyiv", "Ukraine"],\n    ["Warsaw", "Poland"],\n    ["Berlin", "Germany"],\n    ["London", "UK"],\n    ["Madrid", "Spain"],\n    ["Paris", "France"],\n    ["Rome", "Italy"],\n    ["Prague", "Czechia"],\n    ["Istanbul", "Turkey"],\n    ["Stockholm", "Sweden"],\n    ["Sofia", "Bulgaria"],\n    ["Bucharest", "Romania"],\n    ["Zurich", "Switzerland"],\n]\ndf = pd.DataFrame(cities, columns=["city", "country"])\n\n<\/pre><\/div>\n\n\n
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Since the OpenWeather API endpoint requires geographical coordinates such as latitude and longitude, we need to perform geocoding for each city. I would like to use the Nominatim<\/a> geocoder provided by OpenStreetMap.<\/p>\n\n\n\n
locator = Nominatim(user_agent=\"myGeocoder\")\ngeocode = RateLimiter(locator.geocode, min_delay_seconds=.1)\n\ndef get_coordinates(city, country):\n  response = geocode(query={\"city\": city, \"country\": country})\n  return {\n    \"latitude\": response.latitude,\n    \"longitude\": response.longitude\n  }\n\ndf_coordinates = df.apply(lambda x: get_coordinates(x.city, x.country), axis=1)\ndf = pd.concat([df, pd.json_normalize(df_coordinates)], axis=1)<\/code><\/pre>\n\n\n\n
After running this code. Additional columns with coordinates will be added to the pandas DataFrame:<\/p>\n\n\n\n
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We should store the open Weather API key in openweathermap_api_key<\/strong> variable. It will prompt you to enter the API key while running the code.<\/p>\n\n\n\n
from getpass import getpass\nopenweathermap_api_key = getpass('Enter Openweathermap API key: ')<\/code><\/pre>\n\n\n\n
Now we can get weather information for each location<\/p>\n\n\n\n
import datetime\n\ndef get_weather(row):\n\n  owm_url = f\"https:\/\/api.openweathermap.org\/data\/2.5\/weather?lat={row.latitude}&lon={row.longitude}&appid={openweathermap_api_key}\"\n  owm_response = requests.get(owm_url)\n  owm_response_json = owm_response.json()\n  sunset_utc = datetime.datetime.fromtimestamp(owm_response_json[\"sys\"][\"sunset\"])\n  return {\n      \"temp\": owm_response_json[\"main\"][\"temp\"] - 273.15,\n      \"description\": owm_response_json[\"weather\"][0][\"description\"],\n      \"icon\": owm_response_json[\"weather\"][0][\"icon\"],\n      \"sunset_utc\": sunset_utc,\n      \"sunset_local\": sunset_utc + datetime.timedelta(seconds=owm_response_json[\"timezone\"])\n  }\n\ndf_weather = df.apply(lambda x: get_weather(x), axis=1)\ndf = pd.concat([df, pd.json_normalize(df_weather)], axis=1)<\/code><\/pre>\n\n\n\n
As you can see in the code, we do the following processing after weather information loads:<\/p>\n\n\n\n