Working With API Wallet Data

Overview

The audience of this post is a person that has a database table that is populated from the /char/WalletTransactions.xml.aspx API and wishes to use queries to produce meaningful, intelligent results that can be used to help focus trading operations.

Even with limited database query knowledge, we can derive meaningful Business Intelligence out of our dataset. Basic MySQL/SQL knowledge is recommended as values or parts of an example query may need to be modified to suit your environment or table structure.

I won’t cover the design on how to get API data into your database table here as I want to save that topic for its own post. If you need an answer to populating your database from the API, search the Eve Forums as there are a many projects that can help.

Prerequisite

Wallets from multiple characters are stored into a database table.

phpMyAdmin or SQL Server Management Studio for running and manipulating queries.

Business Intelligence from Numbers

Knowing that a Drake sold for 1.1 M profit one time doesn’t tell you much in the larger scheme of your business as we need to extract more intelligence out of our numbers. Getting further metrics out of the wallet data can help focus your operation and deliver better results.

Consider these starter questions: How fast have Drakes been selling (item velocity)? Are the the monthly profit from Drakes worth your time or should you be working with another item? Is working with Tech1 Battlecruisers proving profitable?

These are examples of the types of questions that you can answer with a few database queries and some spreadsheet analysis. The more robust developer will build these queries into a reporting application, but for the purpose of this post, I will stick to running a query and working with the output.

Table Structure

I have added a few unique columns to my table to help me filter my data. Here is my ‘wallet’ table structure for reference.

– Table structure for table `wallet`
CREATE TABLE IF NOT EXISTS `wallet` (
`transactionDateTime` datetime NOT NULL,
`transactionID` bigint(20) unsigned NOT NULL,
`quantity` bigint(20) unsigned NOT NULL,
`typeName` varchar(255) CHARACTER SET latin1 NOT NULL,
`typeID` int(11) NOT NULL,
`price` double unsigned NOT NULL,
`clientID` bigint(20) unsigned NOT NULL,
`clientName` varchar(255) CHARACTER SET latin1 NOT NULL,
`characterID` int(11) NOT NULL,
`stationID` bigint(20) unsigned NOT NULL,
`stationName` varchar(255) CHARACTER SET latin1 NOT NULL,
`transactionType` varchar(4) CHARACTER SET latin1 NOT NULL,
`personal` tinyint(1) NOT NULL DEFAULT ’0′,
`profit` double NOT NULL DEFAULT ’0′,
PRIMARY KEY (`transactionID`),
KEY `characterID` (`characterID`),
KEY `transactionDateTime` (`transactionDateTime`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

characterID, personal, and profit are unique columns that I use to help track items for reporting purposes.

• characterID – I have multiple character wallets writting to this table so I have a ID for each one stored in a characters table.
• personal – this is a 0/1 flag that I use to note if an item in the wallet is for personal use. Examples are fuel for jumping capitals or ammo for PVP adventures.
• profit – calculated profit of the item when sold minus fees.

Examples

– Total Profit per Item
SELECT typeName, typeID, SUM(profit)
FROM wallet
AND personal = 0
GROUP BY typeID
ORDER BY SUM(profit) DESC

– Price and Profit sums per Month in 2012
SELECT MONTH(transactionDateTime) AS calMonth, SUM(price) AS price, SUM(profit) AS profit
FROM wallet
WHERE transactionDateTime LIKE ’2012-%’
AND personal = 0
GROUP BY MONTH(transactionDateTime)

– Total Profit and Sales per day
SELECT DATE(transactionDateTime) as date1, SUM(profit) as totalProfit, SUM(price) as totalPrice
FROM wallet
AND personal = 0
GROUP BY date1
ORDER BY date1

– Average Margin and Total Quantity per Meta Group over the past 365 days
SELECT invMetaTypes.metaGroupID, invMetaGroups.metaGroupName, AVG((profit / (price * quantity))) * 100 as averageMargin, SUM(quantity) AS quantity
FROM wallet
JOIN invMetaTypes ON (wallet.typeID = invMetaTypes.typeID)
JOIN invMetaGroups ON (invMetaTypes.metaGroupID = invMetaGroups.metaGroupID)
WHERE transactionDateTime > DATE_SUB(CURDATE(),INTERVAL 360 DAY)
AND transactionType = “sell”
GROUP BY invMetaTypes.metaGroupID
ORDER BY metaGroupID

–Market Groups
SELECT wallet.typeID, wallet.typeName, SUM(profit) as totalProfit, SUM(quantity), SUM(price), b.marketGroupID, a.marketGroupName, b.marketGroupName as parentName1, c.marketGroupName as parentName2, d.marketGroupName as parentName3
FROM wallet
JOIN (invTypes, invMarketGroups as a, invMarketGroups as b, invMarketGroups as c, invMarketGroups as d)
ON (wallet.typeID = invTypes.typeID
AND invTypes.marketGroupID = a.marketGroupID
AND a.parentGroupID = b.marketGroupID
AND b.parentGroupID = c.marketGroupID
AND c.parentGroupID = d.marketGroupID)
AND personal = 0
AND d.marketGroupID = 11
GROUP BY wallet.typeID
ORDER BY totalProfit DESC

Flex Your Database Muscle

These examples should serve as a branching off point as you will want to tailor them to your operation. You may want to replace SUM with AVG or COUNT, modify the date range to take a look at a specific trading period, or hopefully roll these types of queries into a reporting engine to really drive your business intelligence.