Category Archives: Data Visualization
Dear Students, There is a new Kaggle Visualization Competition in our honor! I encourage you all to enter it! I received this email from Will Cukierski from Kaggle. This email was sent to me and Chris Mulligan. (See the p.s. for the Legend of Chris Mulligan.) Yours, Rachel Chris and Rachel, Thanks to your blog […]
This is another part of the students’ final project. A small group designed a survey to assess their classmates on different dimensions that capture the skills of a data scientist, and administered the survey to their classmates. The questions were of the form “Do you know what ___ means?”, or “Have you ever implemented ____?”. The students were well aware of potential biases in their questions, the limitations of self-reporting, etc. The survey was a great first pass.
This is an innovative way of describing and visualizing Data Scientists — it captures the variablity among data scientists, and allows for the potential for effective Data Science teams to be constructed by creating “constellations” of these stars, or overlaying the stars on top of each other to create “complete” data science teams. The visualization and survey represented an improvement over the data science profiles I gave them at the beginning of the semester. This was a collaborative effort among many students including Adam Obeng, Eurry Kim, Christina Gutierrez, Kaz Sakamoto, and Vaibhav Bhandari. Full report of last lecture still to come.
Last night the students gave their guest lecture. It was awesome! We’ll have a more detailed report tomorrow, but this image was already posted on twitter, so I thought I’d get it up here as a sneak preview for the rest of the lecture. Part of the students’ design concept was constellations and stars, so they have another nice visualization of “data science profiles” as stars. It will make more sense when you see it. Kaz Sakamoto, Eurry Kim and Vaibhav Bhandari created this as part of a larger class collaboration.
Each Tuesday, Eurry Kim, a student in our class, picks one example of data visualization to share with us. This is the last one. Thanks for taking on this challenge this semester, Eurry. You did an awesome job! Eurry writes: With all this talk about big data, big potential, and big problems, I was feeling […]
Each Tuesday, Eurry Kim, a student in our class, picks one example of data visualization to share with us. Eurry writes: I was watching Amanda Cox’s EYEO talk on YouTube a couple of weeks ago and she said something that really stuck with me – There’s this idea that some detail you want to leave […]
Each Tuesday, Eurry Kim, a student in our class, picks one example of data visualization to share with us. This week we did it on a Wednesday. Eurry writes: A few people have asked me about my process for building visualizations. It’s kind of flattering! Well, it’s a simple answer and not far from what […]
Each Tuesday, Eurry Kim, a student in our class, picks one example of data visualization to share with us. Eurry writes: This past Thursday and Friday, I was able to volunteer at the Visualized Conference where I met and heard some interesting perspectives on data visualization. From Shan Carter (http://nyti.ms/XvM9BX) to the WNYC Data News Team (http://wny.cc/W28uBW), […]
Each Tuesday, Eurry Kim, a student in our class, picks one example of data visualization to share with us. This week is a little different. Eurry didn’t pick it– she created it! I asked if we could feature it. Eurry and Kaz Sakamoto, also a student in the class, submitted a visualization to the Hubway Challenge. Here is their submission. You can view the public leaderboard here, and vote for Kaz and Eurry’s submission! I’m excited to see students in our class collaborating in this way. Below I asked them to describe their collaborative process:
Each Tuesday, Eurry Kim, a student in our class, will pick one example of data visualization to share with us. Eurry writes in an email titled “Viz for the Stormy Week”: In light of Sandy, I was thinking about how crises pull people together and make them forget about petty differences — particularly political differences. Ha, […]
Each week Cathy O’Neil blogs about the class. Cross-posted from mathbabe.org. This week in Rachel Schutt’s Columbia Data Science course we had two excellent guest speakers. The first speaker of the night was Mark Hansen, who recently came from UCLA via the New York Times to Columbia with a joint appointment in journalism and statistics. […]