Using Ggplot2 to plot last.fm top 100 albums
I found out that last.fm had made data files available for their Best of 2011 artist list, and I thought it’d be a great opportunity to learn some more about data management in R and Ggplot2.
I began by downloading and importing the tab separated data file
from last.fm (TSV).
Then I did some data cleanup, because one row just contained junk and some columns were unnecessary. I also removed all entries after row 100.
I did a search for missing values, but none were found.
The XML-file contained information about artists location. So I loaded
it and cleaned it up a bit. The location column was a bit messy so I
edited manually in statas data editor, I figured it was the easiest
way. I then read the edited data file back into R and combined that
data.frame
with the rest of the data from the TSV-file.
I tried plotting this data.frame
with ggplot but the location
variable contained 17 countries, which made a messy plot. Therefore I
choose to group some countries under the label “other”.
I still wasn’t satisfied with the plot, because it wasn’t sorted after
album plays. I tried quite a lot of different methods of sorting the
data.frame
before figuring out how to do it successfully with
reorder()
.
I wanted my plot to have readable decimal notation so I created my own x-breaks.
I also used my own custom colors for the plots legend, which I saved in
a list before initiating ggplot2
.
Then, at last, I drew the plot with ggplot2
.
We can see that the plot is dominated by USA and UK and that Adele and
Lady Gaga got exponentially more album plays than the rest. To give a
summary of $location
I used summary()
.
Which gave the following:
Written by Kristoffer Magnusson, a researcher in clinical psychology. You should follow him on Twitter and come hang out on the open science discord Git Gud Science.
Published March 22, 2012 (View on GitHub)
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I've been looking for applets that show this for YEARS, for demonstrations for classes. Thank you so much! Students do not need to tolarate my whiteboard scrawl now. I'm sure they'd appreciate you, too.l
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You finally helped me understand correlation! Many, many thanks... 😄
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Good stuff! It's been so helpful for teaching a Psych Stats class. Cheers!
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Excellent and informative visualizations!
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I wish I could learn more from you about stats and math -- you use language in places that I do not understand. Cohen's D visualizations opened my understanding. Thank you
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Thank you, Kristoffer
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Love your visualizations!
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Thanks. I really love the simplicity of your sliders. Thanks!!
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Thanks for making this Interpreting Correlations: Interactive Visualizations site - it's definitely a great help for this psych student! 😃
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Keep the visualizations coming!
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Your visualizations really help me understand the math.
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Great work!
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Thank you for building such excellent ways to convey difficult topics to students!
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Really wonderful visuals, and such a fantastic and effective teaching tool. So many thanks!
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I really like your work.
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You're awesome. I have students in my intro stats class say, "I get it now," after using your tool. Thanks for making my job easier.
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Incredibly useful tool!
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Thanks for the assistance for RSCH 8210.
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Hi Kristoffer, many thanks for making all this great stuff available to the community!
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Really helpful visualisations, thanks!
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This is amazing stuff. Very slick.
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Thanks so much for creating this! Really helpful for being able to explain effect size to a clinician I'm doing an analysis for.
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Thank you so much for creating these tools! As we face the challenge of teaching statistical concepts online, this is an invaluable resource.
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Fantastic resource. I think you would be well served to have one page indexing all your visualizations, that would make it more accessible for sharing as a common resource.
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Fantastic Visualizations! Amazing way to to demonstrate how n/power/beta/alpha/effect size are all interrelated - especially for visual learners! Thank you for creating this?
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Incredible visualizations and the best power analysis software on R.
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Great website!
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Thank you for this work!!
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Nice explanation and visual guide of Cohen's d
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thank you
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This site is superb!
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thank you for sharing your work.
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Thank you for the website, made me smile AND smarter :O enjoy your coffee! :)
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Struggling with statistics and your interactive diagram made me smile to see that someone cares enough about us strugglers to make a visual to help us out!😍
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Much thanks! Visualizations are key to my learning style!
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