For example, I've used it to crank out random temperature histograms in the past[2], and even plotted some long-term averages to decide on temperature and precipitation ranges when going on camping trips. It's really useful if you're willing to work with the data a tiny bit. You're getting csv files, so it's not terrible to work with in any way via Python or R, or whichever data-friendly language/tool you want to use.
[1] http://cdiac.ornl.gov/epubs/ndp/ushcn/ushcn_map_interface.ht...
[2] http://btus.us/decadal-histograms-of-monthly-yosemite-temper...
I realize that it's theoretically possible to get this working. But it's not easy. What I want is a way to enter a postal code and get a JSON response with the precipitation for the last week. Without having to convert to scientology, learn GeoDjango, license GIS software, read an 800 page manual on parsing a bytestream from a satellite, etc.
It wouldn't be terribly difficult to mechanize this and get all the data at once, but I thought you wanted to occasionally see how much it rained, not build a service out of this.
Does this page[1] not contain what you need?
I share the parent's sentiment; finding easy access to good weather data is hard.
Do you want your side project to be an experience in learning how to parse obscure formats and coordinating obsolete dependencies, or HTTP GET some JSON and immediately do something with the data?
They're literally giving you all of the data in a plaintext format with documentation, and you're still complaining?
Sure, having everything handed to you on a silver platter is nice, but why should they do your project for you?
You know what you get with a format that's not "modern"? A huge, mature set of tooling that works. For instance, without trying because just responding to this whinging is barely worth the wear on my keyboard, I'd be disappointed if OS X wouldn't cheerily open the file, and unarchive it into the original directory structure simply by typing "open weather_data.txt.gz" from a terminal window. In other words, one could script it. I'd show you how, but holding your hand leaves me with only one hand for typing.
> HTTP GET some JSON and immediately do something with the data
Well, that's the magic of JSON: any code I write just wondrously knows what to do it without me telling it how to parse it. How can poor ol' ASCII text possibly compete?
Why can't we ask for nice things, even if they are "free"?
How are you going to get a kid interested in programming historical weather analysis when he's got to figure out how to configure an entire stack just to query your dataset. If you really want my opinion, this should be an AI problem, not yet another tedious MVC application.
Furthermore, when I jump into projects, I am most definitely appreciative that there is a responsive system on the other end, no matter how much I'm getting paid. I'm not some noob and yes I have imported gigabytes of minimally-structured data into my own applications, but I don't want to have to do that every time. Especially just to tinker.
If you're not thinking about how your software development experience can be made quicker, more direct, and less painful, I pity you. Shit on JSON all you want, but I'll take a populated native object and a blinking cursor over FTP'd text files any day.
I'm not sure this particular hill is worth dying for. Remember, text was the universal transport long before JSON was (and probably will be long after).
wget -O - http://cdiac.ornl.gov/ftp/ushcn_daily/state01_AL.txt.gz | gunzip -c | in2csv -s schema.txt | csvjson
I once bought data from them for couple of hundred dollars.
http://www.wunderground.com/history/airport/KSFO/2015/10/28/...
Source: http://www.cnbc.com/2015/10/28/ibm-plans-to-acquire-the-weat...
api: http://www.wunderground.com/weather/api/d/docs
National weather service, http://weather.gov is my goto weather forecaster, but at the time I wrote the code, getting hourly data based on lat/long for several thousand locations (some outside the US) was problematic. and XML..
$ curl -s "http://www.wunderground.com/history/airport/KMSP/2015/09/31/MonthlyHistory.html?format=1" | grep -v Precip | cut -d "," -f 20https://www.ncdc.noaa.gov/data-access/land-based-station-dat...
There is also a link to the python script I made to scrape it
IBM is in the business of providing data about a whole lot of things. I would expect the cost for access to this data to go up, not down -- the majority people who care about how much it rained in the last week only care because they can make more money by knowing that.