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eatDB (educational assessment tools: Data Bases) enables the use of
relational data bases via a pure R interface. It uses
SQLlite3 as a back end and makes use of the packages
DBI and RSQLite. When a relational data base
with multiple data tables is created via createDB, the user
specifies the order in which the data tables are merged when data is
later extracted from the data base. The fkList specifies
which data table references to which other data table via which ID
variable.
eatDB makes use of consistency checks of SQLite3 via
using the definition of primary and foreign keys. Additionally, meta
data (e.g. variable and value labels) can be stored in a separate data
table as part of the relational data base.
# Install eatDB from GitHub via
devtools::install_github("beckerbenj/eatDB")### Setup data base
pkList <- list(df1 = "ID2", df2 = "v2")
fkList <- list(df1 = list(References = NULL, Keys = NULL),
df2 = list(References = "df1", Keys = "ID2"))
createDB(dfList = dfList, pkList = pkList, fkList = fkList, filePath = "insert/path/example.db")
### get information from data base
names_of_variables <- dbNames(filePath = "insert/path/example.db")
key_structure <- dbKeys(filePath = "insert/path/example.db")
### pull data from data base
# single data table
single_data_table <- dbSingleDF(df_name = "df1", filePath = "insert/path/example.db")
# variable selection from multiple tables
dbSingleDF(vSelect = c("var1", "var2"), filePath = "insert/path/example.db")These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.