Annotation station: The Value of an annotated line graph

I really enjoyed the slopegraph challenge from Storytelling with Data, that I decided to tackle the first challenge Cole of SWD issued--the annotated line graph. You can read about the annotated line graph challenge here.

I made up some data to visualize...this time it was sales data for a magical widget.  

Then it was time to visualize.  First was the line graph, since that was the basis of this challenge.  

There are so many formatting and annotation opportunities here.  When first looking at the visualization, a few things came to mind.

• There is an awful lot of white space below the line.  It feels like I haven't efficiently used space.
• I would really love to see what 2018 sales are forecasted to be. 
• I think this graph would be better with the ends of the lines labeled.  

So with those thoughts in mind, I went to iterating. 

Annotation and Format Changes

1. Title change.  Now the reader knows that I'm going to be providing information on the impact of the pricing model on sales. 
2. Annotated relevant points and areas on the line.  To start, I labeled the line ends. I also called out the pricing change (what it was and when it happened).  I also thought it was helpful to label the high point in sales, though if one annotation had to be removed, I think it would be this one.  In this particular case, I'd let my reader give me feedback in the vetting stage on this point. 
3. Noted the forecast range.  As I was reading this visualization, I wondered what the range was.  Instead of making my reader try to figure it out, I added the minimum and maximum.  
4. Removed the Y-axis.  Because I had relevant points labeled, the Y-axis labels became unnecessary. 
5. Truncated the Y-axis by a little.   There was a lot of white space below the line and even with annotations, there still seemed to be a lot.  I tried multiple iterations from taking the axis from 0 to starting at 25,000,000. While that removed the extra white space, it also made the forecast seem like was half of the chart--and that's not the case.  In the end, I started the axis at 10,000,000 to cut a little extra space, but not so much that it skewed how I viewed the forecast. 

The resulting visualization follows.