Sqldf in R - error with first column names - sql

Whenever I use read.csv.sql I cannot select from the first column with and any output from the code places an unusual character (A(tilde)-..) at the begging of the first column's name.
So suppose I create a df.csv file in in Excel that looks something like this
df = data.frame(
a = 1,
b = 2,
c = 3,
d = 4)
Then if I use sqldf to query the csv which is in my working directory I get the following error:
> read.csv.sql("df.csv", sql = "select * from file where a == 1")
Error in result_create(conn#ptr, statement) : no such column: a
If I query a different column than the first, I get a result but with the output of the unusual characters as seen below
df <- read.csv.sql("df.csv", sql = "select * from file where b == 2")
View(df)
Any idea how to prevent these characters from being added to the first column name?

The problem is presumably that you have a file that is larger than R can handle and so only want to read a subset of rows into R and specifying the condition to filter it by involves referring to the first column whose name is messed up so you can't use it.
Here are two alternative approaches. The first one involves a bit more code but has the advantage that it is 100% R. The second one is only one statement and also uses R but additionally makes use an of an external utility.
1) skip header Read the file in skipping over the header. That will cause the columns to be labelled V1, V2, etc. and use V1 in the condition.
# write out a test file - BOD is a data frame that comes with R
write.csv(BOD, "BOD.csv", row.names = FALSE, quote = FALSE)
# read file skipping over header
DF <- read.csv.sql("BOD.csv", "select * from file where V1 < 3",
skip = 1, header = FALSE)
# read in header, assign it to DF and fix first column
hdr <- read.csv.sql("BOD.csv", "select * from file limit 0")
names(DF) <- names(hdr)
names(DF)[1] <- "TIME" # suppose we want TIME instead of Time
DF
## TIME demand
## 1 1 8.3
## 2 2 10.3
2) filter Another way to proceed is to use the filter= argument. Here we assume we know that the end of the column name is ime but there are other characters prior to that that we don't know. This assumes that sed is available and on your path. If you are on Windows install Rtools to get sed. The quoting might need to be changed depending on your shell.
When trying this on Windows I noticed that sed from Rtools changed the line endings so below we specified eol= to ensure correct processing. You may not need that.
DF <- read.csv.sql("BOD.csv", "select * from file where TIME < 3",
filter = 'sed -e "1s/.*ime,/TIME,/"' , eol = "\n")
DF
## TIME demand
## 1 1 8.3
## 2 2 10.3

So I figured it out by reading through the above comments.
I'm on a Windows 10 machine using Excel for Office 365. The special characters will go away by changing how I saved the file from a "CSV UTF-8 (Comma Delimited)" to just "CSV (Comma delimited)".

