Merging dataframes

Thanks - Peter, Eivind, Rui


Sorry, I perhaps could not explain it properly in the first go.

Trying to simplify it here with an example - Say I have two dataframes as
below that are NOT equally-sized data frames (i.e., number of columns are
different in each table):



Table_A:

Email             Name                   Phone

abc at gmail.com   John Chan         0909

bcd at yahoo.com   Tim Ma                    89089

......



Table_B:

Email                     Name                 Sex        Phone

abc at gmail.com    John Chan            M                 0909

khn at hotmail.com           Rosy  Kim               F                   7779

.....



Now, I have used -

merge (Table_A, Table_B, by="Email", all = FALSE))



- to find only the rows that match from these data frames - based on Email
as primary key.



Further, I am also interested (using "Email" as the common key) which rows
from Table_A did not match with Table_B.

I am not sure how to do this here.

Thanks and regards,
Chintanu



On Tue, May 1, 2018 at 8:48 PM, Rui Barradas <ruipbarradas at sapo.pt> wrote:

Hello,

Is it something like this that you want?

x <- data.frame(a = c(1:3, 5, 5:10), b = c(1:7, 7, 9:10))
y <- data.frame(a = 1:10, b = 1:10)

which(x != y, arr.ind = TRUE)


Hope this helps,

Rui Barradas


On 5/1/2018 11:35 AM, Chintanu wrote:

Hi,


May I please ask how I do the following in R. Sorry - this may be trivial,
but I am struggling here for this.



For two dataframes (A and B), I wish to identify (based on a primary
key-column present in both A & B) -

1. Which records (rows) of A did not match with B, and



2. Which records of B did not match with A ?



I came across a setdt function while browsing, but when I tried it, it
says
- Could not find function "setdt".



Overall, if there is any way of doing it (preferably in some simplified
way), please advise.


Many thanks in advance.


regards,

Tito

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Hi,

I'll coded your example into R code:

Table_A <- c('abc at gmail.com', 'John Chan', '0909')
Table_A <- rbind(Table_A, c('bcd at yahoo.com', 'Tim Ma', '89089'))
colnames(Table_A) <- c('Email', 'Name', 'Phone')
Table_A

Table_B <- c('abc at gmail.com', 'John Chan', 'M', '0909')
Table_B <- rbind(Table_B, c('khn at hotmail.com', 'Rosy  Kim', 'F', '7779'))
colnames(Table_B) <- c('Email', 'Name', 'Sex', 'Phone')
Table_B

Did you have a look at this one?
Table_C <- merge (Table_A, Table_B, by="Email", all = TRUE)
Table_C[is.na(Table_C$Name.y),]
Table_C[is.na(Table_C$Name.x),]

Table_C contains all data from Table_A and Table_B. The key.x is NA if
the row comes from Table_B and key.y is NA if the row comes from Table_A.

Best, Robin


On 05/02/2018 11:38 AM, Chintanu wrote:

Thanks - Peter, Eivind, Rui


Sorry, I perhaps could not explain it properly in the first go.

Trying to simplify it here with an example - Say I have two dataframes as
below that are NOT equally-sized data frames (i.e., number of columns are
different in each table):



Table_A:

Email             Name                   Phone

abc at gmail.com   John Chan         0909

bcd at yahoo.com   Tim Ma                    89089

......



Table_B:

Email                     Name                 Sex        Phone

abc at gmail.com    John Chan            M                 0909

khn at hotmail.com           Rosy  Kim               F                   7779

.....



Now, I have used -

merge (Table_A, Table_B, by="Email", all = FALSE))



- to find only the rows that match from these data frames - based on Email
as primary key.



Further, I am also interested (using "Email" as the common key) which rows
from Table_A did not match with Table_B.

I am not sure how to do this here.

Thanks and regards,
Chintanu



On Tue, May 1, 2018 at 8:48 PM, Rui Barradas <ruipbarradas at sapo.pt> wrote:

Hello,

Is it something like this that you want?

x <- data.frame(a = c(1:3, 5, 5:10), b = c(1:7, 7, 9:10))
y <- data.frame(a = 1:10, b = 1:10)

which(x != y, arr.ind = TRUE)


Hope this helps,

Rui Barradas


On 5/1/2018 11:35 AM, Chintanu wrote:

Hi,


May I please ask how I do the following in R. Sorry - this may be trivial,
but I am struggling here for this.



For two dataframes (A and B), I wish to identify (based on a primary
key-column present in both A & B) -

1. Which records (rows) of A did not match with B, and



2. Which records of B did not match with A ?



I came across a setdt function while browsing, but when I tried it, it
says
- Could not find function "setdt".



Overall, if there is any way of doing it (preferably in some simplified
way), please advise.


Many thanks in advance.


regards,

Tito

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--
Dr. Robin Haunschild
Max Planck Institute
for Solid State Research
Heisenbergstr. 1
D-70569 Stuttgart (Germany)
phone: +49 (0) 711-689-1285
fax:   +49 (0) 711-689-1292
email: R.Haunschild at fkf.mpg.de
http://www.fkf.mpg.de/ivs