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
>
> Às 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 <age...@meddatainc.com 
>>> <mailto:age...@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@r-project.org <mailto:R-help@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@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@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.

Reply via email to