Lego Architecture – White House (21006) Review

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Lego Architecture – White House (21006): Well with the presidential campaign very underway by now – it seems like candidates will say and do anything to covet that above building. While I do sort of wish this came with the massive yard and fence from the real building – it is actually a good set.

 

Time to Knoll: 30 Minutes

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View post on imgur.com

Time to Build: 55.5 Minutes

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View post on imgur.com

 

Metrics:

  • Pieces: 561 and 54 Steps – Manual
  • Price: $49.99 on Lego and $45.83 on Amazon
  • Weight 436 grams
  • Combo Points: (6X28X1X1) = 168 points
  • Volume (Based on Blob length/width/height): 48mm x 128mm x 112.0mm or 688.1 cm³ with a little more on top to be 721.7 cm³

21006_blob

 

Scores:

  • Uniqueness: 4 out of 5 Stars
  • Aesthetics: 4 out of 5 Stars
  • Fun to Build: 2 out of 5 Stars
  • Hoarding: 3 out of 5 Stars

 

What Else?

You may have noticed reviews having page numbers, but it’s time once again to announce another feature that will be in all future TopBrick reviews (and past ones by next week.) As evidenced by keeping XL spreadsheets for inane things, and the weird metrics on this site – it should be no surprise I have a love of data and visualizing it. To that end I’ve developed an interactive chart that will actually pull data from a set’s pieces and show you the colors and pieces in a beautiful way. Behold:

To explain a bit what’s going on here:

  • I am getting the CSV data from Brickset
  • I then build a D3 chart that creates a hierarchy by color and part
  • The part itself has an image and count shown via a tooltip
  • I also use the Levenshtein algorithm to test the string from the CSV against the color data from Lego. To understand what this is doing imagine the following example. Say the data I am provided says Md. Stone Grey. Now as a human we know that’s Medium, but how does the computer?
    • Quite simply we use the Levenshtein algorithm which in layman’s terms assigns a score to insertions/deletions/replacements in order to determine how alike one set of text is from another.
    • So say we are matching Md. Stone Grey to Medium Stone Grey, and Light Stone Grey. In this instance we would need to add 5 characters to Md. in order to match both (eium, and light); however to make the text match fully we need to remove characters as well.
    • Since to match light we need to remove all of Md. we get an additional score of 3; however for Medium while we had 5 adds, we only need to remove the period to match since we can insert the additional character (theoretically) at any position.
    • So what happens is because Md. is closer to Medium than it is closer to Light we correctly get the right information.

 

Remix: So for the remix this week I decided to make usage of the stark contrast of colors here. (While the green makes the field, and there is a bit of gray or brown) this comes into a black v. white. I therefore decided to make two towers – light versus dark. Good versus evil.

21006_remix

 

Final Thoughts: Overall I have to wonder why people care so much about such a ‘okay’ looking building. (It is admittedly the power it represents) I normally talk about how I enjoy a set that is the perfect size, but for some reason (maybe it’s the patriotism) I feel like this should be a much larger set. One where we can see an interior, see the Lincoln bedroom, the Oval Office, etc.

Final Score: 3 out of 5 Stars

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