On 07/18/2020 11:54 AM, Rui Barradas wrote:> Hello, > > I don't believe that what you are asking for is possible but like Bert suggested, you can do it after reading in the data. > You could write a convenience function to read the data, then change what you need to change. > Then the function would return this final object. > > Rui Barradas > > ?s 16:43 de 18/07/2020, H escreveu: > >> On 07/17/2020 09:49 PM, Bert Gunter wrote: >>> Is there some reason that you can't make the changes to the data frame (column names, as.date(), ...) *after* you have read all your data in? >>> >>> Do all your csv files use the same names and date formats? >>> >>> >>> Bert Gunter >>> >>> "The trouble with having an open mind is that people keep coming along and sticking things into it." >>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) >>> >>> >>> On Fri, Jul 17, 2020 at 6:28 PM H <agents at meddatainc.com <mailto:agents at meddatainc.com>> wrote: >>> >>> ???? I have created a dataframe with columns that are characters, integers and numeric and with column names assigned by me. I am using read.csv.sql() to read portions of a number of large csv files into this dataframe, each csv file having a header row with columb names. >>> >>> ???? The problem I am having is that the csv files have header rows with column names that are slightly different from the column names I have assigned in the dataframe and it seems that when I read the csv data into the dataframe, the column names from the csv file replace the column names I chose when creating the dataframe. >>> >>> ???? I have been unable to figure out if it is possible to assign column names of my choosing in the read.csv.sql() function? I have tried various variations but none seem to work. I tried colClasses = c(....) but that did not work, I tried field.types = c(...) but could not get that to work either. >>> >>> ???? It seems that the above should be feasible but I am missing something? Does anyone know? >>> >>> ???? A secondary issue is that the csv files have a column with a date in mm/dd/yyyy format that I would like to make into a Date type column in my dataframe. Again, I have been unable to find a way - if at all possible - to force a conversion into a Date format when importing into the dataframe. The best I have so far is to import is a character column and then use as.Date() to later force the conversion of the dataframe column. >>> >>> ???? Is it possible to do this when importing using read.csv.sql()? >>> >>> ???? ______________________________________________ >>> ???? R-help at r-project.org <mailto:R-help at r-project.org> mailing list -- To UNSUBSCRIBE and more, see >>> ???? https://stat.ethz.ch/mailman/listinfo/r-help >>> ???? PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >>> ???? and provide commented, minimal, self-contained, reproducible code. >>> >> Yes, the files use the same column names and date format (at least as far as I know now.) I agree I could do it as you suggest above but from a purist perspective I would rather do it when importing the data using read.csv.sql(), particularly if column names and/or date format might change, or be different between different files. I am indeed selecting rows from a large number of csv files so this is entirely plausible. >> >> Has anyone been able to name columns in the read.csv.sql() call and/or force date format conversion in the call itself? The first refers to naming columns differently from what a header in the csv file may have. >> >> >> ????[[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >The documentation for read.csv.sql() suggests that colClasses() and/or field.types() should work but I may well have misunderstood the documentation, hence my question in this group.
Hello, The documentation says the following. field.types A list whose names are the column names and whose contents are the SQLite types (not the R class names) of the columns. So argument field.types is a named list. ?- The list members names are the column names of the table to be read. ?- The list members values are SQLite types, like "CHAR", "VARCHAR", "INT", etc. As for colClasses, those are R class names. Rui Barradas ?s 17:59 de 18/07/2020, H escreveu:> On 07/18/2020 11:54 AM, Rui Barradas wrote: >> Hello, >> >> I don't believe that what you are asking for is possible but like Bert suggested, you can do it after reading in the data. >> You could write a convenience function to read the data, then change what you need to change. >> Then the function would return this final object. >> >> Rui Barradas >> >> ?s 16:43 de 18/07/2020, H escreveu: >> >>> On 07/17/2020 09:49 PM, Bert Gunter wrote: >>>> Is there some reason that you can't make the changes to the data frame (column names, as.date(), ...) *after* you have read all your data in? >>>> >>>> Do all your csv files use the same names and date formats? >>>> >>>> >>>> Bert Gunter >>>> >>>> "The trouble with having an open mind is that people keep coming along and sticking things into it." >>>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) >>>> >>>> >>>> On Fri, Jul 17, 2020 at 6:28 PM H <agents at meddatainc.com <mailto:agents at meddatainc.com>> wrote: >>>> >>>> ???? I have created a dataframe with columns that are characters, integers and numeric and with column names assigned by me. I am using read.csv.sql() to read portions of a number of large csv files into this dataframe, each csv file having a header row with columb names. >>>> >>>> ???? The problem I am having is that the csv files have header rows with column names that are slightly different from the column names I have assigned in the dataframe and it seems that when I read the csv data into the dataframe, the column names from the csv file replace the column names I chose when creating the dataframe. >>>> >>>> ???? I have been unable to figure out if it is possible to assign column names of my choosing in the read.csv.sql() function? I have tried various variations but none seem to work. I tried colClasses = c(....) but that did not work, I tried field.types = c(...) but could not get that to work either. >>>> >>>> ???? It seems that the above should be feasible but I am missing something? Does anyone know? >>>> >>>> ???? A secondary issue is that the csv files have a column with a date in mm/dd/yyyy format that I would like to make into a Date type column in my dataframe. Again, I have been unable to find a