Error: No Such Column using SQLDF
sqldf(...) does not like . (period) in column names, so you need to change it to something else. Try this: library(sqldf) turnover = read.csv("turnover.csv") colnames(turnover) <- gsub("\\.","_",colnames(turnover)) turnover_hiredate = sqldf("select Status, Current_Hire_Date from turnover") The reason is that the period is used in SQL to indicate a table column, e.g....
sqldf select statements in R not working?
Cast the character column to real: > DF <- data.frame(a = "22", stringsAsFactors = FALSE) > sqldf("select * from DF where cast(a as real) > 6") a 1 22 ...
Skip metadata when Importing dataset in R
You could use count.fields() to determine the skip argument. I call your file "x.txt" read.table("x.txt", skip = which.max(count.fields("x.txt") == 7) - 1, header = TRUE) # var1 var2 var3 var4 var5 var6 var7 # 1 1 1 1 molecule1 1F3 400 4020 # 2 1 2 1 molecule2 1B5 221...
How can I keep a date formatted in R using sqldf?
specify the method as follows sqldf('select date as dt__Date, date as date__Date, acct from df ' , method = "name__class")...
R sqldf - match.fun(asfn) 'c(“as.labelled”, “as.integer”)' is not a function, character or symbol
sqldf does not support the "labelled" column class produced by Hmisc. All the columns seem to be integer or numeric so convert the columns to numeric first: demo_c[] <- lapply(demo_c, as.numeric) sqldf("select seqn from demo_c") You could convert the integer ones to integer if you prefer: isInt <- sapply(demo_c, inherits,...
How to aggregate strings in R SQLDF?
Use group_concat like this: sqldf("select DEPTNO, group_concat(ENAME) ENAMES from emp group by DEPTNO") giving: DEPTNO ENAMES 1 10 CLARK,KING,MILLER 2 20 ADAMS,FORD,JONES ...
Using INSERT statement in sqldf within R
1) As indicated in the warning it can't deal with zero dimensioned data frames so if you really want to do this then try the following: # before running this be sure that data frame d1 does NOT exist sqldf(c("create table d1(min_x real, max_x real)", "insert into d1 select min(x),...
R - join data frames in an RDB-style, and converting multiple entries from one frame to a single entry in the other (string)
1a) sqldf with multiple statements Try this: library(sqldf) dfB_s <- sqldf("select distinct * from dfB order by Name, Color") dfB_g <- sqldf("select Name, group_concat(Color) Color from dfB_s group by Name") sqldf("select * from dfA left join dfB_g using (Name)") 1b) sqldf with one statement or all in one: sqldf("select *...
R- SQLDF - SELECT … CASE… END
The problems are that the query string in the question has quotes within quotes and the syntax is wrong. Using the default SQLite database (sqldf also supports MySQL) we have: library(sqldf) data <- data.frame(E_MAIL = c("[email protected]", "[email protected]")) sqldf("select E_MAIL, case when E_MAIL like '%gmail%' then 1 when E_MAIL like '%yahoo%'...
R command to check if table exists in an sql database
My best guess is you're using the DBI pacakge which does have a dbWriteTable function (possibly via another package, it has an impressive reverse depends field on CRAN). Quickly glancing at its documentation, it also has a dbExistsTable function that seems to do what you want.
Apply CASE WHEN in sqldf statement for manipulating multiple columns
Not sure why you used sqldf, see this example: #dummy data set.seed(12) datwe <- data.frame(replicate(37,sample(c(1,2,99),10,rep=TRUE))) #convert to Yes/No res <- as.data.frame( sapply(datwe[,23:37], function(i) ifelse(i==1, "Yes", ifelse(i==2, "No", ifelse(i==99,NA,"Name itttt"))))) #update dataframe datwe <- cbind(datwe[, 1:22],res) #output, just showing first 2 columns datwe[,23:24] # X23 X24 # 1 No Yes #...
sqldf: How to query based on a date condition
My solution to this problem is to convert your date variable to character and querying on the new character variable: ## create new character version of dt variable result$chardt <- as.character(result$dt) ## query in sqldf on chardt instead sqldf("SELECT * FROM result WHERE chardt='1999-12-31'") ...
