# Climate Normals

Climate normals provide an overview of the typical weather at a given location. Normals are usually calculated over a period of 30 years.

# Example

You can use the Normals class to retrieve mean data and prepare the records for further processing. For more complex analysis and visulization tasks you can utilize Pandas.

# Import Meteostat library and dependencies
from datetime import datetime
import matplotlib.pyplot as plt
from meteostat import Normals

# Get Normals data
data = Normals('10637', (1961, 1990))
data = data.fetch()

# Plot line chart including average, minimum and maximum temperature
data.plot(y=['tavg', 'tmin', 'tmax'])
plt.show()

# API

# Data Structure

Each month is represented by a Pandas DataFrame row which provides the average weather data recorded during that month. These are the different columns:

Column Description Type
station The Meteostat ID of the weather station (only if query refers to multiple stations) String
start The first year (YYYY) of the reference period Integer
end The last year (YYYY) of the reference period Integer
month The month, represented as an integer Integer
tavg The mean air temperature in °C Float64
tmin The mean minimum air temperature in °C Float64
tmax The mean maximum air temperature in °C Float64
prcp The mean monthly precipitation total in mm Float64
wspd The mean wind speed in km/h Float64
pres The mean sea-level air pressure in hPa Float64
tsun The mean sunshine total in minutes (m) Float64