way - if at all possible - to force a conversion into a Date format when importing into the dataframe. The best I have so far is to import is a character column and then use as.Date() to later force the conversion of the dataframe column. >>>> >>>> ???? Is it possible to do this when importing using read.csv.sql()? >>>> >>>> ???? ______________________________________________ >>>> ???? R-help at r-project.org <mailto:R-help at r-project.org> mailing list -- To UNSUBSCRIBE and more, see >>>> ???? https://stat.ethz.ch/mailman/listinfo/r-help >>>> ???? PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >>>> ???? and provide commented, minimal, self-contained, reproducible code. >>>> >>> Yes, the files use the same column names and date format (at least as far as I know now.) I agree I could do it as you suggest above but from a purist perspective I would rather do it when importing the data using read.csv.sql(), particularly if column names and/or date format might change, or be different between different files. I am indeed selecting rows from a large number of csv files so this is entirely plausible. >>> >>> Has anyone been able to name columns in the read.csv.sql() call and/or force date format conversion in the call itself? The first refers to naming columns differently from what a header in the csv file may have. >>> >>> >>> ????[[alternative HTML version deleted]] >>> >>> ______________________________________________ >>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. > The documentation for read.csv.sql() suggests that colClasses() and/or field.types() should work but I may well have misunderstood the documentation, hence my question in this group. > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.-- Este e-mail foi verificado em termos de v?rus pelo software antiv?rus Avast. https://www.avast.com/antivirus
Do either of the postings/threads below help? https://r.789695.n4.nabble.com/read-csv-sql-to-select-from-a-large-csv-file-td4650565.html#a4651534 https://r.789695.n4.nabble.com/using-sqldf-s-read-csv-sql-to-read-a-file-with-quot-NA-quot-for-missing-td4642327.html Otherwise you can try reading through the FAQ on Github: https://github.com/ggrothendieck/sqldf HTH, Bill. W. Michels, Ph.D. On Sat, Jul 18, 2020 at 9:59 AM H <agents at meddatainc.com> wrote:> > On 07/18/2020 11:54 AM, Rui Barradas wrote: > > Hello, > > > > I don't believe that what you are asking for is possible but like Bert suggested, you can do it after reading in the data. > > You could write a convenience function to read the data, then change what you need to change. > > Then the function would return this final object. > > > > Rui Barradas > > > > ?s 16:43 de 18/07/2020, H escreveu: > > > >> On 07/17/2020 09:49 PM, Bert Gunter wrote: > >>> Is there some reason that you can't make the changes to the data frame (column names, as.date(), ...) *after* you have read all your data in? > >>> > >>> Do all your csv files use the same names and date formats? > >>> > >>> > >>> Bert Gunter > >>> > >>> "The trouble with having an open mind is that people keep coming along and sticking things into it." > >>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > >>> > >>> > >>> On Fri, Jul 17, 2020 at 6:28 PM H <agents at meddatainc.com <mailto:agents at meddatainc.com>> wrote: > >>> > >>> I have created a dataframe with columns that are characters, integers and numeric and with column names assigned by me. I am using read.csv.sql() to read portions of a number of large csv files into this dataframe, each csv file having a header row with columb names. > >>> > >>> The problem I am having is that the csv files have header rows with column names that are slightly different from the column names I have assigned in the dataframe and it seems that when I read the csv data into the dataframe, the column names from the csv file replace the column names I chose when creating the dataframe. > >>> > >>> I have been unable to figure out if it is possible to assign column names of my choosing in the read.csv.sql() function? I have tried various variations but none seem to work. I tried colClasses = c(....) but that did not work, I tried field.types = c(...) but could not get that to work either. > >>> > >>> It seems that the above should be feasible but I am missing something? Does anyone know? > >>> > >>> A secondary issue is that the csv files have a column with a date in mm/dd/yyyy format that I would like to make into a Date type column in my dataframe. Again, I have been unable to find a way - if at all possible - to force a conversion into a Date format when importing into the dataframe. The best I have so far is to import is a character column and then use as.Date() to later force the conversion of the dataframe column. > >>> > >>> Is it possible to do this when importing using read.csv.sql()? > >>> > >>> ______________________________________________ > >>> R-help at r-project.org <mailto:R-help at r-project.org> mailing list -- To UNSUBSCRIBE and more, see > >>> https://stat.ethz.ch/mailman/listinfo/r-help > >>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > >>> and provide commented, minimal, self-contained, reproducible code. > >>> > >> Yes, the files use the same column names and date format (at least as far as I know now.) I agree I could do it as you suggest above but from a purist perspective I would rather do it when importing the data using read.csv.sql(), particularly if column names and/or date format might change, or be different between different files. I am indeed selecting rows from a large number of csv files so this is entirely plausible. > >> > >> Has anyone been able to name columns in the read.csv.sql() call and/or force date format conversion in the call itself? The first refers to naming columns differently from what a header in the csv file may have. > >> > >> > >> [[alternative HTML version deleted]] > >> > >> ______________________________________________ > >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > >> https://stat.ethz.ch/mailman/listinfo/r-help > >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > >> and provide commented, minimal, self-contained, reproducible code. > > > The documentation for read.csv.sql() suggests that colClasses() and/or field.types() should work but I may well have misunderstood the documentation, hence my question in this group. > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.
