Context Wanted to find the best place to live in the USA based on the weather, as a way to practice programming Python. Data is compiled from over 50 airports, at least one weather station per state. While I used the data set to determine the median dew point for each location for calendar year 2018, it's rich in other data as well: wind speed, pressures, rain fall, etc. Content Date range is January 1, 2018 to December 31, 2018. For most states, one station per state, except Pennsylvania which includes two stations. Also included are stations in American Samoa and Puerto Rico. Tips Recommend filtering out "SOD " from Report_Type - it's just a marker for the end of a day. Recommend filtering out (10) header lines within the dataset - inadvertent artifact of combining several sets. Some columns are interpreted as text/objects so recommend filtering out values with the letter "s" in the value. Acknowledgements Kudos to the National Oceanic & Atmospheric Association (NOAA) for making this Local Climatological Data available as CSV files. https://www.ncdc.noaa.gov/cdo-web/ https://www.ncdc.noaa.gov/cdo-web/datatools/lcd Inspiration Interested in seeing how the 2018 weather data compares to data from other years as a pragmatic view of the climate - concerned that weather data is becoming less publicly accessible, e.g. Weather Underground no longer has data links. Also, interested in how weather in the USA compares to the weather in other countries: I used dew point to determine how comfortable a location is throughout the year.