You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 beer_factory
【Schema】
# Table: rootbeer
[
(RootBeerID:INTEGER, Primary Key, Examples: [100000, 100001, 100002]),
(BrandID:INTEGER, Examples: [10001, 10002, 10003]),
(ContainerType:TEXT, Examples: [Bottle, Can]),
(LocationID:INTEGER, Examples: [1, 2]),
(PurchaseDate:DATE, Examples: [2015-07-03])
]
# Table: location
[
(LocationID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(LocationName:TEXT, Examples: [LOST]),
(StreetAddress:TEXT, Examples: [6000 J St]),
(City:TEXT, Examples: [Sacramento]),
(State:TEXT, Examples: [CA]),
(ZipCode:INTEGER, Examples: [95819])
]
# Table: transaction
[
(TransactionID:INTEGER, Primary Key, Examples: [100000, 100001, 100002]),
(CreditCardNumber:INTEGER, Examples: [6011583832864739, 4716634257568793, 5597608517846968]),
(CustomerID:INTEGER, Examples: [864896, 610766, 207846]),
(TransactionDate:DATE, Examples: [2014-07-07]),
(CreditCardType:TEXT, Examples: [Discover, Visa, MasterCard]),
(LocationID:INTEGER, Examples: [2, 1]),
(RootBeerID:INTEGER, Examples: [105661, 105798, 102514]),
(PurchasePrice:REAL, Examples: [3.0, 1.0])
]
# Table: geolocation
[
(LocationID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(Latitude:REAL, Examples: [0.0, 38.566129, 38.559615]),
(Longitude:REAL, Examples: [0.0, -121.426432, -121.42243])
]
# Table: customers
[
(CustomerID:INTEGER, Primary Key, Examples: [101811, 103508, 104939]),
(First:TEXT, Examples: [Kenneth, Madeleine, Damen]),
(Last:TEXT, Examples: [Walton, Jones, Wheeler]),
(StreetAddress:TEXT, Examples: [6715 Commonwealth Dr, 3603 Leola Way, 6740 Branwood Way]),
(City:TEXT, Examples: [Sacramento, Orangevale, Folsom]),
(State:TEXT, Examples: [CA]),
(ZipCode:INTEGER, Examples: [94256, 94258, 95662]),
(Email:TEXT),
(PhoneNumber:TEXT, Examples: [(916) 918-1561, (916) 186-9423, (916) 164-1156]),
(FirstPurchaseDate:DATE, Examples: [2013-05-30]),
(SubscribedToEmailList:TEXT, Examples: [FALSE, TRUE]),
(Gender:TEXT, Examples: [M, F])
]
# Table: rootbeerreview
[
(CustomerID:INTEGER, Primary Key, Examples: [101811, 105549, 105771]),
(BrandID:INTEGER, Primary Key, Examples: [10012, 10014, 10015]),
(StarRating:INTEGER, Examples: [5, 1, 3]),
(ReviewDate:DATE, Examples: [2013-07-15]),
(Review:TEXT)
]
# Table: rootbeerbrand
[
(BrandID:INTEGER, Primary Key, Examples: [10001, 10002, 10003]),
(BrandName:TEXT, Examples: [A&W, A.J. Stephans, Abita]),
(FirstBrewedYear:INTEGER, Examples: [1919, 1926, 1986]),
(BreweryName:TEXT, Examples: [Dr Pepper Snapple Group]),
(City:TEXT, Examples: [Lodi, Fall River, Covington]),
(State:TEXT, Examples: [CA, MA, LA]),
(Country:TEXT, Examples: [United States, Australia]),
(Description:TEXT),
(CaneSugar:TEXT, Examples: [FALSE, TRUE]),
(CornSyrup:TEXT, Examples: [TRUE, FALSE]),
(Honey:TEXT, Examples: [FALSE, TRUE]),
(ArtificialSweetener:TEXT, Examples: [FALSE, TRUE]),
(Caffeinated:TEXT, Examples: [FALSE, TRUE]),
(Alcoholic:TEXT, Examples: [FALSE]),
(AvailableInCans:TEXT, Examples: [TRUE, FALSE]),
(AvailableInBottles:TEXT, Examples: [FALSE, TRUE]),
(AvailableInKegs:TEXT, Examples: [FALSE, TRUE]),
(Website:TEXT),
(FacebookPage:TEXT),
(Twitter:TEXT),
(WholesaleCost:REAL, Examples: [0.42, 0.98, 1.13]),
(CurrentRetailPrice:REAL, Examples: [1.0, 3.0, 44.0])
]
【Foreign keys】
rootbeer.LocationID=geolocation.LocationID
rootbeer.LocationID=location.LocationID
rootbeer.BrandID=rootbeerbrand.BrandID
location.LocationID=geolocation.LocationID
transaction.CustomerID=customers.CustomerID
transaction.LocationID=location.LocationID
transaction.RootBeerID=rootbeer.RootBeerID
geolocation.LocationID=location.LocationID
rootbeerreview.CustomerID=customers.CustomerID
rootbeerreview.BrandID=rootbeerbrand.BrandID

    【Question】
    List the brands of root beer produced by Dr Pepper Snapple Group and calculate their percentage of purchases between 2014 to 2016. brand of root beer refers to BrandName; produced by Dr Pepper Snapple Group refers to BreweryName = 'Dr Pepper Snapple Group'; percentage of purchases = MULTIPLY(DIVIDE(SUM(BrandID WHERE PurchaseDate > = '2014-01-01' AND PurchaseDate < = '2016-12-31'), COUNT(BrandID) WHERE BreweryName = 'Dr Pepper Snapple Group'), 1.0); between 2014 to 2016 refers to PurchaseDate > = '2014-01-01' AND PurchaseDate < = '2016-12-31;

    【Evidence】
    brand of root beer refers to BrandName; produced by Dr Pepper Snapple Group refers to BreweryName = 'Dr Pepper Snapple Group'; percentage of purchases = MULTIPLY(DIVIDE(SUM(BrandID WHERE PurchaseDate > = '2014-01-01' AND PurchaseDate < = '2016-12-31'), COUNT(BrandID) WHERE BreweryName = 'Dr Pepper Snapple Group'), 1.0); between 2014 to 2016 refers to PurchaseDate > = '2014-01-01' AND PurchaseDate < = '2016-12-31;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T1.BrandName , CAST(SUM(CASE WHEN T2.PurchaseDate >= '2014-01-01' AND T2.PurchaseDate <= '2016-12-31' THEN 1 ELSE 0 END) AS REAL) / COUNT(T2.BrandID) AS purchase FROM rootbeerbrand AS T1 INNER JOIN rootbeer AS T2 ON T1.BrandID = T2.BrandID WHERE T1.BreweryName = 'Dr Pepper Snapple Group' GROUP BY T2.BrandID