Daily Weather
Daily time series data is ideal for analyzing weather patterns over longer periods, such as weeks, months, or years.
🚀 Example
Let's fetch some daily temperature data for Frankfurt, Germany in 2018:
# Import Meteostat library and dependencies
from datetime import date
import meteostat as ms
# Set time period
start = date(2018, 1, 1)
end = date(2018, 12, 31)
# Get daily data
ts = ms.daily(ms.Station(id='10637'), start, end)
df = ts.fetch()
# Print DataFrame
print(df)
This is the output you would get:
temp tmin tmax rhum prcp snwd wspd wpgt pres tsun cldc
time
2018-01-01 8.1 6.6 11.2 70 1.1 0 26.6 59.8 1005.0 42 7
2018-01-02 6.4 5.2 8.0 74 5.8 0 22.0 50.8 1011.9 12 7
2018-01-03 8.1 5.3 10.4 72 6.3 0 36.4 83.9 999.1 144 6
2018-01-04 7.6 5.9 10.9 83 8.4 0 20.9 58.7 999.9 0 6
2018-01-05 8.5 7.1 10.2 83 4.8 0 18.7 59.4 1001.8 0 7
... ... ... ... ... ... ... ... ... ... ... ...
2018-12-27 -1.4 -2.1 -0.4 96 0.0 0 6.5 22.3 1030.7 0 8
2018-12-28 -0.5 -1.0 0.3 94 0.0 0 9.7 24.1 1031.8 0 8
2018-12-29 1.3 -0.7 4.6 92 0.8 0 16.9 45.7 1033.8 0 8
2018-12-30 7.2 4.5 8.3 76 0.0 0 17.3 48.6 1033.2 0 8
2018-12-31 6.8 5.6 9.0 94 0.0 0 9.7 43.9 1034.5 0 8
[365 rows x 11 columns]
🌥 Default Parameters
The default parameters for daily data requests are listed here.
🔍 API
Interface
meteostat.daily
Parameters
station
Weather station(s) or geographical point(s)
Data Type
str, Station, Point, List[str], List[Station], List[Point], DataFrame
Examples
Please refer to the chapter "Stations & Points" for detailed examples on how to specify the station parameter.
start
Start date of the desired period
Data Type
end
End date of the desired period
Data Type
parameters
Requested meteorological parameters
Data Type
List[Parameter]
Default Value
providers
Requested data providers
Data Type
List[Provider]
Default Value
[Provider.DAILY]