Re: [R] change col types of a df/tbl_df
On Thu, Dec 10, 2015 at 1:47 PM, Giorgio Garziano <
giorgio.garzi...@ericsson.com> wrote:
> my_convert <- function(col) {
> v <- grep("[0-9]{2}.[0-9]{2}.[0-9]{4}", col);
> w <- grep("[0-9]+,[0-9]+", col)
> col2 <- col
> if (length(v) == length(col)){
> col2 <- as.Date(col, format="%d.%m.%y")
> } else if (length(w) == length(col)) {
> col2 <- as.numeric(gsub(",", "", col))
> }
> col2
> }
>
> myDf <- as.data.frame(lapply(myDf, my_convert), stringsAsFactors = FALSE)
>
> Sounds good. I will give a try,
Thank you
> --
> GG
>
>
> [[alternative HTML version deleted]]
>
> __
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Re: [R] change col types of a df/tbl_df
my_convert <- function(col) {
v <- grep("[0-9]{2}.[0-9]{2}.[0-9]{4}", col);
w <- grep("[0-9]+,[0-9]+", col)
col2 <- col
if (length(v) == length(col)){
col2 <- as.Date(col, format="%d.%m.%y")
} else if (length(w) == length(col)) {
col2 <- as.numeric(gsub(",", "", col))
}
col2
}
myDf <- as.data.frame(lapply(myDf, my_convert), stringsAsFactors = FALSE)
--
GG
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Re: [R] change col types of a df/tbl_df
On Thu, Dec 10, 2015 at 12:54 PM, Duncan Murdoch
wrote:
> On 10/12/2015 6:12 AM, arnaud gaboury wrote:
>
>> Here is a sample of my data frame, obtained with read_csv2 from readr
>> package.
>>
>> myDf <- structure(list(X15 = c("30.09.2015", "05.10.2015", "30.09.2015",
>>
>> "29.09.2015", "10.10.2015"), X16 = c("02.10.2015", "06.10.2015",
>> "01.10.2015", "01.10.2015", "13.10.2015"), X17 = c("Grains",
>> "Grains", "Grains", "Grains", "Grains"), X18 = c("Soyabeans",
>> "Soyabeans", "Soyabeans", "Soyabeans", "Soyabeans"), X19 = c("20,000",
>> "20,000", "20,000", "29,930", "26,000")), .Names = c("X15", "X16",
>> "X17", "X18", "X19"), class = c("tbl_df", "data.frame"), row.names = c(NA,
>> -5L))
>>
>> gabx@hortensia [R] str(myDf)
>> Classes ‘tbl_df’ and 'data.frame': 5 obs. of 5 variables:
>> $ X15: chr "30.09.2015" "05.10.2015" "30.09.2015" "29.09.2015" ...
>> $ X16: chr "02.10.2015" "06.10.2015" "01.10.2015" "01.10.2015" ...
>> $ X17: chr "Grains" "Grains" "Grains" "Grains" ...
>> $ X18: chr "Soyabeans" "Soyabeans" "Soyabeans" "Soyabeans" ...
>> $ X19: chr "20,000" "20,000" "20,000" "29,930" ...
>>
>> I want to change date to date class and numbers (X19) to numeric, and
>> keep the class of my object.
>>
>> This code works:
>>
>> myDf$X19 <- as.numeric(gsub(",", "", myDf$X19))
>> myDf$X15 <- as.Date(myDf$X15, format = "%d.%m.%Y"))
>> myDf$X16 <- as.Date(myDf$X16, format = "%d.%m.%Y"))
>>
>> Now, as I have more than 5 columns, this can be fastidious and slowing
>> code (?), even if I can group by type. Columns are only types of char,
>> num and Date, so it could be OK.
>>
>> I tried with lapply for the Date columns. It works BUT will place NA
>> in any columns with numbers as characters.
>> The reuslt will be this for X19: num NA NA NA NA NA NA NA NA NA NA ..
>>
>> How can I target my goal with something else than lapply or writing a
>> line for each type ?
>>
>
> I don't see how a function could reliably detect the types,
In fact, I only have 25 columns, so it is not difficult to list them in the
3 types: char, num and Date. No need of a function thus.
> but it might be good enough to use a regular expression, possibly just on
> the first line of the result. Once you've identified columns, e.g.
>
> numcols <- 19
> datecols <- c(15:16)
>
> etc, you can use lapply:
>
> myDf[,numcols] <- lapply(myDf[, numcools, drop=FALSE], function(x)
> as.numeric(gsub(",", "", x)))
>
> You can simplify myDf[,numcols] to myDf[numcols] if you want, but I think
> it makes it less clear.
Thank you.
>
>
> Duncan Murdoch
>
>
--
google.com/+arnaudgabourygabx
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Re: [R] change col types of a df/tbl_df
On 10/12/2015 6:12 AM, arnaud gaboury wrote:
Here is a sample of my data frame, obtained with read_csv2 from readr package.
myDf <- structure(list(X15 = c("30.09.2015", "05.10.2015", "30.09.2015",
"29.09.2015", "10.10.2015"), X16 = c("02.10.2015", "06.10.2015",
"01.10.2015", "01.10.2015", "13.10.2015"), X17 = c("Grains",
"Grains", "Grains", "Grains", "Grains"), X18 = c("Soyabeans",
"Soyabeans", "Soyabeans", "Soyabeans", "Soyabeans"), X19 = c("20,000",
"20,000", "20,000", "29,930", "26,000")), .Names = c("X15", "X16",
"X17", "X18", "X19"), class = c("tbl_df", "data.frame"), row.names = c(NA,
-5L))
gabx@hortensia [R] str(myDf)
Classes ‘tbl_df’ and 'data.frame': 5 obs. of 5 variables:
$ X15: chr "30.09.2015" "05.10.2015" "30.09.2015" "29.09.2015" ...
$ X16: chr "02.10.2015" "06.10.2015" "01.10.2015" "01.10.2015" ...
$ X17: chr "Grains" "Grains" "Grains" "Grains" ...
$ X18: chr "Soyabeans" "Soyabeans" "Soyabeans" "Soyabeans" ...
$ X19: chr "20,000" "20,000" "20,000" "29,930" ...
I want to change date to date class and numbers (X19) to numeric, and
keep the class of my object.
This code works:
myDf$X19 <- as.numeric(gsub(",", "", myDf$X19))
myDf$X15 <- as.Date(myDf$X15, format = "%d.%m.%Y"))
myDf$X16 <- as.Date(myDf$X16, format = "%d.%m.%Y"))
Now, as I have more than 5 columns, this can be fastidious and slowing
code (?), even if I can group by type. Columns are only types of char,
num and Date, so it could be OK.
I tried with lapply for the Date columns. It works BUT will place NA
in any columns with numbers as characters.
The reuslt will be this for X19: num NA NA NA NA NA NA NA NA NA NA ..
How can I target my goal with something else than lapply or writing a
line for each type ?
I don't see how a function could reliably detect the types, but it might
be good enough to use a regular expression, possibly just on the first
line of the result. Once you've identified columns, e.g.
numcols <- 19
datecols <- c(15:16)
etc, you can use lapply:
myDf[,numcols] <- lapply(myDf[, numcools, drop=FALSE], function(x)
as.numeric(gsub(",", "", x)))
You can simplify myDf[,numcols] to myDf[numcols] if you want, but I
think it makes it less clear.
Duncan Murdoch
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