You might have noticed this part of the 2016 Emoji Report – part of the graphic features an emoji for each of our subscribers. It’s a randomized ordering of all the different skin tones of the 👩💻 and 👨💻 emoji, repeated [number of subscribers] / 12. Our subscriber count wasn’t exactly divisible by 12, so I […]
Brenda gave a great talk at Pycon-AU about using IPython and Pandas for her research. Slightly rough notes below. She has a dataset of 12 million tweets containing the word “science” – about a years worth of data, after filtering fout non-English tweets and spam. Using UTC for fewer timezone problems. Although still some – mostly […]