from meteostat import Stations, Daily
pageviews = pd.read_csv('pageviews.csv',
index_col='Date',
parse_dates=['Date'])
# Mehrere Threads für schnellere Downloads
Daily.max_threads = 6
# Zeitliche Periode
start = datetime(2019, 12, 1)
end = datetime(2020, 11, 30)
# 50 Zufällige Wetterstationen in Deutschland
stations = Stations()
stations = stations.region('DE')
stations = stations.inventory('daily', (start, end))
stations = stations.fetch(limit=50, sample=True)
# Tageswerte laden
weather = Daily(stations, start, end)
# Daten monatlich aggregieren
weather = weather.aggregate('1MS', spatial=True).fetch()
# Titel des Diagramms
TITLE = 'Interesse an Klimaanlagen & Max. Temperaturen in Deutschland'
# Darstellung der Seitenaufrufe
ax = pageviews['Klimaanlage'].plot(color='tab:blue', title=TITLE)
ax.set_ylabel('Seitenaufrufe', color='tab:blue')
"""
from datetime import datetime
import matplotlib.pyplot as plt
from meteostat import Stations, Daily
# Configuration
Daily.max_threads = 5
# Time period
start = datetime(1980, 1, 1)
end = datetime(2019, 12, 31)
# Get random weather stations in the US
stations = Stations()
stations = stations.region('US')
stations = stations.inventory('daily', (start, end))
stations = stations.fetch(limit=20, sample=True)
# Get daily data
data = Daily(stations, start, end)
# Normalize & aggregate
data = data.normalize().aggregate('1Y', spatial=True).fetch()
# Chart title
TITLE = 'Average US Annual Temperature from 1980 to 2019'
# Plot chart
data.plot(y=['tavg'], title=TITLE)
plt.show()
"""
Example: Select weather stations by country & state
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 stations in Ontario
stations = Stations()
stations = stations.region('CA', 'ON')
# Print count to console
print('Stations in Ontario:', stations.count())
