I have few blank values in one of my columns in dataset. I need to make sql query to database with only this few id (86) that contain missing value.
I have in mind something like that (not just paste id to in statement):
SELECT x.id,
x.sent
FROM x
WHERE x.id IN [my R vector with id]
glue_sql will expand vectors into a comma separated list if you use * after the variable name in the glue expression.
glue::glue_sql("
SELECT x.id,
x.sent
FROM x
WHERE x.id IN ({idVector*})
", .con = con)
con is a DBI connection to your database
Conjecture.
Real data is in #sourcemt (a temp table, the "#" is purely local for my database, ignore it).
sourcemt <- mt <- transform(mtcars, id = seq_len(nrow(mtcars)))
DBI::dbWriteTable(con, "#sourcemt", sourcemt)
mt <- head(mt)
mt$cyl[c(1,3,4)] <- NA
mt
# mpg cyl disp hp drat wt qsec vs am gear carb id
# Mazda RX4 21.0 NA 160 110 3.90 2.620 16.46 0 1 4 4 1
# Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 2
# Datsun 710 22.8 NA 108 93 3.85 2.320 18.61 1 1 4 1 3
# Hornet 4 Drive 21.4 NA 258 110 3.08 3.215 19.44 1 0 3 1 4
# Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 5
# Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1 6
We want to fix the missing cyl values.
miss_ids <- mt$id[is.na(mt$cyl)]
miss_ids
# [1] 1 3 4
(qmarks <- paste(rep("?", length(miss_ids)), collapse = ","))
# [1] "?,?,?"
fixmt <- DBI::dbGetQuery(con, sprintf("select id, cyl from #sourcemt where id in (%s)", qmarks), params = miss_ids)
fixmt
# id cyl
# 1 1 6
# 2 3 4
# 3 4 6
(FYI, the qmarks parts are using parameter-binding for safe querying of data without paste-ing or sprintf-ing the data into the query. See parameterized queries for good discussions about this.)
From here, we just need to merge them and coalesce the missing values back in. (Both methods below should capture the output back into mt.)
library(dplyr)
mt %>%
left_join(fixmt, by = "id", suffix = c("", ".y")) %>%
mutate(cyl = coalesce(cyl, cyl.y)) %>%
select(-cyl.y)
# mpg cyl disp hp drat wt qsec vs am gear carb id
# 1 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 1
# 2 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 2
# 3 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 3
# 4 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 4
# 5 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 5
# 6 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1 6
merge(mt, fixmt, by = "id", all.x = TRUE, suffixes = c("", ".y")) |>
transform(cyl = ifelse(is.na(cyl), cyl.y, cyl), cyl.y = NULL)
# id mpg cyl disp hp drat wt qsec vs am gear carb
# 1 1 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
# 2 2 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
# 3 3 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
# 4 4 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
# 5 5 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
# 6 6 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