On 2020-07-18 18:09 +0100, Rui Barradas wrote: | ?s 17:59 de 18/07/2020, H escreveu: | | On Fri, Jul 17, 2020 at 6:28 PM H <agents at meddatainc.com> wrote: | | | | | | The problem I am having is that | | | the csv files have header rows | | | with column names that are | | | slightly different from the column | | | names I have assigned in the | | | dataframe and it seems that when I | | | read the csv data into the | | | dataframe, the column names from | | | the csv file replace the column | | | names I chose when creating the | | | dataframe. | | | | | | A secondary issue is that the csv | | | files have a column with a date in | | | mm/dd/yyyy format that I would | | | like to make into a Date type | | | column in my dataframe. Again, I | | | have been unable to find a way - | | | if at all possible - to force a | | | conversion into a Date format when | | | importing into the dataframe. The | | | best I have so far is to import is | | | a character column and then use | | | as.Date() to later force the | | | conversion of the dataframe | | | column. | | | | The documentation for read.csv.sql() | | suggests that colClasses() and/or | | field.types() should work but I may | | well have misunderstood the | | documentation, hence my question in | | this group. | | As for colClasses, those are R class | names. Ok Mister H, I might have hit the nail on the head this time with this badass example for your usecase: # Make a csv with %d/%m/%Y dates in it ... Lines <- "STM05-1 2005/02/28 17:35 Good -35.562 177.158 STM05-1 2005/02/28 19:44 Good -35.487 177.129 STM05-1 2005/02/28 23:01 Unknown -35.399 177.064 STM05-1 2005/03/01 07:28 Unknown -34.978 177.268 STM05-1 2005/03/01 18:06 Poor -34.799 177.027 STM05-1 2005/03/01 18:47 Poor -34.85 177.059 STM05-2 2005/02/28 12:49 Good -35.928 177.328 STM05-2 2005/02/28 21:23 Poor -35.926 177.314 " DF <- read.table(textConnection(Lines), as.is = TRUE, col.names = c("Id", "Date", "Time", "Quality", "Lat", "Long")) DF$Date <- format(as.Date(DF$Date, "%Y/%m/%d"), "%d/%m/%Y") write.csv(DF, file="df.csv", row.names=FALSE) colClasses <- c("character", "Date", "character", "character", "numeric", "numeric") sql <- paste0( "select ", "date(", # [2] "substr(Date, 8, 4) || '-' || ", # [1] "substr(Date, 5, 2) || '-' || ", "substr(Date, 2, 2)), Long, Lat, Quality ", "from ff where Quality like '%oo%' and Long>177.129") ff <- file(description="df.csv", open="r") dat <- sqldf::read.csv.sql( sql=sql, colClasses=colClasses) close(ff) str(dat) as.Date(dat[,1]) dat[,3] Both sqlite and Postgres has a function substr you can call on strings like this.[5] I have a hunch this has always been possible in sql from way back ... The warning from sqldf about unused connections, might suggest file descriptor handling to be a bit crusty ... [3] The thing is, defining the second column as of type Date in colClasses happens to work, but it's still character when you check with str(dat) ... perhaps it has something to do with this info from [4]: as_tibble_row() converts a vector to a tibble with one row. The input must be a bare vector, e.g. vectors of dates are not supported yet. If the input is a list, all elements must have length one. [1] https://stackoverflow.com/questions/15563656/convert-string-to-date-in-sqlite [2] https://www.sqlite.org/lang_datefunc.html [3] https://groups.google.com/forum/#!topic/sqldf/mcQ_K_E--q8 [4] https://tibble.tidyverse.org/reference/as_tibble.html [5] https://www.sqlite.org/lang_corefunc.html#substr, https://www.postgresql.org/docs/9.1/functions-string.html, http://www.h2database.com/html/functions.html#substring -------------- next part -------------- A non-text attachment was scrubbed... Name: signature.asc Type: application/pgp-signature Size: 833 bytes Desc: not available URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20200719/f6c63baa/attachment.sig>
