Posts Tagged ‘ Tableau ’

History of a Chart 4. “This Is The New Flesh”

See also:

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View interactive chart here

We saw from “Where Did All the Rockstars Go?” that todays bands are being outperformed by their heroes from the 70s and 80s. Yet rock still has a significant presence in the charts, so where are these albums coming from.

I decided to have a look at the numbers of different artists in the charts over time.
Whether it’s the advent of the internet and sites like Myspace giving every small wannabe band a chance at success, or the
labels are switching the investment capabilities they have left from a few big artists to many smaller ones, but there are significantly more rock  bands in the charts now than there was in the 70’s.
However, this could be explained by the fact that those 70’s bands still have a presence in the charts today. We need to find out how many unique bands there are in each decade – bands that are appearing in the charts for the first time.

Method

  1. Filter the Data: In order to focus JUST on new bands, and not have figures that incorporated long running bands I performed a filter on the data using Tableau.  Grouping the years into decades and listing the artists that appeared, I was able to filter out the bands that had appeared in the decade before, leaving just unique artists.
  2. Group the data: I also opted to group the years into decades which went someway to dictate the chart style. I took this decision in order to create a simple, hard hitting chart (the impact of the data sometimes gets lots in a busy chart and was not necessary in this case). Had I decided to use full yearly data I would have been better using a line or narrow bar chart without animation or use of a symbol.
  3. Decide on Chart Design: After some variations I settled on a simplified bar chart (so self sufficient that it did not have axes), with stacked symbols, each representing a set number value and distinguished by colour (explained by a very simple key). I decided a simple stack clearly showed the respective values. I kept within the colour themes of the project by showing rock as black, pop as pink and other as grey.
  4. Search for Symbol: I instinctively went for the MAN logo first, as this is an option within Tableau and seemed to sum up the story. However, I also tried the chart with guitar symbol, simple squares, circles and stars. However, I settled on the MAN logo.
  5. Animate: I decided to animate the chart within Flash – with a gradual reveal of each column building  – “pop” first, then “other” then finally “rock”. I felt this gradual “reveal” of the rock category actually increased the impact when it became apparent that rock produced more bands than the other groups. I created the completed chart, and in the same way as History of a Chart 3. “Where Did All the Rockstars Go?”, I imported the chart into Flash and  – over a series of keyframes – removed one “man” at a time. I then reversed the frames to the columns appeared to build.

Evolution

Inspiration:  n/a

Idea: To show the numbers of artists in the charts over time.

Method: I initially drew up a chart simply showing the numbers of bands in the charts, grouped into 1 of 3 categories, “rock”, “pop” and “other” categories. This was to free up the chart from the clutter of the smaller genres that did not significantly impact upon rock and pop.

Why Ditched: The chart clearly shows  a gradual increase in the number of artists over time, explained by artists from earlier years still being active in later years.

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History of a Chart 2. “Rock V The World”

See also:

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(click to see full interactive chart)

A simple chart but effective in allowing the user to track each of the music genres over time, and see them in context. The lower lines are still crowded, but being able to separate them off allows the user to see where they are placed. As rock was the backdrop to the entire study, I made it the backdrop to all of the charts. It allows the user to compare rock against the other values at any point, instead of having to assess 2 lines together.
The chart clearly shows the battle for chart supremacy between rock and pop and the rise of one, as the other falls. We can also see the introduction and rise of hiphop on the charts, and the decline of the classical/orchestral/jazz section since the 70’s.

Idea

The very first chart I created with this data was a line graph that showed ALL of the genres (more in those early stages before I merged some of them together). The idea was effective but the chart was incredibly cluttered.

A problem that emerged time and time again was one of scale. Pop and rock were such HUGE genres, with large data sets, yet the smaller genres, still important, disappeared among other small genres at the base of the chart.

I then decided to brush up on my Flash (something I had wanted to avoid, as I was hoping to create a larger static visualization) and create an interactive chart that allowed the user to select the genre they wanted, and also be able to see them all together in context.

Method

A chart for each genre was created in Tableau (using the same axis and scale to maintain accuracy)

These were then exported into Illustrator (for re-colouring), and into Flash to build into a rollover chart.

Evolution

The chart above was the result of much manipulation and “playing” in Tableau. Here are some of the more interesting developments during that process.

Inspiration: n/a

Idea: This was one of the first charts I created in Tableau with my data set. I wanted to get a simple overview of the charts and judge the best way to show it. The line version of this remains the simplest way to show the chart.

