Nothing
## ----pre, include = FALSE-----------------------------------------------------
if (!rlang::is_installed("randomForest")) {
knitr::opts_chunk$set(
eval = FALSE
)
}
## ----setup, include=FALSE-----------------------------------------------------
library(dplyr)
library(tidypredict)
library(randomForest)
library(dbplyr)
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
set.seed(100)
## -----------------------------------------------------------------------------
library(dplyr)
library(tidypredict)
library(randomForest)
library(dbplyr)
flights_table <- nycflights13::flights %>%
mutate(
current_score = 0,
flight_id = row_number()
)
## -----------------------------------------------------------------------------
library(DBI)
con <- dbConnect(RSQLite::SQLite(), path = ":memory:")
db_fligths <- copy_to(con,flights_table )
## -----------------------------------------------------------------------------
df <- db_fligths %>%
select(dep_delay, hour, distance) %>%
head(1000) %>%
collect()
## -----------------------------------------------------------------------------
model <- lm(dep_delay ~ ., data = df)
## -----------------------------------------------------------------------------
tidypredict_test(model)
## ---- eval = FALSE------------------------------------------------------------
# if(tidypredict_test(model)$alert) stop("Threshold exceeded!")
## -----------------------------------------------------------------------------
library(dbplyr)
update_statement <- build_sql("UPDATE flights_table SET current_score = ", tidypredict_sql(model, con = con), con = con)
update_statement
## -----------------------------------------------------------------------------
dbSendQuery(con, update_statement)
## -----------------------------------------------------------------------------
db_fligths %>%
select(current_score) %>%
head(10)
## -----------------------------------------------------------------------------
dbWriteTable(con, "daily_scores",
tibble(
flight_id = 0,
score = 0,
date = ""
))
## -----------------------------------------------------------------------------
new_predictions <- db_fligths %>%
filter(month == 12) %>%
tidypredict_to_column(model, vars = "score") %>%
select(
flight_id,
score) %>%
mutate(date = "01/01/2018")
## -----------------------------------------------------------------------------
insert_scores <- build_sql("INSERT INTO daily_scores ", sql_render(new_predictions, con = con), con = con)
insert_scores
## -----------------------------------------------------------------------------
dbSendQuery(con, insert_scores)
## -----------------------------------------------------------------------------
tbl(con, "daily_scores") %>%
inner_join(tbl(con, "flights_table"), by = "flight_id") %>%
filter(date == "01/01/2018") %>%
select(dep_delay, hour, distance, score, date)
## ---- include = FALSE---------------------------------------------------------
dbDisconnect(con)
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