meteostat.TimeSeries.aggregate

Aggregation is an important tool in data analysis. Meteostat allows both time-wise and spatial aggregation.

Parameters

The freq parameter specifies the time series' frequency. For full specification of available frequencies, please see here (opens new window). If you want to aggregate across all weather stations, just set the spatial parameter to True.

Parameter	Description	Type	Default
freq	Group by the specified frequency	String	1H, 1D, 1MS
spatial	Calculate averages across weather stations	Boolean	False

Returns

A copy of self

Aggregate Functions

Meteostat uses the following aggregate functions:

• temp => mean
• dwpt => mean
• rhum => mean
• tavg => mean
• tmin => min
• tmax => max
• prcp => sum
• snow => max
• wdir => meteostat.utilities.aggregations.degree_mean
• wspd => mean
• wpgt => max
• pres => mean
• tsun => sum
• coco => max

Examples

Hourly

Get weekly weather data for Frankfurt Airport in December 2018.

from datetime import datetime
from meteostat import Stations, Hourly

start = datetime(2018, 12, 1)
end = datetime(2018, 12, 31, 23, 59)

data = Hourly('10637', start=start, end=end)
data = data.normalize()
data = data.aggregate('1W')
data = data.fetch()

print(data)

Daily

Get weekly weather data for Frankfurt Airport in 2018.

from datetime import datetime
from meteostat import Stations, Daily

start = datetime(2018, 1, 1)
end = datetime(2018, 12, 31)

data = Daily('10637', start=start, end=end)
data = data.normalize()
data = data.aggregate('1W')
data = data.fetch()

print(data)

Monthly

Get annual data for Frankfurt Airport from 2000 to 2018.

from datetime import datetime
from meteostat import Monthly

start = datetime(2000, 1, 1)
end = datetime(2018, 12, 31)

data = Monthly('10637', start, end)
data = data.normalize()
data = data.aggregate('1Y')
data = data.fetch()

print(data)