History of a Chart 5. “Guess What?”

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As I began to look into the subgenres of rock music, I was constantly surprised by the genres that were having an impact. I was surprised to see New Wave perform as well as it did, whilst the impact of indie and alternative in the more recent years was also of significant note.
I was looking for a way to recreate the surprise I felt from making these discoveries within a visualization.
I had examined the “reveal” mechanism in “This is the New Flesh” so I was keen to try something else.
I wanted to  challenge the users preconceptions about the data by creating a simple game. The user was asked to make their guesses for the top genres, and simply compare their guesses to the correct answers. Seeing this in action with several users, it is interesting how people are immediately drawn into an internal debate about the genres, and are surprised by the results.

Method

This was the most complicated visualization I developed and took extensive use of Action Script 3.

Unlike the other charts, the majority of this was build within Flash CS5  (the graphic content was developed in Illustrator). In this case there was no chart to export from Tableau.

  1. Plan out the idea on paper (I use paper or Ipad PhatPad). I find this to be the easiest and quickest way to imagine how the chart will look.
  2. Build the individual elements in Illustrator  – creating circles and outlines and deciding on colour schemes (dictated by the red and black theme running throughout the chart when talking about rock as opposed to the other genres).
  3. Import the elements into Flash Cs5
  4. Duplicate the elements to create as many as you need (4 in total)
  5. Convert them all into Button > Movie Clips
  6. Apply  the “Drag and Drop” snippet code to each. This allowed the element to be moved around the screen.
  7. Converting the “Reveal” circle into Movie Clip with timeline navigation qualities (move to next keyframe and stop), I was able to move the movie onto the next keyframe to reveal the results.
  8. Convert answer circles into rollover buttons to show further information about each genre
  9. Insert mini charts into “OVER” setting of button for each genre
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2011
09/07
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History of a Chart 4. “This Is The New Flesh”

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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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2011
09/07
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History of a Chart 3. “Where Did All the Rockstars Go?”

See also:

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(click to see full interactive chart)

Inspiration: McCandless Vintage Years Red/White Wine

When your dad/uncle/big brother bemoans the state of rock today, saying it’s not what it used to be, have you ever thought they MAY have a point?

Chart data shows that most of the top performing rock bands of the past 40 years were active in the 70s’s, with 2 having major success in the 80s (Queen and Meatloaf) and just one in the 90s (Oasis).

This chart shows that artists were not relying on ONE album to give them chart success, but several – all of which were dominating the charts for months at a time. Simon and Garfunkel had FIVE albums in the charts in 1970. You’d be hard pushed to find a band matching that nowadays.

If musical success is built on a steady career and a large body of work, you have  to wonder who will be the Pink Floyd, Dire Straits and Beatles of the future.

Idea

I wanted to look at the distribution of the top rock bands over time and clearly show when they were active and how successful they were.

Method

  1. Tableau: Starting in Tableau, I placed genre on the Y axis and Year on the X axis, with the entries turned to circles, coloured by scale of Weeks in Chart, we were able to make a clearly shaded chart which immediately shows the highs points. It took a while to get the colour scheme and other settings right – (as you can see below).
  2. Export to Illustrator: Using the Print to PDF option I exported the chart to Illustrator, there I recoloured the circles (the original setting had the middle values as grey and low as black (obviously a fiancial setting) but this was unsuitable for this chart so I switched the black and grey over. I also resized the chart and split the circles into separare items so they could be manipulated and removed in Flash.
  3. Animate: To create the animation, I imported the chart into Flash and inserted keyframes at regular intervals and removed a few of the points each keyframe until the chart was blank. I then reversed the order of the frames to they seemed to appear, not disappear, during the movie clip. I then turned the red points into rollover buttons to show more information. (In retrospect, I wonder if these are entirely necessary, and in fact detract from the finished form)

Evolution

Inspiration: n/a

Idea:  To show when the most successful bands of the past 40 years were active using a bar chart.

Method: I created a bar chart showing the numbers of weeks spent in the charts per year, by the top 10 rock artists of the past 40 years. Marking these by colour, I hoped it would clearly show the peaks over time, and when the majority of artists were successful.  I knew that the colours would overlap, but I hoped that using a cyclical colour scheme would allow the user to get a general idea of timescale.

