You receive a hard drive of gigabytes upon gigabytes of Panda data. There are excels pointing to excels with little to no documentation. Some have unique identifiers, corresponding to each csv file. Some have a dozen headers while some have hundreds of columns in a single dataset. If there was going to be the key to Pandas hooking up it would be here. Each dataset seemed to always track the number of offspring and number of coitus linking to a plethora of panda stats and panda partner stats. You never thought you’d ever want to know the stats on Panda Penis girth size, but damn, you could estimate it if you wanted to. You’ve got all the data, you even have a repo marked “PANDA_Sex_classifier_algorithm_v8_17_Sep22” that appears to be the old algorithm. What do you do?
You look at the data
Published by B McGraw
B McGraw has lived a long and successful professional life as a software developer and researcher. After completing his BS in spaghetti coding at the department of the dark arts at Cranberry Lemon in 2005 he wasted no time in getting a masters in debugging by print statement in 2008 and obtaining his PhD with research in screwing up repos on Github in 2014. That's when he could finally get paid. In 2018 B McGraw finally made the big step of defaulting on his student loans and began advancing his career by adding his name on other people's research papers after finding one grammatical mistake in the Peer Review process. View more posts