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
Às 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
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()?
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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.
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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.
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