A US district judge William Alsup has dismissed Elon Musk's X Corp's #lawsuit against #BrightData, a data-scraping company accused of improperly accessing #X (formerly #Twitter) systems and violating both X terms and state laws when scraping and selling #data.
State or State Sponsored attack on BC Government systems happened a month ago but was kept secret until this week on advice from cyber security experts.
"A cyberattack on the Ascension health system across the U.S. diverted ambulances, caused patients to miss medical visits and blocked online access to their records"
In my latest blog post, I cover how to find specific strings in data columns using the str_detect function from the stringr package and base R functions. You'll see practical examples with both grepl for identifying matches and gregexpr for counting occurrences.
I've ended up with an inquiry from a #DataScience student interested in examples of #harm coming to people because of #data collection (especially in a war context, but open to anything). Do folks have any favorite pointers / examples I could pass along?
Learn efficient ways to collapse text by group in R! Explore base R's aggregate(), dplyr's group_by() and summarise(), and data.table's grouping. Mastering these techniques enhances data preprocessing skills. Try these examples with your datasets to optimize workflows. Happy coding! 📊💻
"Microsoft and OpenAI are reportedly working on a massive datacenter to house an AI-focused supercomputer featuring millions of GPUs. The Information reports that the project could cost "in excess of $115 billion" and that the supercomputer, currently dubbed "Stargate" inside OpenAI, would be U.S.-based."
So much could be done with that amount of money... such a huge waste.
"The Arsenical Books Database — part of the Winterthur Museum and the University of Delaware’s Poison Book Project — has identified hundreds of examples of 19th-century books that used [green pigments containing arsenic] in their covers and other binding components."
👍 In R, you can easily extract specific columns from a data frame by their numerical positions. For instance, to grab the second column from a data frame df, you can use df[, 2].
🙅♂️ You can also exclude columns by using negative indexing, such as df[, -2] to exclude the second column.
The political landscape in Maharashtra looks vastly different from what it was in 2019. While the BJP on paper is in alliance with the official factions of the 2 biggest regional parties in the state, the factions led by their founders stand against it. The charts below explains how BJP traded uncertainty for influence in Maharashtra.
Did you ever need to adjust some time series for the count of #EU members in a given year? I did. It turned out to be quite tedious, because I wanted to allow for the fact that not all enlargements happened at the first of January (so the membership count of that year is actually a fraction), and take lap years into account. Brexit included.