Presentation describing the merge function in R

Ashu Guru Author

03/13/2019 Added

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Presentation describing the merge function in R , by Ashu Guru, Univ of Nebraska Raikes School (5 mins)

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[00:00:00.280]Many time we have a scenario where we have two tables which have one common
[00:00:06.500]column and we like to join the 2 tables side by side.
[00:00:10.920]So for example, suppose we have a data in a table and one
[00:00:15.635]of them is stored in a file called merge CSV TXT and it looks like it has a column
[00:00:22.383]merge on attribute 1, attribute 2 and then it has a set of rows
[00:00:27.586]of values.
[00:00:29.040]Similarly, we have a second table which is stored in
[00:00:32.674]another file and in this case I'm saying it's in merge 2 CSV TXT.
[00:00:37.640]It has two columns merge on attribute 3 and the merge on column has the same
[00:00:44.163]column header in both the files and this is the column with which we will join
[00:00:50.857]these two tables side by side and it has values 100.1 and 900.1 and 800.3 and 2.
[00:00:59.240]One thing you want to notice that I have deliberately added two rows which have
[00:01:07.094]the same joining columns value in the second table.
[00:01:13.360]The reason I wanted to do that is just to include that in this tutorial as well.
[00:01:20.040]So we will know the behavior of R when we like to join tables based on a common
[00:01:26.163]column and what happens when there are values which are duplicated on the
[00:01:31.826]joining column and if there are missing ones as well.
[00:01:35.960]Because in this case in the first table we have a value of 10.
[00:01:40.102]25 in the joining column, but there is no 10.25 in the joint column.
[00:01:44.640]So we'll see the behaviour of R.
[00:01:48.360]So what I am going to do is as always I'm going to set the working directory to the
[00:01:54.828]folder which contains my input file.
[00:01:57.600]So it is in the folder which you see on screen and here is the file just to show
[00:02:05.791]that we have it in merge.
[00:02:13.480]So this is the first file I have merge on attribute 1,
[00:02:17.427]attribute 2 and the rows of values, separated.
[00:02:22.800]Then I have merge 2 again 2 columns, 3 values, 3 rows of values, separated.
[00:02:38.520]So the first step as always is to set the working directory.
[00:02:41.960]I am going to run this instruction.
[00:02:45.280]Next is I'm going to read the file merge dot CSV dot TXT.
[00:02:49.720]It has headers and the separator is in a variable called tabdata 1.
[00:02:55.720]So I'm going to run this instruction.
[00:02:57.800]Similarly, I'm going to read the second table from
[00:03:01.221]the CSV file in a variable called tabdata 2.
[00:03:05.120]Now we will use the command merge which takes an argument first table,
[00:03:10.919]the second table, and the common column with which we have
[00:03:15.738]to join them.
[00:03:17.480]Sorry.
[00:03:18.040]So I'm going to run this instruction and then I will print what is the value of
[00:03:24.173]the merge table.
[00:03:27.160]So what we see is that R was able to join the 2 tables because I do see that there
[00:03:33.026]is 1/3 column now attribute 3 in the merge table.
[00:03:37.240]And what I do also notice is that it only merges the rows which have common values
[00:03:46.848]in the joined column.
[00:03:49.760]So the join column has 100.1, 100.2, 100. 25, 100.3 and 100 .1 and 100.3.
[00:03:59.080]The common values in the two is 100.1, 100.1 and 100.3.
[00:04:03.480]So the join column will only have the values which are common in the 2 tables.
[00:04:11.560]What I also see is that since I had two values for 100.1 in the second table,
[00:04:19.020]it has actually repeated 100.1 twice.
[00:04:22.560]So I have 100.1, 20, 29 so 100.1, 20, 29 and then I have 100.1, 20, 28 so 100.1,
[00:04:32.905]20, 28.
[00:04:34.320]Then there is no 100. 2 in the second table,
[00:04:37.265]so skip that there is no 100. 25 in the second table.
[00:04:40.800]Skip that, there is 100. 3 in the second table,
[00:04:45.517]so that will be 100.3, 35, 30. 100.3, 35, 30 and then 2.

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Presentation describing the merge function in R

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