import DocCardList from '@theme/DocCardList';

The Meteostat Python library offers an easy and efficient way to access open weather and climate data through Pandas. It retrieves historical observations and statistics from Meteostat’s bulk data interface, which aggregates information from various public sources — primarily governmental agencies. Among Meteostat’s data providers are national weather services such as the National Oceanic and Atmospheric Administration (NOAA) and Germany’s Meteorological Service (DWD).

The Meteostat Python package is available through PyPI:

pip install meteostat

Let's plot 2018 temperature data for Frankfurt, Germany:

from datetime import date
import matplotlib.pyplot as plt
import meteostat as ms

# Specify location and time range
POINT = ms.Point(50.1155, 8.6842, 113)  # Try with your location
START = date(2018, 1, 1)
END = date(2018, 12, 31)

# Get nearby weather stations
stations = ms.stations.nearby(POINT, limit=4)

# Get daily data & perform interpolation
ts = ms.daily(stations, START, END)
df = ms.interpolate(ts, POINT).fetch()

# Plot line chart including average, minimum and maximum temperature
df.plot(y=[ms.Parameter.TEMP, ms.Parameter.TMIN, ms.Parameter.TMAX])
plt.show()

This is how the resulting chart looks: