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from IPython.display import Image
Find a data-focused visualization on one of the following websites that is a negative example of the principles that Tufte describes in The Visual Display of Quantitative Information.
Upload the image for the visualization to this directory and display the image inline in this notebook.
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# Add your filename and uncomment the following line:
Image(filename='confusing graph part 1.PNG')
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Image(filename='confusing graph part 2.PNG')
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Image(filename='confusing graph part 3.PNG')
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Image(filename='confusing graph part 4.PNG')
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Describe in detail the ways in which the visualization violates graphical integrity and excellence:
YOUR ANSWER HERE
This image is used as a reference in the Time article yet you have to follow a link to get to the information. Not only do you have to follow a link to get to the data, this image consists of 4 zoomed out, full page screen shots. It clearly does not represent the most data in the smallest space possible with the least amount of ink. The figure itself is offsetting soley due to its emmense size. The data-ink ratio is very bad and the space is very uneffiencently used, most of the plot is unneeded blank space and there is much more ink dedicated to non-data things within the figure. The values for which the data point reperesent are vague and the labeling is a little ambiguous. For example it lists what is under each category, all of which also have pulldown menues that show more categories, which seems a little to complex. Due to the extreme length of the figure, once you get to the bottom it is difficult to compare the data to previous data near the top of the graph. The data is not presented in an efficient, precise way. It is very hard to tell if the data tells the truth about the data because there is so much going on in the figure.