Yesterday, the weather was great. I pick up my girlfriend from her place, and we ride around with the windows down on the way to get food. We get to Taco Bell, and we’re just chilling in the drive thru line when I see this really sweet grey FR-S. It isn’t slammed, I think it’s about stock ride height. The aftermarket wheels looked nice, and there was a tasteful spoiler. For context, I really wanted an 86 but ended up with a Focus ST. I love my ST with all my heart, but I still get excited when I see a nice 86. Maybe this was dumb on my part, but I decide to take a photo so I could asshow my roommate, who’s a huge auto enthusiast too.
A few minutes later, the guy in his FR-S pulls up next to me while I’m at the drive thru window, drops his windows, rips a cloud of vape (not tryna hate on vaping, my Juul helped me quit smoking), makes a kissing sound at me, yells “Oh, you got an ST? That’s cute,” bangs the needle on the rev limiter so everyone in the TB parking lot could hear his exhaust, and dumps the clutch to speed through the lot.
After that, he drove down the block and sat there waiting for me, but drove away after I went the other direction. Granted, people around here (Texas) have really gotten aggressive while driving since the weather became nice, but I still think this guy’s a dick on his own accord. Not gonna lie, it did hurt my feelings a bit that a fellow enthusiast who owns one of my dream cars just shat on my ST like that. Then again, if that’s what the 86 community is like around here, I’m not sure if I wanna be apart of it.
TL;DR: A guy with an 86 hated on my FoST because I took a photo of his car.
So i have data with massive amounts of metadata. What are the best practices for reading in, aggregating, and displaying it? I can do it, but it isn’t very elegant. More specifically i end up with dozens of subsetted data frames, plots, etc.
For example, i have a gigantic table of enviro samples. To aggregate or process data i end up subsetting to smaller more specific frames. These start to take up memory. So, i rm() when im done with it. Is there a more memory efficient way or elegant way to do this?
I am going to be working with dna sets with 200+ million observations over hundreds of sets. My current approach isn’t going to work unless i have access to a computing cluster, which i don’t.
Title says it all. From humble beginnings Dubshed has opened its doors in a much bigger event and has allowed many other non Volkswagen-Audi-Group cars onto the showgrounds for more diversity while still staying true to its routes of having only the highest quality VWs on the showroom floor. Have a look.
Hello, so I am trying to figure out what statistical test I should use for this situation.
I want to see if the data I collected is significantly below a certain number (Lets say 10). Let’s say I collected 25 datasets and the average came out to 6.02 +/- 2.23. How can I prove this is statistically below 10 using lets say a p-value? Thank you.
Today is the third week I own my Mazda 6.
In the first week I noticed it uses ridiculous amounts of oil and yesterday the car felt slow as I merged onto the highway, the engine light started blinking and I pulled aside. Car running on 3 cylinders.
Made it home, no compression on cylinder 2 and sounds terrible. Probably valve related and will have to get the head rebuilt, which might total the car.
What is the worst luck you’ve ever had with any car you owned?