Inspired by Fridays for Future demonstrations around the world, our first knitting project is a sweater showing the worldwide temperature rise since 1880. For this we used the Global Land-Ocean Temperature Index from a Study by NASA's Goddard Institute for Space Studies. Using the statistical programming language R, we visualized the temperature index as an area chart.
As defined by NASA, the index describes the change in global surface temperature relative to 1951-1980 average temperatures. A negative index means that the temperature was lower relative to the baseline period 1951-1980, wheras positive values equal an increase in temperature. All in all the study shows that the average temperature has risen rapidly since 1970.
First of all, we selected a knitting pattern for a sweater and calculated the number of knitting stitches in length and width that we have for the pattern on the front and back. We decided to use only the straight surface without slopes for the chart to keep it simple. In our case we had 80 stitches width and 73 stitches height per sweater side for the chart.
To convert our area chart to this area of stitches, we interpreted it as two tile plots with 80 columns and 73 rows each. We rescaled the years to a scale of 1 to 160 (80 + 80), and the temperature index to a scale of 1 to 73. We then plotted the rescaled data as tile plots. Each tile represents a stitch. The zero line of the area chart in the knitting pattern is at row 24. In the tile plot, those stitches per year that lie between row 24 and the rescaled temperature index must be colored.
The resulting tile plot can be used as a guideline for the knitting pattern. Additional labels like the row number and the stitch number per row help to keep track of the pattern while knitting.
During the rescaling and transformation of the data to a pixeled tile plot, we will loose some information. As you can see comparing the knitting pattern of the sweater with our area chart, the pattern is coarser, less detailed. Also the pattern is quite a knitting challenge for beginners, because in many rows we have blue stitches between the orange ones, where we have to carry the orange thread with every other blue stitch, so that we don't have yarn loops hanging around too loosely on the inside.
However, we are very happy with how our cuddly data visualization, which reminds us even on cold days that we all have to do something to stop global warming. If you like it, too, feel free to check out the data, our code and the knitting pattern on our GitHub page and knit your own sweater!