Related

Clean up code and keep null values from crashing read.csv.sql

I am using read.csv.sql to conditionally read in data (my data set is extremely large so this was the solution I chose to filter it and reduce it in size prior to reading the data in). I was running into memory issues by reading in the full data and then filtering it so that is why it is important that I use the conditional read so that the subset is read in, versus the full data set.
Here is a small data set so my problem can be reproduced:
write.csv(iris, "iris.csv", row.names = F)
library(sqldf)
csvFile <- "iris.csv"
I am finding that the notation you have to use is extremely awkward using read.csv.sql the following is the how I am reading in the file:
# Step 1 (Assume these values are coming from UI)
spec <- 'setosa'
petwd <- 0.2
# Add quotes and make comma-separated:
spec <- toString(sprintf("'%s'", spec))
petwd <- toString(sprintf("'%s'", petwd))
# Step 2 - Conditionally read in the data, store in 'd'
d <- fn$read.csv.sql(csvFile, sql='select * from file where
"Species" in ($spec)'
and "Petal.Width" in ($petwd)',
filter = list('gawk -f prog', prog = '{ gsub(/"/, ""); print }'))
My main problem is that if any of the values above (from UI) are null then it won't read in the data properly, because this chunk of code is all hard coded.
I would like to change this into: Step 1 - check which values are null and do not filter off of them, then filter using read.csv.sql for all non-null values on corresponding columns.
Note: I am reusing the code from this similar question within this question.
UPDATE
I want to clear up what I am asking. This is what I am trying to do:
If a field, say spec comes through as NA (meaning the user did not pick input) then I want it to filter as such (default to spec == EVERY SPEC):
# Step 2 - Conditionally read in the data, store in 'd'
d <- fn$read.csv.sql(csvFile, sql='select * from file where
"Petal.Width" in ($petwd)',
filter = list('gawk -f prog', prog = '{ gsub(/"/, ""); print }'))
Since spec is NA, if you try to filter/read in a file matching spec == NA it will read in an empty data set since there are no NA values in my data, hence breaking the code and program. Hope this clears it up more.
There are several problems:
some of the simplifications provided in the link in the question were not followed.
spec is a scalar so one can just use '$spec'
petwd is a numeric scalar and SQL does not require quotes around numbers so just use $petwd
the question states you want to handle empty fields but not how so we have used csvfix to map them to -1 and also strip off quotes. (Alternately let them enter and do it in R. Empty numerics will come through as 0 and empty character fields will come through as zero length character fields.)
you can use [...] in place of "..." in SQL
The code below worked for me in both Windows and Ubuntu Linux with the bash shell.
library(sqldf)
spec <- 'setosa'
petwd <- 0.2
d <- fn$read.csv.sql(
"iris.csv",
sql = "select * from file where [Species] = '$spec' and [Petal.Width] = $petwd",
verbose = TRUE,
filter = 'csvfix map -smq -fv "" -tv -1'
)
Update
Regarding the update at the end of the question it was clarified that the NA could be in spec as opposed to being in the data being read in and that if spec is NA then the condition involving spec should be regarded as TRUE. In that case just expand the SQL where condition to handle that as follows.
spec <- NA
petwd <- 0.2
d <- fn$read.csv.sql(
"iris.csv",
sql = "select * from file
where ('$spec' == 'NA' or [Species] = '$spec') and [Petal.Width] = $petwd",
verbose = TRUE,
filter = 'csvfix echo -smq'
)
The above will return all rows for which Petal.Width is 0.2 .

in R, read special columns with read.csv.sql

I am trying to read a big csv file. Indeed, I want select a subset using a special column which name is Race Color. Reading the file via read.csv, I have the head
library(sqldf)
df <- read.csv(file = 'df.txt', header = T, sep = ";")
head(df)
id Region Race Color ....
1 1 1
2 1 1
3 2 1
4 3 2
5 4 1
6 4 1
I would like to use read.csv.sql for selecting a subset of df without use the read.csv file. For example, I want all the people with Race Color equal to 1.
Using read.csv.sql, I have something like
>df <- read.csv.sql("df.txt", sql = "select * from file where Race Color = 1", sep=";", header=T, eol="\n")
but I have the following error
Error in sqliteSendQuery(con, statement, bind.data) :
error in statement: near "Color": syntax error
Trying
>df <- read.csv.sql("df.txt", sql = "select * from file where 'Race Color' = 1", sep=";", header=T, eol="\n")
I have df with zero rows.
Any solution?
R automatically adds a . to column names with a space on reading in the data to make Race.Color, but a . has a special meaning in sql, so that will screw things up.
There is a built in method in sqldf using square brackets ([Race.Color]) to explicitly name columns we can use so that we don't run into that problem. You can also use escaped quotes : \"Race.Color\"
This should work:
library(sqldf)
read.csv.sql("test.csv", sql = "select * from file where [Race.Color] = 1", sep=";", header=T, eol="\n")

