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()?