When using markets/{region_id}/history/ ESI I’m slightly confused on what the actual key: values are (i’m using python). Is order_count the total orders sold or just total orders placed AND sold? I’m trying to get a total number of items sold actually and not sure how to do it. I’m pretty sure that ‘volume’ is the total items on the market so I should have that covered. I’m also trying to figure out how to do a 7 day history in python (I’m doing this as a python learning experience) using today -7 days if anyone wants to comment on that.
If I remember correctly, order_count is the number of trades for the day (i.e. orders filled) and volume is the number of items which were bought or sold (which seems to be what you’re looking for).
@salacious_necrosis Thanks for answering, but isn’t “orders filled” and “bought” and “sold” all the same from the view of a seller?
Not sure what you mean, but here’s an example of what I mean:
Suppose there is a sell order listed on the market for 1000 Tritanium at 10 ISK.
Suppose a buyer comes along and buys 500 Tritanium by selecting the existing sell order. What actually happens is that EVE creates and posts a buy order for 500 Tritanium at 10 ISK which instantly matches the sell order.
After this transaction:
order_count = 1 (the buyer’s order which completed)
volume = 500
Now another buyer comes along and buys the next 500 Tritanium. Another buy order is posted and fully consumes the seller’s order.
After this transaction:
order_count = 2 (possibly 3 since sell order now completely filled, not clear from scant CCP docs)
volume = 1000
Hope that clears things up.
@salacious_necrosis Ah, THANK YOU for clearing that up! I’ve been seeing this all wrong. Well, thats going to change my python coding some. You’re awesome!
So is there a way to get total volume on the market per day?
For a given market type, the “volume” field of the ESI history result is the total volume for a given day. If you sum that across all market types, you can compute the total volume for all items for a given day.
You may find it useful to compare your computations with the data on this site. For example, you can compute a 30 day average and see if it agrees with the data published on A4E site. That would give you some validation that you’re on the right track.
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