FDR Error fdrtool in R

Iam using fdrtool for my pvalues but i have an error which is :
Error in if (max(x) > 1 | min(x) < 0) stop("input p-values must all be in the range 0 to 1!") : missing value where TRUE/FALSE needed
The p value are not less than 0,greater than 1.
The range of p value are [1,0]. the code is :
n=40000
pval1<-vector(length=n)
pval1[1:n]= pv1list[["Pvalue"]]
fdr<-fdrtool(pval1,statistic="pvalue")
I ran your code without problem (although I can't reproduce it because I don't have the object "pvlist").
Since you're having a missing value error, my guess is that you're having problems reading the csv file into R. I recommend the "read.table" function since from my experience it usually reads in data from a csv file without errors:
pvlist<- read.table("c:/pvslit.csv", header=TRUE,
sep=",", row.names="id")
And now you want to check the number of rows and missingness:
nrow(pvlist) # is this what you expect?
nrow(na.omit(pvlist)) # how many non-missing rows are there?
Additionally you want to make sure that your "p-value" column is not a character or factor:
str(pvlist) # examining the structure of the dataframe
pvlist[,2] <- as.numeric(pvlist[,2]) # assuming the 2nd column is the pvalue
In short, you most likely have a problem with reading in the data or the class of the data in the dataframe.

Read only n-th column of a text file which has no header with R and sqldf

I have a similiar problem like this question:
selecting every Nth column in using SQLDF or read.csv.sql
I want to read some columns of large files (table of 150rows, >500,000 columns, space separated, filled with numeric data and only a 32 bit system available). This file has no header, therefore the code in the thread above didn't work and I decided to write a new post.
Do you have an idea to solve this problem?
I thought about something like that, but any results with fread or read.table are also ok:
MyConnection <- file("path/file.txt")
df<-sqldf("select column 1 100 1000 235612 from MyConnection",file.format = list(header=F,sep=" "))
You can use substr to specify the start and end position of the columns you want to read in if they are fixed width:
x <- tempfile()
cat("12345", "67890", "09876", "54321", sep = "\n", file = x)
myfile <- file(x)
sqldf("select substr(V1, 1, 1) var1, substr(V1, 3, 5) var2 from myfile")
# var1 var2
# 1 1 345
# 2 6 890
# 3 9 76
# 4 5 321
See this blog post for some more examples. The "select" statement can easily be constructed with paste if you know the details about the column starting positions and widths.

