[R] Antwort: RE: Merging variables
G.Maubach at weinwolf.de
G.Maubach at weinwolf.de
Tue Jun 7 08:35:18 CEST 2016
Hi Petr,
I would like to describe the data situation in brief:
I have an business warehouse dataset (referred to as BW data) containing
sales and an ERP customer master data dataset with additional information
(referred to as ERP data). Though customer IDs and customer names are
identical due to the fact that the business warehouse data is derived from
the ERP data. Due to selection criteria the BW data contains slightly
more customers than the ERP data. So customer names and all other
information is missing in the ERP data for some cases of the BW data. If
I merge those by customer ID variable customer names are duplicated using
customer.x and customer.y as variable names.
As both fields contains the same contents I would have expected R to merge
this into one variable, e. g. customer. But this is not the case.
Can I adjust the below given merge statement - which looks almost the same
in my script - that R does the merge of the variables if they are
identical automatically?
This is my code using left join:
-- cut --
ds_merge1 <- merge(x = ds_bw_customer_4_match, y =
ds_erp_customer_4_match,
by.x = "CustID", by.y = "CustID",
all.x = TRUE, all.y = FALSE)
-- cut --
Kind regards
Georg
Von: PIKAL Petr <petr.pikal at precheza.cz>
An: Michael Dewey <lists at dewey.myzen.co.uk>, "G.Maubach at weinwolf.de"
<G.Maubach at weinwolf.de>, "r-help at r-project.org" <r-help at r-project.org>,
Datum: 06.06.2016 17:04
Betreff: RE: [R] Merging variables
Hi Michael
it is simple
set.seed(111)
let=sample(letters[1:10],6, replace=T)
dat1<-data.frame(let=let, customer=sample(1:10,6, replace=T))
let=sample(letters[1:10],6, replace=T)
dat2<-data.frame(let=let, customer=sample(1:10,6, replace=T))
merge(dat1, dat2, by.x="let", by.y="let", all=T)
Of course you could add customer variable to by parameter but sometimes it
is necessary to leave it out. When you have two sets of analytical results
and you have 2 variables operator but you want to merge those sets e.g. by
date/hour of analysis.
Regards
Petr
> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Michael
> Dewey
> Sent: Monday, June 6, 2016 3:46 PM
> To: G.Maubach at weinwolf.de; r-help at r-project.org
> Subject: Re: [R] Merging variables
>
> X-Originating-<%= hostname %>-IP: [217.155.205.190]
>
> Dear Georg
>
> I find it a bit surprising that you end up with customer.x and
customer.y. Can
> you share with us a toy example of two data.frames which exhibit this
> behaviour?
>
> On 06/06/2016 13:29, G.Maubach at weinwolf.de wrote:
> > Hi All,
> >
> > I merged two datasets:
> >
> > ds_merge1 <- merge(x = ds_bw_customer_4_match, y =
> > ds_zww_customer_4_match,
> > by.x = "customer", by.y = "customer",
> > all.x = TRUE, all.y = FALSE)
> >
> > R created a new dataset with the variables customer.x and customer.y.
> > I would like to merge these two variable back together. I wrote a
> > little function (code can be run) for it:
> >
> > -- cut --
> >
> > customer.x <- c("Miller", "Smith", NA, "Bird", NA)
> > customer.y <- c("Miller", NA, "Doe", "Fish", NA)
> > ds_test <- data.frame(customer.x, customer.y, stringsAsFactors =
> > FALSE)
> >
> > t_merge_variables <-
> > function(dataset,
> > var1,
> > var2,
> > merged_var) {
> >
> > # Initialize
> > dataset[[merged_var]] = rep(NA, nrow(dataset))
> > dataset[["mismatch"]] = rep(NA, nrow(dataset))
> >
> > for (i in 1:nrow(dataset)) {
> >
> > # Check 1: var1 missing, var2 missing
> > if (is.na(dataset[[i, var1]]) &
> > is.na(dataset[[i, var2]])) {
> > dataset[["mismatch"]] <- 1 # var1 & var2 are missing
> >
> > # Check 2: var1 filled, var2 missing
> > } else if (!is.na(dataset[[i, var1]]) &
> > is.na(dataset[[i, var2]])) {
> > dataset[[i, merged_var]] <- dataset[[i, var1]]
> > dataset[["mismatch"]] <- 0
> >
> > # Check 3: var1 missing, var2 filled
> > } else if (is.na(dataset[[i, var1]]) &
> > !is.na(dataset[i, var2])) {
> > dataset[[i, merged_var]] <- dataset[[i, var2]]
> > dataset[["mismatch"]] <- 0
> >
> > # Check 4: var1 == var2
> > } else if (dataset[[i, var1]] == dataset[[i, var2]]) {
> > dataset[[i, merged_var]] <- dataset[[i, var1]]
> > dataset[["mismatch"]] <- 0
> >
> > # Leftover: var1 != var2
> > } else {
> > dataset[[i, merged_var]] <- NA
> > dataset[["mismatch"]] <- 2 # var1 != var2
> > } # end if
> > } # end for
> > return(dataset)
> > }
> >
> > ds_var_merge1 <- t_merge_variables(dataset = ds_test,
> > var1 = "customer.x",
> > var2 = "customer.y",
> > merged_var = "customer")
> >
> > ds_var_merge1
> >
> > -- cut --
> >
> > It is executed without error but delivers the wrong values in the
> > variable "mismatch". This variable is always 1 although it should be
> > NA, 1 or 2 respectively.
> >
> > Can you tell me why the variable is not correctly set?
> >
> > Kind regards
> >
> > Georg
> >
> > ______________________________________________
> > 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.
> >
>
> --
> Michael
> http://www.dewey.myzen.co.uk/home.html
>
> ______________________________________________
> 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.
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