How to read a table in R

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Reading a table in R is quite straight-forward. We are going to read a table from the web and also one locally.

If you have come across a .dat file and want to import that table into R you’ll find this to be incredibly easy compared to other imports.

We will use a Princeton dataset, get the location of the file and use the function read.table.


> tableTest <- read.table("http://data.princeton.edu/wws509/datasets/effort.dat")
> tableTest
               setting effort change
Bolivia             46      0      1
Brazil              74      0     10
Chile               89     16     29
Colombia            77     16     25
CostaRica           84     21     29
Cuba                89     15     40
DominicanRep        68     14     21
Ecuador             70      6      0
ElSalvador          60     13     13
Guatemala           55      9      4
Haiti               35      3      0
Honduras            51      7      7
Jamaica             87     23     21
Mexico              83      4      9
Nicaragua           68      0      7
Panama              84     19     22
Paraguay            74      3      6
Peru                73      0      2
TrinidadTobago      84     15     29
Venezuela           91      7     11

The above took the table and imported and now we can utilize the data in many different ways. We will get into evaluating and utilizing data more in the future, but next we will show you how to take your own table and import that data into R locally.

We created a generic table file like this:


T B D
1 2 3
4 5 6

We saved this file from our text editor as a tbd.dat. Then saved it to our working R directory. With a similar command as before we were able to import with the following:


> testTable2 = read.table("tbd.dat")
> testTable2
  V1 V2 V3
1  T  B  D
2  1  2  3
3  4  5  6

Now lets say we want to name our headers we would have imported the table this way:


> testTable3 = read.table("tbd.dat", col.names = c("A", "B", "C"))
> testTable3
  A B C
1 T B D
2 1 2 3
3 4 5 6

Above we set the col.names with the associated A, B, C titles and were able to label all of our columns and that is it.

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