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Weather Data Analysis with NumPy & Matplotlib

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Weather Data Analysis with NumPy & Matplotlib

In this exercise we analyze weather data from the Global Climate Observing System (GCOS) surface network (GSN), a set of roughly 1000 stations established after the 1992 World Climate Conference for basic planetary climate monitoring. Open the Jupyter Notebook file (Weather Data Analysis.ipynb) to start the project.

Note: The files readme.txt, stations.txt, RSM00030710.dly, USW00014922.dly, USW00022536.dly, USW00023188.dly were downloaded in January 2019 from the U.S. NOAA Climate Data Online service, and specifically from URLs ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily (where stations.txt appears as ghcnd-stations.txt) and ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/gsn/STATIONCODE.dly. The DOI for the GHCN-daily dataset is 10.7289/V5D21VHZ. All information on government servers, such as this one, is in the public domain, unless stated otherwise, and may be used freely by the public.

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Weather Data Analysis with NumPy & Matplotlib


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