Method: With Year on the X axis, and Measure Value on Y, and colour set to mark GENRE, this plotted out the values of each genre per year.

Why Ditched: This chart has no real value  it is near impossible to distinguish any flow as there is so much data crammed into a small space.   I reverted to the line version.

Inspiration: n/a

Ideato show a definite sense of trend over time

Method: To use the POLYGON setting in Tableau to show the overall trends between the various genres over time.

Why Ditched: I am still unconvinced about the benefits of the POLYGON chart. Whilst you can quickly see the trend, it simply shows a line from the start of the chart to the end, and highlights the above and below points. Whilst this may be useful for a definite data set, this is very much a part-data set. I chose to begin in 1970, but that is in no way the start of music. This chart would look very different were I to all music over a different time period. It does highlight a moment where rock and pop switched over in terms of dominance, but overall I decided it was overly simplistic and better suited to financial static data.

Inspiration: DNA charts (example: DNA chart)

Idea: to use a simple heat map to show the presence, and strength of presence, of each genre over time. 3 shades of colour would be given to each genre – not present (grey for each) then dark and light to show the high and low values.

Method: This  was created with separate charts for each genre, to account for the vastly different scales. So it marked the relative values of each genre separately. I then exported the layers, and placed them together in Illustrator.

Why Ditched: I was pleased with this chart and how it looked (I later have doubts about it’s validity – see next chart) but at this stage I was interested to see it displayed in a circle. I hoped I would be able to widen the data areas to make it less cramped.

Inspiration: Jake Kennedy Hobart – The Rain Project,

Idea: I wanted to use the chart above to create a circular, or semi circular chart. I hoped I would be able to stretch out the size of each unit, so it would appear less cluttered.

Method: Using the table created above (and removing any excess white at each side), I used the Envelope Distort function in Illustrator to bend it into a 100% circle.

Why Ditched: I realized that the original method of shading was giving a false impression of the chart. I was comparing each music genre on its own scale, yet placing them next to each other, giving the impression that they were on the same marked scale.  This only shows that pop and rock were a lot more present in the charts than the others, not by how much. A simpler and more accurate chart would have show simple presence, or no presence – colour and no colour. This lighter colour is deceiving.

Inspiration: n/a

Idea: Despite the issues with the colour on the last chart, I was keen to attempt another circular chart using the same process (ie bending a rectangular chart into a curve). Again, I hoped that chart that formerly suffered for lack of space would benefit from a circular shape.

Method: I created a line chart, showing all of the genres (distinguished by colour) on a black background (it showed the lines up clearer than white). I then concluded that I would have to break the chart into quarters, to enable a full 360deg circle to be created (I later solved this problem). For demonstration purposes I created one 90deg bend, and simply copied it 3 more times, and placed the quarters into a circle.

Why Ditched: I was concerned that, as with the simple line chart, the smaller genres (classical, spoken word etc) were being lost at the centre of the chart and therefore were unreadable – rendering the chart useless.

Inspiration: as above

Idea: as above but I hoped  – by reversing the chart and having the smaller values on the outside, wider part of the circle, they would be clearer

Method: I simply turned the chart upside down before creating the circle shape – hence the larger values were on the inside

Why Ditched: Although this did make the smaller values easier to see, it went against logic to have the larger values at the centre of the chart. Naturally the eye would treat the middle of the circle as the bottom of the line chart, hence reading the values upside down. The chart was not useful in any form .

Inspiration: C. Van Vleck | Information Taking Shape,

Idea: Still interested in pursuing the idea of a circular chart, I decided to solve the problem of concealed and cluttered data, by attempting an interactive rollover chart in Flash. This means that even if the data is hidden, the user can make a selection and see it in isolation as well as in relation to the other values.

Method:  I created a full stacked bar chart, with each colour block showing the percentage of albums each genre represented per year. Exporting this as a PDF into Illustrator I was able to recolour the chart (to help distinguish the smaller genres). I then created 8 versions of the chart, each of them with one colour highlighted and the rest “greyed out”. In Flash I converted  the menu boxes into a series of rollover buttons and each showed a version of the chart with the respective colour highlighted. Roll off, and the whole chart was shown.

Why Ditched: I was essentially happy with this chart. It was a little fuzzy about showing the smaller genres and all in all it was difficult to compare respective values (a design fault of the stacked bar chart and its transformation into a circle). However, the main reason for scrapping this chart was the discovering of a major error in the data that would have required redrawing the chart from scratch at a late stage. I took a judgement call that it was not strong enough a visualization to construct again from scratch.

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