Why Ditched: Whilst the chart gave a good general overview of  the shape of success over time (the majority of the artists having success in the 70s) it was hard to see the individual artists amounts. The cyclical colour scheme was not enough to give an idea of timescale.

Inspiration: catalogtree 4.0

Idea:  I still wanted to show prominence over time, but switched from artist to album – focussing on the top 20 rock albums over the 40 year period.

I hoped this would be a more engaging chart for the user, who would look for their favourite album and connect with the chart.  By placing them on the Xaxis, in release order, I hoped it would be easier to navigate.

Method:  By listing the albums  on the Y axis and time on the X, I wanted to use differently sized circles to signify chart prominence. As the albums were sorted into release date we get a clear pattern of impact, and i some cases, the “tail”, (i.e. how long the album remained in the charts after release date).

Why Ditched: I felt the “album” idea, although engaging and in a way more emotional for the reader than “artist”, there was no overall message. Yes, it showed the top albums, but would not show artist presence, for example, if an artist appeared twice, etc. This would work as a supplementary chart to one dealing with artist, but not alone. I was also concerned that relying on size of circle, not colour, did not immediately show when the albums were prominent.

Inspiration: N/A

Method: Returning to the idea of artist, I decided to look at all artists, not just rock bands. Finding the top 10 artists and placing them in “overall success” order as opposed to release date, we immediately lose the pleasing pattern, but we can see when the larger bands were successful.I decided to introduce colour to the circles to represent value alongside circle size. We can immediately see where the larger values are found, and which artists they belonged to.

Why Ditched: There was no distinction between POP and ROCK artists, which was the point of the project. With colour representing Value, it would have been difficult to use this distinguish between the different genres. Also, sorting them into overall value was of little interest to the chart, and made it appear cluttered. I also doubted the need for size to represent value, when colour was the more effective indicator.

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2011
09/07
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History of a Chart 2. “Rock V The World”

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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

Idea: to 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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2011
09/06
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History of a Chart 1. “Good Times, Bad Times”

See also:

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Inspiration: WorldOfViolence,  Globalize me! : JUNG + WENIG , Nicholas Felton, es / Books / Personal
Kurt Kranz Urs Hofer , Flags By Colours 

(click to view full interactive chart)

The critics may claim that rock is dead, but there could be life in the electric guitar yet.

We are undeniably in a rock slump, with rock albums performing at their worst for 10 years. However, we saw similar poor showings in the 80s and 90s, and  rock always fought back.

The popularity of prog and folk in the early 1970’s saw rock dominate around 60% of the album charts, but by 1978 disco had forced that down to 43%. However, by the early 80s rock was back on top as the New Wave movement took hold, then to be hit once again by the commercial pop explosion and then, a double drop when house music took hold.

The pattern continues in this way, through the rise of Britpop and the modern successes of Green Day, The Killers and British indie rock bands such as Kaiser Chiefs, with rock always fighting back from a slump with a sudden rise in interest.

With 2010 seeing the worst performance for rock albums in the charts for a decade, are we in one of those slumps now, and is there a new rock craze waiting to revive the genre and take it back to chart glory?

Idea

I had been working through various versions of this chart, using rollover panels to show various sets of information for each year as well as the values for other genres. I decided to split this information into 2 separate charts (see History of a Chart 2. “Rock V The World”) for simplicity.

I wanted to show the highs and lows of the rock scene over the past 40 years, with some specific information – e.g. top selling artists, % of charts as rock, etc. I felt this would be an engaging chart for the user and would hold attention. (Ideally every year would be interactive, not just the highs and lows, but time restricted this).

Method

  1. Within Tableau Desktop I create the basic bar chart (with genre filtered to just rock), with Numbers of Records on the Y axis, and Year on X.

I then put imagined myself in the shoes of the user. What extra information would I like to see on the chart?

I decided to illustrate the most successful artists of each year, the % of rock in charts and a circular date chart showing when rock was at number 1 in the album charts.

The % of chart as rock was created using the Pie chart setting, with colour set to genre (with All genres except rock grouped and coloured as black, and rock set as red), and Angle was Measure Value. With The X axis as Year, this created one pie chart for every year.

To edit, re-colour and manipulate the charts, I selected “Print to PDF”, and opened the PDF in Illustrator, and then in Flash to create the rollover buttons/animation.

Evolution

Below I talk through some of the stages and decisions I made.

