Hi there! I am fairly new to R and would like to know if I can use this amazing programming tool to help me achieve my goals.
Briefly, I am gathering historical weather data for each county in the US. I am gathering data through NOAA. Their website has a feature where I can request data in bulk. For example, I can request county data for all 39 counties in Washington state and the site will nicely compile all data into one Excel sheet. The problem is the Excel sheet does not contain 39 rows of data to account for each county. Since each county has multiple weather stations, I am looking at 512 rows of data!
My goal in using R is to use some GIS package to map out my historical weather data (e.g., temperature) by county, which I am sure I could do with some research. My main concern is magically separating all these weather stations and figuring out where each of them belong. For example, understanding if weather station A belongs in King county or Snohomish county, and plotting the data there.
With so many counties and weather stations to look at, having an R package to do this automatically would be a life-saver. I'm unsure if R can help me with this, but I've heard amazing things and how you can do practically anything with this.
Yes, R absolutely is capable for this type of task. There is nothing stopping you from working with millions of rows in R, so I wouldn't worry about this too much.
Did you try something already? Did you come across something you can't do? If so, it'll be easier to help you with a particular task.
It's not that I'm worried if R can handle millions of rows, but it's more about if a GIS package can read a location on a cell (e.g., Yakima) and identify which county it belongs to.
I am a bit overwhelmed by the amount of packages there are and will need to do some investigating to see which one works best for me.
To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one: