def _weather_data_extraction(lat, lon):
start = datetime(2015, 1, 1)
end = datetime(2021, 1, 16)
stations = Stations()
stations = stations.nearby(lat, lon)
stations = stations.inventory('daily', (start, end))
station = stations.fetch(1)
data = Daily(station, start, end)
data = data.fetch()
return data
def meteostat(lat_degr,long_degr,alt_avrg,start_time,end_time):
#Retrieve nearest weather station
stations = Stations()
stations = stations.nearby(lat_degr, long_degr)
station = stations.fetch(1)
#Use Point to agregate nearby weather stations data for better accuracy
weather_point = Point(lat_degr, long_degr,alt_avrg)
weather_data = Hourly(weather_point, start_time - timedelta(0,7200), end_time + timedelta(0,7200))
weather_data = weather_data.fetch()
#Use weather data from nearest station if Point returns an empty dataset
if weather_data.empty:
weather_data = Hourly(station, start_time - timedelta(0,7200), end_time + timedelta(0,7200))
weather_data = weather_data.fetch()
return weather_data
"""
Example: Closest weather station by coordinates
Meteorological data provided by Meteostat (https://dev.meteostat.net)
under the terms of the Creative Commons Attribution-NonCommercial
4.0 International Public License.
The code is licensed under the MIT license.
"""
from meteostat import Stations
# Get weather station
stations = Stations()
stations = stations.nearby(50, 8)
stations = stations.inventory('hourly', True)
station = stations.fetch(1).to_dict('records')[0]
# Print name
print('Closest weather station at coordinates 50, 8:', station["name"])
Example: Simple chart
Meteorological data provided by Meteostat (https://dev.meteostat.net)
under the terms of the Creative Commons Attribution-NonCommercial
4.0 International Public License.
The code is licensed under the MIT license.
"""
from datetime import datetime
import matplotlib.pyplot as plt
from meteostat import Stations, Daily
# Time period
start = datetime(2018, 1, 1)
end = datetime(2018, 12, 31)
# Get a weather station
stations = Stations()
stations = stations.nearby(49.2497, -123.1193)
stations = stations.inventory('daily', (start, end))
station = stations.fetch(1)
# Get daily data
data = Daily(station, start, end)
data = data.fetch()
# Plot chart
data.plot(y=['tavg', 'tmin', 'tmax'])
plt.show()
# Downloading weather data
###############################################################################
start = datetime(2021, 1, 1)
end = datetime(2021, 12, 31)
container = []
retrived = []
retrivedIndex = []
notRetrived = []
notRetrivedIndex = []
for k, val in enumerate(uniqueLocations):
stations = Stations()
stations = stations.nearby(val[0], val[1])
station = stations.fetch(1)
data = Daily(station, start, end)
data = data.fetch()
if len(data) > 0:
data['week'] = data.index.isocalendar().week
ndst = data.groupby('week').mean()
localdf = ndst[['tavg', 'prcp', 'pres']]
disc = localdf.isna().sum().sum()
if disc > 40:
notRetrived.append(val)
notRetrivedIndex.append(k)