Inspiration: The STEM Dilemma,

Idea: Was to create an all encompassing chart for both different genre lines and rock artists. I was also drawn to the idea of the barchart as an industrial skyline, so wanted to create the idea of Smoke emerging from them.

Method: (see History of a Chart 2. for how I created the rollover line chart).

I sourced the top 5 artists per year by using Tableau to filter, calculate and sort the information. The black circles were created in Illustrator, using a simple process – each value had a corresponding, and very simple, size. So, 140 units = 140pixels (sq) in size. I would apply this to all circles, and the key, then resize ALL as necessary to fit the chart. The relation stays the same and the key still works.

Why Ditched: Overly complicated. Errors in data. Style over usability.

Inspiration: McCandless “Media Jungle”

The Idea: A static chart that showed easily the major events and interests in Pop music that kept rock out of the spotlight over time.

The Method: Using Wikipedia and other websites to research this, I placed the major events on “flagpoles” emerging from the barchart. These showed showing key albums, deaths, events to affect music.

Inspiration: music-family-tree,

Idea: To create a rollover chart showing the various key moments in music. The black area would show the rock highlights, the white, non-rock.

Method: Adding to the data I researched for the above chart, I then created a series of rollover buttons (in Flash CS5) from the YEAR tab, and for the “over” function, showed the information.

Why Ditched: Too cluttered and unclear. Hard to distinguish between Rock and Non-Rock. Space restricted amount of data so each year looked sparse until ALL option was displayed. Users asked if the placement on Y axis was relevant. It wasn’t but the axis suggested it may be.  The text data was also a little vague. I decided to drop the text and switch to numerical data and charts instead.

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2011
09/06
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Update, link and thanks

I’ve been incredibly quiet on this blog for the last month or so as I’ve been immersed in the world of visualization. It was always going to be my favourite part of the assignment, but that is not to say it’s been easy going.

I use the Tableau software to create the basic charts, and then  manipulate them in Illustrator and then Flash, for the animations.

I find it difficult to talk about HOW I visualize, its a very organic process with plenty of chopping and changing of settings to allow the data to “talk”. I will go through this at some point, but for now – here’s the link to the finished pieces.

Thank you to everyone who has helped out so far with advice, or suggestions. It is much appreciated.

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2011
08/31
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research
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Starting the next stage: Visualization

Intro

I’ve been spending the past 200 hours (over a series of months) gathering and cleaning up my data set as part of my final project for an MA in Online Journalism.

This has included:

  • deciding on the best data set to use
  • finding a source
  • scraping that data
  • developing my basic skills of Scraperwiki,  Yahoo Pipes, Outwit Hub
  • Cleaning up the data with a combination of Outwit Hub, Excel, Word and notepad (for stripping and replacing)
  • Checking and double checking the data for errors
  • Pivoting the data and reducing it into a usable form (converting a Top 40 list into a single line of Genre counts her chart)
So now I have reduced my 85000 lines into more like 2,000 – a lot easier to use.
I am now at the stage where I can begin to think about the visualization.
With previous projects I have used ManyEyes and Tableau (my favourite) and used the ability to change setting quickly to PLAY with the options, and try a huge amount of different charts.
As I am working within the bounds of a project, called Is Rock Dead?, I must not forget some of the main facets of the project (initially set out in my MA Proposal Document pdf)MA Online Journalism Proposal Rock is Dead-3  (NOTE: My tutor Paul Bradshaw advised that I focus on ONE element of this to avoid “mission creep”.)
So I will focus on the larger GENRE chart first and take it from there!
  • to answer the question – Is Rock Dead? Is it on its last legs?
  • Does music genre go in cycles – radio/music professionals claim rock, pop and dance/electro go in cycles over time – is this true? What are those cycles?
  • What is powering the rock genre in the charts? What is the future looking like for rock?
If I have time I would also like to produce some extra visualizations showing the breakdown of the genre in the charts,  the hot genres, the dead ones and perhaps WHY some of them peak at other times.
—
In order to show the pattern of genre over time, I need to produce  a version of David McCandless’ Mountains Out Of Molehills Interactive  – do I simply copy this, or produce a version of it?
I must confess, I’m not a HUGE fan of 3D charts – I think anything that is asking the eye to compare to values, should not place them on a 3rd axis …

The chart wins in the fact that NONE of the values are obscured, but it’s hard to compare them

Whilst I think this chart is very interesting, I am not sure it’s EXACTLY what I am after.

