Closed peterjost closed 6 years ago
Nice Idea! Some people think bad of wordclouds but in this case it's a very powerful tool to summarize the data and bring across a couple of good points. Also, I like the idea of coloring the charts in the respective flag colors of a country. Can you compare groups of countries against one another (eg european vs asian countries)?
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I really like the fact that it's a simple idea but still very informative and it speaks in the heart of every person! I would like to see more correlations related to the topic of each anthem. And maybe pick the 2-3 more interesting ones in terms of the findings and explain more about the historical events that are connected to the lyrics so as to give it a serious journalistic spin.
The most frequent words of the national anthem of each european country as a word cloud:
No major changes.
Dataset is incomplete (only the neighbour countries of Switzerland yet). I have to fix it as fast as possible. Visuals are still basic.
No sound, no videos.
Visuals are still basic.
Headline: The Sound of blood and patriotism
Published website version: https://peterjost.github.io/studio-projects/nationalanthems/
Code repository: https://github.com/peterjost/studio-projects
Final data set(s): https://github.com/peterjost/studio-projects/blob/master/code/National_Anthems/National_Anthems.csv
It was difficult coming out of the starting blocks, to find the right pace through the project schedule and to get comfortable with the project-templates. And I had to create the dataset by my own, collect the date from different sources.
It is a first step - not more, not less. But there are many things to improve. I have no problem to find a story line. Handling the data, graph them and made the graphs nicer and more accurate with the best matching tool are the topics I have to work on.
Hi Peter, interesting topic. I've never seen this done before. First, yes, I agree on not liking word clouds. The problem with them is that if the word Tree and the word Constantinople are used at the same frequency, guess which one is more prominent....?!
Since you already have a good start using words-as-data let me suggest taking it a step further. With the age chart, I was going to suggest you flip the axis. We generally thinking of timelines as horizontal. But the how do you do the labeling if the dots stack up? What if, you used the names as the data, but like the word cloud but instead of a random arrangement (which is another reason I'm not a fan of word clouds) you simply stacked them up along the appropriate years?
You'd have something like
Also note here that I've arranged the countries alphabetically. I don't believe you have them in any order by year, so that is a question you should ask yourself whenever you have data: what order should they be in?
And what if you took that same idea and applied it to the count of the words in the lyrics. The words are the data. That would look something like this.
These are suggestions that are a little unconventional. It is important to get comfortable with the primary charting language first -- but, I thought I'd share this with you to keep in your back pocket for the future for next time you work with language (so you can skip word clouds!)
:)
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Pitch
Summary
On August 1st the Swiss celebrate their National Day. As in many other countries the National Day is THE DAY for playing the National Anthem. Before it starts I want to explore and to compare the National Anthems of Europe in terms of topic, word frequency, length, music style and more.
Type of visualization: word clouds, bars, mapping. Audio and video on the website would be a plus.
Details
Possible headline(s):
National Anthems - keep it short and violent // Violent French, fraternized Italians, devout Swiss
Data set(s): Lyrics and music files: http://www.laenderservice.de/hymnen/ Lyrics and additional information: https://www.bpb.de/system/files/dokument_pdf/4808b_hymnen-booklet_i_140429.pdf Music files (MP3): http://www.bpb.de/internationales/europa/europaeische-union/171039/die-nationalhymnen-der-28-eu-mitgliedstaaten
Code repository: https://github.com/peterjost/studio-projects
Possible problems/fears/questions:
Work so far
First examples of National Anthems word clouds.
Switzerland:
Germany:
Checklist
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[Project]
in the title