{"id":134750,"date":"2023-09-13T15:35:05","date_gmt":"2023-09-13T15:35:05","guid":{"rendered":"https:\/\/blog.finxter.com\/?p=1651525"},"modified":"2023-09-13T15:35:05","modified_gmt":"2023-09-13T15:35:05","slug":"python-code-for-getting-historical-weather-data","status":"publish","type":"post","link":"https:\/\/sickgaming.net\/blog\/2023\/09\/13\/python-code-for-getting-historical-weather-data\/","title":{"rendered":"Python Code for Getting Historical Weather Data"},"content":{"rendered":"\n
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5\/5 – (1 vote) <\/div>\n<\/p><\/div>\n

To get historical weather data in Python, install the Meteostat library using pip install meteostat<\/code> or run !pip install meteostat<\/code> with the exclamation mark prefix !<\/code> in a Jupyter Notebook. <\/p>\n

If you haven’t already, also install the Matplotlib library using pip install matplotlib<\/code>.<\/p>\n

Then, copy the following code into your programming environment and change the highlighted lines to set your own timeframe (start<\/code>, end<\/code>) and GPS location<\/code>:<\/p>\n

# Import Meteostat library and dependencies\nfrom datetime import datetime\nimport matplotlib.pyplot as plt\nfrom meteostat import Point, Daily # Set time period\nstart = datetime(2023, 1, 1)\nend = datetime(2023, 12, 31) # Create Point for Stuttgart, Germany\nlocation = Point(48.787399767583295, 9.205803269767616) # Get daily data for 2023\ndata = Daily(location, start, end)\ndata = data.fetch() # Plot line chart including average, minimum and maximum temperature\ndata.plot(y=['tavg', 'tmin', 'tmax'])\nplt.show()<\/pre>\n
This code fetches and visualizes the average, minimum, and maximum temperatures for Stuttgart, Germany<\/em>, for the entire year of 2023 using the Meteostat library<\/a>.<\/p>\n
Here’s the output:<\/p>\n
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Here are the three highlighted lines:<\/p>\n