read.csv(file = 'path where csv is located in your computer')Importing Data in R
Comma-Seperated Values (CSV)
Warning
This tutorial assumes the data set is in working condition. That is we assume the default settings for read.csv. In some cases we may need to change the header, specify the field separator and more. See ?read.csv for further details and examples.
We will now import a csv file, to do this we will use the read.csv function. A simple template to follow is
An easy way to find the location of your data (or any file) is using the file.choose() function in R. file.choose() will bring up a file explorer window that allows you to interactively choose a file path to work with.
In your console, run the following command
file.choose()For example, after running the above command the births dataset is located in
[1] "/Users/toledo60/Desktop/Projects/ucla-stats13/data/births.csv"
Warning
Depending on your location and operating system the directory will be different
Therefore, to read the births data set I would copy/paste the directory of the csv location and run the following command
birth_dat <- read.csv(file = "/Users/toledo60/Desktop/Projects/ucla-stats13/data/births.csv") X Gender Premie weight Apgar1 Fage Mage Feduc Meduc TotPreg Visits Marital
1 1 Male No 116 9 28 34 6 3 2 10 Married
2 2 Male No 126 8 30 18 12 12 1 14 Unmarried
3 3 Male No 161 8 28 29 12 12 3 14 Married
4 4 Male No 133 9 26 23 8 9 3 10 Married
5 5 Female No 119 8 30 19 12 12 2 12 Unmarried
6 6 Male No 110 9 30 26 12 16 2 13 Unmarried
Racemom Racedad Hispmom Hispdad Gained Habit MomPriorCond BirthDef
1 White White Mexican Mexican 30 NonSmoker None None
2 White Unknown NotHisp Unknown 50 Smoker At Least One None
3 White White OtherHisp OtherHisp 65 NonSmoker None None
4 White White Mexican Mexican 8 NonSmoker None None
5 Black Unknown NotHisp Unknown 20 NonSmoker None None
6 Black Unknown NotHisp Unknown 32 NonSmoker None None
DelivComp BirthComp
1 None None
2 None None
3 At Least One None
4 At Least One None
5 None None
6 None NoneWe are not just limited to csv files, we can import data from Excel (in csv, XLSX, or txt format), SAS, Stata, SPSS, or others. A good reference to import various data formats can be found on datacamp r-data-import tutorial
Text File (TXT)
Next, we consider importing a .txt file. To do so we will use the read.table function instead of the read.csv function. For this example, we consider the ozone.txt file from our course website
A simple template to follow is
read.table(file = 'path where txt file is located in your computer')After running file.choose() on our console and locating the path in which we stored our data
file.choose()[1] "/Users/toledo60/Desktop/Projects/ucla-stats13/ucla/stats10/data/ozone.txt"we can copy/paste the path as follows
ozone_dat <- read.table(file = "/Users/toledo60/Desktop/Projects/ucla-stats13/data/ozone.txt",
header =TRUE)ozone_dat x y o3
1 -120.0258 34.4622 0.044
2 -119.7413 36.7055 0.081
3 -121.7333 36.4819 0.035
4 -119.2908 36.3325 0.080
5 -117.1289 32.8364 0.053You will notice we now used an additional argument header = TRUE in our read.table function. We use header=TRUE, whenever the text tile contains names of the variables as its first line.
If we forget to use header=TRUE, the first line of the text file will be treated as a row of the dataset and read.table will automatically create the variable names for us
wrong_ozone_dat <- read.table(file = "/Users/toledo60/Desktop/Projects/ucla-stats13/data/ozone.txt")wrong_ozone_dat V1 V2 V3
1 x y o3
2 -120.0258 34.4622 0.044
3 -119.7413 36.7055 0.081
4 -121.7333 36.4819 0.035
5 -119.2908 36.3325 0.08In the above example, read.table automatically create the variable names V1,V2,V3 for each column and the first row has values x,y,o3 (which is incorrect).
In conclusion, some text files do not have variable names in the first row and only contain the actual data. As a result, it is our responsibility to import the data in a suitable manner.