target_by.tbl_dbi: Target by one column in the DBMS

Description

In the data analysis, a target_df class is created to identify the relationship between the target column and the other column of the DBMS table through tbl_dbi

Usage

# S3 method for tbl_dbi
target_by(.data, target, in_database = FALSE,
  collect_size = Inf, ...)

Arguments

.data

a tbl_dbi.

target

target variable.

in_database

Specifies whether to perform in-database operations. If TRUE, most operations are performed in the DBMS. if FALSE, table data is taken in R and operated in-memory. Not yet supported in_database = TRUE.

collect_size

a integer. The number of data samples from the DBMS to R. Applies only if in_database = FALSE.

...

arguments to be passed to methods.

Value

an object of target_df class. Attributes of target_df class is as follows.

type_y : the data type of target variable.

Details

Data analysis proceeds with the purpose of predicting target variables that correspond to the facts of interest, or examining associations and relationships with other variables of interest. Therefore, it is a major challenge for EDA to examine the relationship between the target variable and its corresponding variable. Based on the derived relationships, analysts create scenarios for data analysis.

target_by() inherits the grouped_df class and returns a target_df class containing information about the target variable and the variable.

See vignette("EDA") for an introduction to these concepts.

Examples

Run this code

# NOT RUN {
library(dplyr)

# Generate data for the example
carseats <- ISLR::Carseats
carseats[sample(seq(NROW(carseats)), 20), "Income"] <- NA
carseats[sample(seq(NROW(carseats)), 5), "Urban"] <- NA

# connect DBMS
con_sqlite <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")

# copy carseats to the DBMS with a table named TB_CARSEATS
copy_to(con_sqlite, carseats, name = "TB_CARSEATS", overwrite = TRUE)

# If the target variable is a categorical variable
categ <- target_by(con_sqlite %>% tbl("TB_CARSEATS") , US)

# If the variable of interest is a numarical variable
cat_num <- relate(categ, Sales)
cat_num
summary(cat_num)
plot(cat_num)

# If the variable of interest is a categorical column
cat_cat <- relate(categ, ShelveLoc)
cat_cat
summary(cat_cat)
plot(cat_cat)

##---------------------------------------------------
# If the target variable is a categorical column, 
# and In-memory mode and collect size is 350
num <- target_by(con_sqlite %>% tbl("TB_CARSEATS"), Sales, collect_size = 350)

# If the variable of interest is a numarical column
num_num <- relate(num, Price)
num_num
summary(num_num)
plot(num_num)
plot(num_num, hex_thres = 400)

# If the variable of interest is a categorical column
num_cat <- relate(num, ShelveLoc)
num_cat
summary(num_cat)
plot(num_cat)
# }