Here is a bunch of vintage streetwear pieces to kind of capture that throwback look/style. These are all pieces that were either from earlier eras or current clothing pieces that I thought had a retro look to them. There is a couple outfits that are layered, which can be geared towards the more cool seasons. Each shoe that I wore was a classic design by Vans and Reebok. I also styled the outfits with some jewelry here and there. I wanted to give you guys an idea of some streetwear to go to when styling the vintage look. Featured Brands: Urban Outfitters, Guess, vans, Zara, Tommy Hilfiger, Nike, Reebok, Levi, Pacsun, Forever 21 and Ralph Lauren.
Make sure you HIT THE THUMBS UP & SUBSCRIBE!
UO Plaid Pants
Forever 21 Denim
Vans old skool
Reebok Club C sneakers
Levi 510 Denim
Guess Jeans Dad hat
Iron Maiden tee
Zara Denim Jacket
Nike Techfleece Joggers
Guy I discover your channel right now. I edit my first lookbook, my vintage lookbook. I wanted to see the others video with this same theme and yours is sooooooo dooooopeeeeee mannnnn ! XOXO from Paris. See ya !!!!
This article has been motivated by a response I gave to a problem raised on an Oracle developer forum. Our requirement is to produce a report that details customer spending for each month of the year. Our database only records actual spend, so for any given month, data for dormant or idle customers will have to be generated.
First, well create a mock CUSTOMER_ORDERS table with sparse data to represent customer spending. To keep the example simple, well denormalise the customer name onto the orders table.
a sparse report.
With our customer orders data as sparse as it is, a monthly report for purchases by customer would look as follows.
adding the missing months.
We can see from the data that we are missing most months of the year for our two customers. Remember that our requirement is to show a report for every month in 2004 for every customer. First we will build a "time dimension" set (using subquery factoring) and outer join it to our orders table.
We can see that this hasnt quite worked. We have the zero sums and the year-months, but we are missing customer names. This is because we outer joined to CUSTOMER_ORDERS on the year-months, so any customer columns would show as NULL for deficient rows. Until PARTITION OUTER JOIN appeared in Oracle 10g, we couldnt "invent" data easily , though the next section shows that it is possible in prior versions.
data-densification without partition outer join.