Inserting values of a column from one dataframe to another while respecting a given condition
1) This performs a left join along the indicated columns: library(sqldf) sqldf("select * from d1 left join d2 using(t1, t2, numVehicles)") We could alternately use a left natural join which causes the join to occur along commonly named columns: sqldf("select * from d1 left natural join d2") For the data...
R call variable inside sqldf
Variable i will not be replaced in the query as it is. You need sprintf to assign a value to it. (I also don't know if you need to account for break lines but just to be sure I provide it below. Maybe you don't need for sqldf; in which...
r read in multiple .dat-files
This seems to work (but i assume there is a quicker sql way to this) sql.l <- lapply(filelist , file) df_list2 <- lapply(sql.l, function(i) sqldf("select * from i" , dbname = tempfile(), file.format = list(header = TRUE, row.names = FALSE))) Look at speeds - partially taken from mnel's post Quickly...
Encoding of Umlauts while importing into R tables
Since you stated you are not geting a TRUE on agstudy's code, I'm assuming you're using a Mac or a Linux Machine. Try instead x1= "L\374ck" x2 = "L\303\274ck" iconv(x1,"latin1","UTF-8") [1] "Lück" identical(iconv(x1,"latin1","UTF-8"),x2) [1] TRUE Tested this on a Linux CentOS 7. I believe it should work on Macs too....
Shortest time and trip between two stops across many trip options (GTFS)
I think this should work using max and case with limit: select trip_id, max(case when stop_id = 90003 then arrival_time end) - max(case when stop_id = 90001 then departure_time end) from stop_times where stop_id in (90001,90003) group by trip_id order by 1 limit 1 SQL Fiddle Demo I will note...
How can I concatenate strings in SQLDF in R
Just use the syntax for concatenation in SQL, e.g., d <- data.frame(x = c("a", "b"), y = c("1", "2")) sqldf("select *, x||y from d") # x y x||y # 1 a 1 a1 # 2 b 2 b2 ...
Identify Inf in sqldf
Try this: > sqldf("select val from x where cast(val as text) != 'Inf'") val 1 1 2 2 3 3 ...
ERROR use datename/datepart in R sqldf package
sqldf is a thin layer which passes the data and SQL statement to a back end of your choice. The default back end is sqlite but it also supports H2, PostgreSQL and MySQL. SQLite does not support datename but H2 does support dayname: # reproducibly set up input data frame...
Created table, by selecting from data frames when a match occurs
Could try some merge manipulations such as temp <- merge(data, dbase, by.x = "iddata", by.y = "idbase", all = TRUE) temp2 <- data.frame("nr" = unlist(dcode)) temp2$foc <- rep(names(dcode), each = nrow(dcode)) temp <- merge(temp, temp2, by = "nr", all.x = TRUE) temp[order(temp$iddata), ] # nr iddata foc # 12 115...
Trouble Finding ID's with Duplicate Fields
Are you also sure you don't have the opposite condition, multiple ids with the same email? select Email, count(*) from data group by Email having count(*) > 1; ...
Select specified rows when importing CSV
Try this example: library(sqldf) #dummy csv write.csv(data.frame(myid=1:10,var=runif(10)),"temp.csv") #define ids ids <- c(1,3,4) ids <- paste(ids,collapse = ",") f <- file("temp.csv") #query with subset fn$sqldf("select * from f where myid in ($ids)", file.format = list(header = TRUE, sep = ",")) #output # X myid var # 1 "1" 1 0.2310945 #...
Count of data by Sqldf
An option using data.table library(data.table) setDT(df1)[, Count:=.N, ID] # ID category Count #1: 101 A 3 #2: 101 B 3 #3: 101 C 3 #4: 102 A 1 #5: 103 B 2 #6: 103 C 2 Or using dplyr library(dplyr) df1 %>% group_by(ID) %>% mutate(Count=n()) Or using base R df1$Count...