On 07/18/2020 01:38 PM, William Michels wrote:> Do either of the postings/threads below help? > > https://r.789695.n4.nabble.com/read-csv-sql-to-select-from-a-large-csv-file-td4650565.html#a4651534 > https://r.789695.n4.nabble.com/using-sqldf-s-read-csv-sql-to-read-a-file-with-quot-NA-quot-for-missing-td4642327.html > > Otherwise you can try reading through the FAQ on Github: > > https://github.com/ggrothendieck/sqldf > > HTH, Bill. > > W. Michels, Ph.D. > > > > On Sat, Jul 18, 2020 at 9:59 AM H <agents at meddatainc.com> wrote: >> On 07/18/2020 11:54 AM, Rui Barradas wrote: >>> Hello, >>> >>> I don't believe that what you are asking for is possible but like Bert suggested, you can do it after reading in the data. >>> You could write a convenience function to read the data, then change what you need to change. >>> Then the function would return this final object. >>> >>> Rui Barradas >>> >>> ?s 16:43 de 18/07/2020, H escreveu: >>> >>>> On 07/17/2020 09:49 PM, Bert Gunter wrote: >>>>> Is there some reason that you can't make the changes to the data frame (column names, as.date(), ...) *after* you have read all your data in? >>>>> >>>>> Do all your csv files use the same names and date formats? >>>>> >>>>> >>>>> Bert Gunter >>>>> >>>>> "The trouble with having an open mind is that people keep coming along and sticking things into it." >>>>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) >>>>> >>>>> >>>>> On Fri, Jul 17, 2020 at 6:28 PM H <agents at meddatainc.com <mailto:agents at meddatainc.com>> wrote: >>>>> >>>>> I have created a dataframe with columns that are characters, integers and numeric and with column names assigned by me. I am using read.csv.sql() to read portions of a number of large csv files into this dataframe, each csv file having a header row with columb names. >>>>> >>>>> The problem I am having is that the csv files have header rows with column names that are slightly different from the column names I have assigned in the dataframe and it seems that when I read the csv data into the dataframe, the column names from the csv file replace the column names I chose when creating the dataframe. >>>>> >>>>> I have been unable to figure out if it is possible to assign column names of my choosing in the read.csv.sql() function? I have tried various variations but none seem to work. I tried colClasses = c(....) but that did not work, I tried field.types = c(...) but could not get that to work either. >>>>> >>>>> It seems that the above should be feasible but I am missing something? Does anyone know? >>>>> >>>>> A secondary issue is that the csv files have a column with a date in mm/dd/yyyy format that I would like to make into a Date type column in my dataframe. Again, I have been unable to find a way - if at all possible - to force a conversion into a Date format when importing into the dataframe. The best I have so far is to import is a character column and then use as.Date() to later force the conversion of the dataframe column. >>>>> >>>>> Is it possible to do this when importing using read.csv.sql()? >>>>> >>>>> ______________________________________________ >>>>> R-help at r-project.org <mailto:R-help at r-project.org> mailing list -- To UNSUBSCRIBE and more, see >>>>> https://stat.ethz.ch/mailman/listinfo/r-help >>>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >>>>> and provide commented, minimal, self-contained, reproducible code. >>>>> >>>> Yes, the files use the same column names and date format (at least as far as I know now.) I agree I could do it as you suggest above but from a purist perspective I would rather do it when importing the data using read.csv.sql(), particularly if column names and/or date format might change, or be different between different files. I am indeed selecting rows from a large number of csv files so this is entirely plausible. >>>> >>>> Has anyone been able to name columns in the read.csv.sql() call and/or force date format conversion in the call itself? The first refers to naming columns differently from what a header in the csv file may have. >>>> >>>> >>>> [[alternative HTML version deleted]] >>>> >>>> ______________________________________________ >>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >>>> https://stat.ethz.ch/mailman/listinfo/r-help >>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >>>> and provide commented, minimal, self-contained, reproducible code. >> The documentation for read.csv.sql() suggests that colClasses() and/or field.types() should work but I may well have misunderstood the documentation, hence my question in this group. >> >> ______________________________________________ >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code.I had read the sqldf() documentation but was left with the impression that what I want to do is not easily doable.