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)
print('Wait')
time.sleep(4)
print('Go')
else:
container.append(ndst[['tavg', 'prcp', 'pres']])
retrived.append(val)
retrivedIndex.append(k)
print('Wait')
time.sleep(4)
return 1
else:
return 0
# Convert wind direction
data['wdir'] = data['wdir'].apply(direction)
# Filter for DEC and JAN only
time = data.index.get_level_values('time')
data = data.loc[((time.map(lambda x: x.month) == 12) |
(time.map(lambda x: x.month) == 1))]
# Group annually and aggregate
data = data.groupby(pd.Grouper(level='time', freq='1Y')).agg({
'wdir': 'sum',
'tavg': 'mean'
})
# Create chart
fig, ax = plt.subplots(figsize=(8, 6))
# Wind data
ax.set_ylabel('Days with North-East Wind', color='tab:blue')
data['wdir'].plot(
kind='line',
ax=ax,
color='tab:blue',
title=
'Correlation between North-East Wind and Low Mean Temperature in DE (DEC & JAN)'
)
from meteostat import Stations, Daily
from datetime import datetime
import matplotlib.pyplot as plt
# Get weather stations by WMO ID
stations = Stations(id=['D1424', '10729', '10803', '10513']).fetch()
# Get names of weather stations
names = stations['name'].to_list()
# Get daily data for 2019
data = Daily(stations, start=datetime(2000, 1, 1), end=datetime(2019, 12, 31))
data = data.aggregate(freq='1Y').fetch()
# Plot data
fig, ax = plt.subplots(figsize=(8, 6))
data.groupby(['station']).plot(x='time',
y='tmax',
kind='line',
legend=True,
ax=ax,
style='.-',
ylabel='Max. Annual Temperature (°C)',
title='Max. Temperature Report')
plt.legend(names)
# Show plot
plt.show()