Over the next few days I will be using various visualization tools to see which are the most effective – watch out for a blog post on these at some point
I am now experimenting with various chart shapes and designs  – you can check them on Flickr out there – Id love to get your feedback on what works, what doesn’t etc!
2011
08/08
CATEGORY
research
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Square pegs, round holes and a mighty big hammer – genre defining

When I started this project I was determined to filter the dozens and dozens of sub genres of music onto a few (fewer than 10) master genres. I knew this would be difficult, but I was convinced that – with some hard work, tough decisions and an emotional detachment I would get there in the end.

Why so few master genres?

My eventual aim is to create an all encompassing visualisation of the entire time scale of my project – 40 years) and any more genres than that would make the visualisation cluttered and useless. Plus many of smaller genres would simply disappear in the larger image.

However, am I removing vital elements of the visualisation if I put them in a master category?

It’s a tough one – I developed, fairly early on, a definitive list of genres – although I knew these would bend and shift.

  • pop
  • rock
  • classical / orchestral / performance / theatre
  • easy listening
  • entertainment (incl. spoken word, comedy, childrens, fitness album etc)
  • soundtrack
  • dance
  • electronic
I know this poses a ton of questions
  • Should Dance and Electronic be merged? they have a similar sound and use of instruments
  • Do I have a soundtracks category out of pure laziness? Should I not go through each of them and assign a proper genre? And if not, should there be a COMPILATION soundtrack (a category I have now merged into pop)
  • Where does Jazz go? and Reggae? What about SOUL?
  • Am I removing a key category by putting RnB into pop?
  • Easy listening – I developed this for the POPULAR music that does not belong in POP – Val Doonican etc. However, am I simply moving it out of POP because it is “old”? Also, am I just putting what I consider to be the “dull stuff” in there?

However, the biggest question is – do I need a pop category at all?

The focus of my project is ROCK – so there has to be a rock category – but does POP = ROCK in terms of a category size?

I wanted my final categories to be as equal as possible – not in size but in classification terms. If I was going to put FOLK under ROCK, then should I put RnB under POP?

Any help, advice or thoughts much appreciated …

2011
08/02
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40 years of charts, by genre, in a Wordle

It needs tidying and some reclassifying … but it’s an interesting sight! (click through to a larger version)

2011
07/08
CATEGORY
Charts
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Further Adventures in Google Refine: trials and tribulations

I’ve had a bit of a game with Google Refine recently.
Following on from the success I talked about in my last post (Adventures in … Google Refine Pt 1) things went decidely downhill
Refine was often freezing, glitching and I was losing all my data and wasting hours of work.
However, after some very helpful messages on the Google Refine Group I was able to install an updated version of Refine, and deal with the data in a more manageable way.

It appears, despite being told that Refine would be able to handle 85,000 lines of data – that breaking it up into sections of 5000 rows is wiser.

—

The process is now as follows: ( am currently at stages 6/7/8 so bear with me)

  1. start with 2 columns – Artist and Album
  2. Using FACET,  row.index / 5000 I split the columns into 5000 line sections – easier to manage = less likely to crash/freeze
  3. For each 5000 line facet, reconcile the artist column using FREEBASE (do not attempt to fix the failed matches by using DBPedia)
  4. Manually work through the unmatched options with the suggestions from Freebase
  5. For items still unmatched, decide – researching if necessary – WHICH musical genre that album/artist belongs in. e.g. for the Now That’s What I Call Music – I flagged it as POP VARIOUS (this may eventually drop into a POP category, but I can decide that at a later time)
  6. Working within the 5000 line facets, CREATE A COLUMN  FROM FREEBASE based on the Artist.
  7. Within the Musical Genre tag, constrain to 1  – I don’t want a list of MANY genres, I want just the first one (is this risky??) 
  8. Each time I do this, it creates a NEW column, so I then  TRANSPOSE that it into the current GENRE column using  cells[“Musical Genres2”].value
  9. We are still left with blanks for all the artists that we set to a GENRE in Stage 5.
  10. Using, FACET BLANK we can copy all the data from ARTIST into genre by using a modification of the TRANSFORM comment above   cells[“Artist”].value
  11. Repeat through all the facets, and tadaaaaa – 3 columns, Album, Artist and Genre
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2011
07/06
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