To explore how accurately the position of Mariah Carey’s hand during live performance reflects the pitch of the note she is singing.
I hypothesize that Mariah’s hand is not a perfect representation of the pitch but will produce a melody that is recognizable as the original song.
For our final project in Sculpting Data Into Everyday Objects, I worked with Ben Kauffman to visualize the cohort* dropout rate for high schools in New York City using data from the city’s Department of Education.
Each bead on the map represents one high school in New York City, placed in its geographic location. The length of the string represents how many students dropped out from that high school. A bead is glued at each end to hold the string in place and enable it to hang down. If there are multiple high schools at one location, extra beads are added.
For my Data Rep final, I am comparing the position of Mariah Carey’s hand to the note that she is singing and re-imagining her melodies as if played by an invisible theremin. See here for my initial post.
Work has been coming along well. This past week, I completed my two data collection tasks: track her hand and identify frames in which she begins singing a note.
I have some serious, deep, issue-tackling projects nearing completion. This is not one of them. For my final project in Data Representation, I will answer the question “how does the position of Mariah Carey’s flailing hand relate to the pitch of her voice?”
Hey internet, watch out! I can now produce these:
I used TileMill to color the states according to their Civil War allegiances, and Processing with Unfolding to place the dots. That dot way off in Idaho (Washington Territory at the time) is the site of the Bear River Massacre.
This week in Data Rep, we are working with a database of 500,000 hotels around the globe. The assignment is to create different maps for hotel star ratings, to find the northernmost hotel and to find the most remote hotel.
This week for Data Rep, we had to take a dataset from the Guardian’s Data Blog and represent it in two different ways – one “dry” and one specific to the data it represents. I chose the dataset titled “Pineapple Business Figures.” It contains a list of countries split into two categories: importers and exporters. For each country, the Guardian gives data for total kilograms of pineapples imported or exported, and the price at which they import or export at.
My first visualization plots total weight (x axis) against price per kilo (y axis). The size of the circle represents the total dollar amount. Importers are shown in yellow (the inside of a pineapple) and exporters are shown in green (the outside – cute, right?). The large circle on the far right is Costa Rica (1,112,090,000 kilos exported at $0.40 per kilo). The next one in is the USA (712,950,000 kilos imported at $0.74 per kilo).
My second visualization is a pineapple that represents pineapples! Exporters are on the left, importers are on the right. The height each shoot correlates to the total weight and the width of each shoot correlates to the price per kilo.