i will sure do return to view some more contents from your blog thanks. Then we can graph it using ggplot2.So nice reading through your article with many powerful tips and points.i most say i have gained a lot from reading through your content. The JSON is nested deeply, so this is kinda ugly…Īlmost there… now we just have to make a dataframe in the format that ggplot2 likes to have… Then, using the RJSONIO package, I parsed the data to create two vectors, my score for every week, and my opponent’s score for every week. I choose JSON with the “?format=json” at the end of the URL. Using the matchups endpoint, I can get the data for all of my games for the regular season (13 games). My league id should not work for you, as mine is a private league.
You will need your league id that is in the URL when you visit your normal Yahoo fantasy football page. Next, you have to discover your game key, league key, and team key. Pipedreams integration platform allows you to. I have my credentials saved to a text file that I read in, but you can use environment variables too, whatever you are comfortable with. Setup the Google Sheets API trigger to run a workflow which integrates with the Yahoo Fantasy Sports API. This page has information about the auth process. This entails registering an application with Yahoo and getting API keys.
The first step, obviously, is to authenticate with the Yahoo API and get a signature to attach to all of the requests. In this post, I will expand on this a little to downloading personal Yahoo fantasy football data and creating a graph showing my regular season results. I recently created a gist that demonstrated how to authenticate with the Yahoo API, using the httr package.
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