I have a table in SQLite and I’d like to open it with dplyr. I use SQLite Expert Version 35.58.2478, R Studio Version 0.98.1062 on a PC with Win 7.
After connecting to th
I had the same problem. I solved it like below. However, I do not guarantee that the solution is rock solid. Give it a try:
library(dplyr)
library(sqldf)
# Modifying built-in mtcars dataset
mtcars$test <-
c("č", "ž", "š", "č", "ž", "š", letters) %>%
enc2utf8(.)
mtcars$češćžä <-
c("č", "ž", "š", "č", "ž", "š", letters) %>%
enc2utf8(.)
names(mtcars) <-
iconv(names(mtcars), "cp1250", "utf-8")
# Connecting to sqlite database
my_db <- src_sqlite("my_db.sqlite3", create = T)
# exporting mtcars dataset to database
copy_to(my_db, mtcars, temporary = FALSE)
# dbSendQuery(my_db$con, "drop table mtcars")
# getting data from sqlite database
my_mtcars_from_db <-
collect(tbl(my_db, "mtcars"))
# disconnecting from database
dbDisconnect(my_db$con)
# a function that encodes
# column names and values in character columns
# with specified encodings
convert_to_encoding <-
function(x, from_encoding = "UTF-8", to_encoding = "cp1250"){
# names of columns are encoded in specified encoding
my_names <-
iconv(names(x), from_encoding, to_encoding)
# if any column name is NA, leave the names
# otherwise replace them with new names
if(any(is.na(my_names))){
names(x)
} else {
names(x) <- my_names
}
# get column classes
x_char_columns <- sapply(x, class)
# identify character columns
x_cols <- names(x_char_columns[x_char_columns == "character"])
# convert all string values in character columns to
# specified encoding
x <-
x %>%
mutate_each_(funs(iconv(., from_encoding, to_encoding)),
x_cols)
# return x
return(x)
}
# use
convert_to_encoding(my_mtcars_from_db, "UTF-8", "cp1250")
# before conversion
my_mtcars_from_db
Source: local data frame [32 x 13]
mpg cyl disp hp drat wt qsec vs am gear carb češćžä test
1 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 ÄŤ ÄŤ
2 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 Ĺľ Ĺľ
3 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 š š
4 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 ÄŤ ÄŤ
5 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 Ĺľ Ĺľ
6 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 š š
7 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 a a
8 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 b b
9 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 c c
10 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 d d
.. ... ... ... ... ... ... ... .. .. ... ... ... ...
# after conversion
convert_to_encoding(my_mtcars_from_db, "UTF-8", "cp1250")
Source: local data frame [32 x 13]
mpg cyl disp hp drat wt qsec vs am gear carb test češćžä
1 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 č č
2 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 ž ž
3 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 š š
4 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 č č
5 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 ž ž
6 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 š š
7 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 a a
8 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 b b
9 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 c c
10 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 d d
.. ... ... ... ... ... ... ... .. .. ... ... ... ...
devtools::session_info()
Session info -------------------------------------------------------------------
setting value
version R version 3.2.0 (2015-04-16)
system x86_64, mingw32
ui RStudio (0.99.441)
language (EN)
collate Slovenian_Slovenia.1250
tz Europe/Prague
Packages -----------------------------------------------------------------------
package * version date source
assertthat * 0.1 2013-12-06 CRAN (R 3.2.0)
chron * 2.3-45 2014-02-11 CRAN (R 3.2.0)
DBI 0.3.1 2014-09-24 CRAN (R 3.2.0)
devtools * 1.7.0 2015-01-17 CRAN (R 3.2.0)
dplyr 0.4.1 2015-01-14 CRAN (R 3.2.0)
gsubfn 0.6-6 2014-08-27 CRAN (R 3.2.0)
lazyeval * 0.1.10 2015-01-02 CRAN (R 3.2.0)
magrittr * 1.5 2014-11-22 CRAN (R 3.2.0)
proto 0.3-10 2012-12-22 CRAN (R 3.2.0)
R6 * 2.0.1 2014-10-29 CRAN (R 3.2.0)
Rcpp * 0.11.6 2015-05-01 CRAN (R 3.2.0)
RSQLite 1.0.0 2014-10-25 CRAN (R 3.2.0)
rstudioapi * 0.3.1 2015-04-07 CRAN (R 3.2.0)
sqldf 0.4-10 2014-11-07 CRAN (R 3.2.0)