Ok, merging in this way the total number of rows of the new dataset is the
number of rows of the dataset "request".
Is it possible to obtain a new dataset with the number of rows of the
dataset "phone"?
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I tried to do using merge, I think now it works (anyway it is your worth), I
wrote:
df1<-read.csv("df1.csv",head=T)
attach(df1)
df2<-read.csv("df2.csv",head=T)
attach(df2)
join<-merge(df1,df2,by.x="name",by.y="name")
Is it correct? Coz I'm very frightened to lose datas or make mistakes
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Hi Ruri, sorry for my vagueness. The problem is not the order.
I tried to merge the datasets as you wrote. The result is that when I input:
table(phone)
The output is:
0
And this happens for all the variables.
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it doesn't work.
Find attached what I need explained in xls.
Thank you very very much!
http://r.789695.n4.nabble.com/file/n4622912/interweaving_of_2_datasets.xls
interweaving_of_2_datasets.xls
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I have two datasets, the first has this shape (each word is a column)
Name address phone .. ..
The second one has the following shape
Name request
I need a contingency table with for example phone and request.
The people registered in these datasets are present in both datasets, BUT in
the fi
I have a great dataset like this:
name colour ... ... ...
jerry red
pippo red
tom red
tom yellow
tom green
jessie orange
jessie red
bill yellow
kate red
henry green
..
..
I want to find out, in this great dat
I have a matrix like this
0.05 0.13 1.2 0 0 0 0 0 red
0 0 0 0 0 0 0 0 white
0 0.06 0 0 0 0 0 0 blue
If only 1 number in the first 8 columns is more than 0, in a new variable I
write 1, if they're all 0 or less, I write 0, so
0.05 0.13 1.2 0 0 0 0 0 red 1
0 0 0 0
I have this kind of matrix, with thousands of cases.
A 2 apple
A 2 peach
A 3 peach
B 1 pear
B 4 peach
B 4 beef
B 7 beef
C 1 peach
D 2 apple
D 5 peach
I have to distinguish, from the other rows, the rows with "peach" and this
is not a problem.
I also have to discriminate the rows with
8 matches
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