gnuplot store one number from data file into variable

OSX v10.6.8 and Gnuplot v4.4
I have a data file with 8 columns. I would like to take the first value from the 6th column and make it the title. Here's what I have so far:
#m1 m2 q taua taue K avgPeriodRatio time
#1 2 3 4 5 6 7 8
K = #read in data here
graph(n) = sprintf("K=%.2e",n)
set term aqua enhanced font "Times-Roman,18"
plot file using 1:3 title graph(K)
And here is what the first few rows of my data file looks like:
1.00e-07 1.00e-07 1.00e+00 1.00e+05 1.00e+04 1.00e+01 1.310 12070.00
1.11e-06 1.00e-07 9.02e-02 1.00e+05 1.00e+04 1.00e+01 1.310 12070.00
2.12e-06 1.00e-07 4.72e-02 1.00e+05 1.00e+04 1.00e+01 1.310 12070.00
3.13e-06 1.00e-07 3.20e-02 1.00e+05 1.00e+04 1.00e+01 1.310 12090.00
I don't know how to correctly read in the data or if this is even the right way to go about this.
EDIT #1
Ok, thanks to mgilson I now have
#m1 m2 q taua taue K avgPeriodRatio time
#1 2 3 4 5 6 7 8
set term aqua enhanced font "Times-Roman,18"
K = "`head -1 datafile | awk '{print $6}'`"
print K+0
graph(n) = sprintf("K=%.2e",n)
plot file using 1:3 title graph(K)
but I get the error: Non-numeric string found where a numeric expression was expected
EDIT #2
file = "testPlot.txt"
K = "`head -1 file | awk '{print $6}'`"
K=K+0 #Cast K to a floating point number #this is line 9
graph(n) = sprintf("K=%.2e",n)
plot file using 1:3 title graph(K)
This gives the error--> head: file: No such file or directory
"testPlot.gnu", line 9: Non-numeric string found where a numeric expression was expected
You have a few options...
FIRST OPTION:
use columnheader
plot file using 1:3 title columnheader(6)
I haven't tested it, but this may prevent the first row from actually being plotted.
SECOND OPTION:
use an external utility to get the title:
TITLE="`head -1 datafile | awk '{print $6}'`"
plot 'datafile' using 1:3 title TITLE
If the variable is numeric, and you want to reformat it, in gnuplot, you can cast strings to a numeric type (integer/float) by adding 0 to them (e.g).
print "36.5"+0
Then you can format it with sprintf or gprintf as you're already doing.
It's weird that there is no float function. (int will work if you want to cast to an integer).
EDIT
The script below worked for me (when I pasted your example data into a file called "datafile"):
K = "`head -1 datafile | awk '{print $6}'`"
K=K+0 #Cast K to a floating point number
graph(n) = sprintf("K=%.2e",n)
plot "datafile" using 1:3 title graph(K)
EDIT 2 (addresses comments below)
To expand a variable in backtics, you'll need macros:
set macro
file="mydatafile.txt"
#THE ORDER OF QUOTES (' and ") IS CRUCIAL HERE.
cmd='"`head -1 ' . file . ' | awk ''{print $6}''`"'
# . is string concatenation. (this string has 3 pieces)
# to get a single quote inside a single quoted string
# you need to double. e.g. 'a''b' yields the string a'b
data=#cmd
To address your question 2, it is a good idea to familiarize yourself with shell utilities -- sed and awk can both do it. I'll show a combination of head/tail:
cmd='"`head -2 ' . file . ' | tail -1 | awk ''{print $6}''`"'
should work.
EDIT 3
I recently learned that in gnuplot, system is a function as well as a command. To do the above without all the backtic gymnastics,
data=system("head -1 " . file . " | awk '{print $6}'")
Wow, much better.
This is a very old question, but here's a nice way to get access to a single value anywhere in your data file and save it as a gnuplot-accessible variable:
set term unknown #This terminal will not attempt to plot anything
plot 'myfile.dat' index 0 every 1:1:0:0:0:0 u (var=$1):1
The index number allows you to address a particular dataset (separated by two carriage returns), while every allows you to specify a particular line.
The colon-separated numbers after every should be of the form 1:1:<line_number>:<block_number>:<line_number>:<block_number>, where the line number is the line with the the block (starting from 0), and the block number is the number of the block (separated by a single carriage return, again starting from 0). The first and second numbers say plot every 1 lines and every one data block, and the third and fourth say start from line <line_number> and block <block_number>. The fifth and sixth say where to stop. This allows you to select a single line anywhere in your data file.
The last part of the plot command assigns the value in a particular column (in this case, column 1) to your variable (var). There needs to be two values to a plot command, so I chose column 1 to plot against my variable assignment statement.
Here is a less 'awk'-ward solution which assigns the value from the first row and 6th column of the file 'Data.txt' to the variable x16.
set table
# Syntax: u 0:($0==RowIndex?(VariableName=$ColumnIndex):$ColumnIndex)
# RowIndex starts with 0, ColumnIndex starts with 1
# 'u' is an abbreviation for the 'using' modifier
plot 'Data.txt' u 0:($0==0?(x16=$6):$6)
unset table
A more general example for storing several values is given below:
# Load data from file to variable
# Gnuplot can only access the data via the "plot" command
set table
# Syntax: u 0:($0==RowIndex?(VariableName=$ColumnIndex):$ColumnIndex)
# RowIndex starts with 0, ColumnIndex starts with 1
# 'u' is an abbreviation for the 'using' modifier
# Example: Assign all values according to: xij = Data33[i,j]; i,j = 1,2,3
plot 'Data33.txt' u 0:($0==0?(x11=$1):$1),\
'' u 0:($0==0?(x12=$2):$2),\
'' u 0:($0==0?(x13=$3):$3),\
'' u 0:($0==1?(x21=$1):$1),\
'' u 0:($0==1?(x22=$2):$2),\
'' u 0:($0==1?(x23=$3):$3),\
'' u 0:($0==2?(x31=$1):$1),\
'' u 0:($0==2?(x32=$2):$2),\
'' u 0:($0==2?(x33=$3):$3)
unset table
print x11, x12, x13 # Data from first row
print x21, x22, x23 # Data from second row
print x31, x32, x33 # Data from third row