Importing market data into Excel: Difference between revisions

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=== Understanding imported data ===

We have at column A of the spreadsheet the "API Version" and at the column B we have the "Method", both columns can be ignored. At column C we have the "typeid", at D "buy volume", that represents the total volume of buy orders at the broker, at column E "buy average price", that means that if you want to supply all market demand for the typeid you will receive at the end of the transactions ISK equivalent to column D multiplied by column E, column F is the "maximum price offer of the buy orders", column G is the "minimun price offer of the buy orders", column H is the "standard deviation of buy orders", that is a measure of dispertion of the data around the buy average price, column I is the "median buy prices", that means if you want to supply 50% of the demand selling for the best buy orders you will receive payments between the median and maximun price offer of the buy orders per unit of item sold. At column J we have "percentile of buy orders", this percentile reffers to 95th percentile, that means that if you want to supply 5% of market demand you will receive payments between percentile of buy orders and maximum buy orders prices, in our example we can see at ~~Figure~~ 2, that the 95th percentile is the same value of maximum buy orders prices. To understande percentile better I suggest to read [https://en.wikipedia.org/wiki/Percentile Percentile]

We have at column A of the spreadsheet the "API Version" and at the column B we have the "Method", both columns can be ignored. At column C we have the "typeid", at D "buy volume", that represents the total volume of buy orders at the broker, at column E "buy average price", that means that if you want to supply all market demand for the typeid you will receive at the end of the transactions ISK equivalent to column D multiplied by column E, column F is the "maximum price offer of the buy orders", column G is the "minimun price offer of the buy orders", column H is the "standard deviation of buy orders", that is a measure of dispertion of the data around the buy average price, column I is the "median buy prices", that means if you want to supply 50% of the demand selling for the best buy orders you will receive payments between the median and maximun price offer of the buy orders per unit of item sold. At column J we have "percentile of buy orders", this percentile reffers to 95th percentile, that means that if you want to supply 5% of market demand you will receive payments between percentile of buy orders and maximum buy orders prices, in our example we can see at Image 2, that the 95th percentile is the same value of maximum buy orders prices. To understande percentile better I suggest to read [https://en.wikipedia.org/wiki/Percentile Percentile]

Columns K to Q are information about sell orders, respectively: Volume, average,

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 === Understanding imported data ===
-We have at column A of the spreadsheet the "API Version" and at the column B we have the "Method", both columns  can be ignored. At column C we have the "typeid", at D "buy volume", that represents the total volume of buy orders at the broker, at column E "buy average price", that means that if you want to supply all market demand for the typeid you will receive at the end of the transactions ISK equivalent to column D multiplied by column E, column F is the "maximum price offer of the buy orders", column G is the "minimun price offer of the buy orders", column H is the "standard deviation of buy orders", that is a measure of dispertion of the data around the buy average price, column I is the "median buy prices", that means if you want to supply 50% of the demand selling for the best buy orders you will receive payments between the median and maximun price offer of the buy orders per unit of item sold. At column J we have "percentile of buy orders", this percentile reffers to 95th percentile, that means that if you want to supply 5% of market demand you will receive payments between percentile of buy orders and maximum buy orders prices, in our example we can see at Figure 2, that the 95th percentile is the same value of maximum buy orders prices. To understande percentile better I suggest to read [https://en.wikipedia.org/wiki/Percentile Percentile]
+We have at column A of the spreadsheet the "API Version" and at the column B we have the "Method", both columns  can be ignored. At column C we have the "typeid", at D "buy volume", that represents the total volume of buy orders at the broker, at column E "buy average price", that means that if you want to supply all market demand for the typeid you will receive at the end of the transactions ISK equivalent to column D multiplied by column E, column F is the "maximum price offer of the buy orders", column G is the "minimun price offer of the buy orders", column H is the "standard deviation of buy orders", that is a measure of dispertion of the data around the buy average price, column I is the "median buy prices", that means if you want to supply 50% of the demand selling for the best buy orders you will receive payments between the median and maximun price offer of the buy orders per unit of item sold. At column J we have "percentile of buy orders", this percentile reffers to 95th percentile, that means that if you want to supply 5% of market demand you will receive payments between percentile of buy orders and maximum buy orders prices, in our example we can see at Image 2, that the 95th percentile is the same value of maximum buy orders prices. To understande percentile better I suggest to read [https://en.wikipedia.org/wiki/Percentile Percentile]
 Columns K to Q are information about sell orders, respectively: Volume, average,