# Weather Stations

In contrast to other meteorological data interfaces Meteostat does not use a global data model. Instead, Meteostat provides weather observations and long-term climate statistics for individual weather stations. Understandably, no one knows the identifiers of each and every weather station. Therefore, Meteostat provides the Stations class - a simple interface for querying weather stations using several filters.

# Example

Using the Stations class is pretty straight-forward. Just initialize a new instance and apply some filters using a method.

# Import Meteostat library
from meteostat import Stations

# Get nearby weather stations
stations = Stations()
stations = stations.nearby(49.2497, -123.1193)
station = stations.fetch(1)

# Print DataFrame
print(station)

# API

# Data Structure

Each weather station is represented by a Pandas DataFrame row which provides meta information about the station. These are the different columns:

Column Description Type
id The Meteostat ID of the weather station String
name The English name of the weather station Object
country The ISO 3166-1 alpha-2 country code of the weather station String
state The ISO 3166-2 state or region code of the weather station String
wmo The WMO ID of the weather station String
icao The ICAO ID of the weather station String
latitude The latitude of the weather station Float64
longitude The longitude of the weather station Float64
elevation The elevation of the weather station in meters above sea level Float64
timezone The time zone of the weather station String
hourly_start The first day on record for hourly data Datetime64
hourly_end The last day on record for hourly data Datetime64
daily_start The first day on record for daily data Datetime64
daily_end The last day on record for daily data Datetime64
Last Updated: 12/8/2020, 11:28:13 AM