Read Csv Line by Line in C
R scan Function (v Example Codes) | Read Text or CSV File Line by Line
In this article, I'll explain how to utilise the browse function to read data into R. Let's first have a expect at the basic R syntax and the definition of browse():
Bones R Syntax:
browse( "data.txt", what = "character" )
browse("data.txt", what = "character")
Definition:
The scan function reads information into a vector or listing from a file or the R panel.
Below, I'll show you five examples for the application of the scan role in R. So let's get started…
Example ane: Scan Text into R
Typically, the scan function is applied to text files (i.due east. txt format). Allow's therefore create such a text file on our computers:
First, nosotros are going to create an case data frame in R:
data <- data. frame (x1 = c( 4, four, 1, ix ), # Create example information.frame x2 = c( one, 8, 4, 0 ), x3 = c( five, 3, 5, 6 ) ) data # Impress information to RStudio panel # x1 x2 x3 # 4 1 5 # four eight three # one 4 5 # 9 0 6
information <- data.frame(x1 = c(four, iv, 1, 9), # Create example data.frame x2 = c(1, 8, 4, 0), x3 = c(5, 3, v, six)) data # Impress data to RStudio console # x1 x2 x3 # 4 1 v # 4 8 iii # one 4 5 # 9 0 6
Our case data contains three columns and four rows with numeric values. Now, allow's write this data frame as txt file to our computer:
write. table (information, # Write data as txt file to directory file = "data.txt", row. names = Fake )
write.table(data, # Write data as txt file to directory file = "data.txt", row.names = FALSE)
You lot can check if everything worked well by going to the post-obit directory:
getwd( ) # Become currently used directory "C:/Users/Your Path..."
getwd() # Get currently used directory "C:/Users/Your Path..."
In the directory, you should have a txt-file with the proper noun data.txt.
Now we can apply the scan office to read this text file into R:
data1 <- scan( "data.txt", what = "character" ) # Utilise scan part to txt file data1 # Print scan output to RStudio panel # [1] "x1" "x2" "x3" "4" "1" "5" "4" "viii" "3" "1" "4" "5" "9" "0" "vi"
data1 <- browse("data.txt", what = "character") # Utilize scan part to txt file data1 # Print scan output to RStudio panel # [ane] "x1" "x2" "x3" "4" "1" "v" "4" "8" "iii" "one" "four" "5" "9" "0" "6"
Equally you tin can meet, the previous code created a vector, which contains all values of our data frame (including cavalcade names).
So what if we want to read the information in a handier format? Continue on reading…
Example ii: Browse Text Data as List
The scan command also allows u.s. to read information as into a listing. With the following R code, we are creating a listing with 3 list elements. Each of the list elements contains one cavalcade of our original information frame (i.due east. nosotros scan the data file line by line):
data2 <- scan( "data.txt", what = listing( "", "", "" ) ) # Read txt file into list data2 # Print browse output to RStudio console # [[1]] # [1] "x1" "4" "four" "i" "nine" # # [[2]] # [1] "x2" "1" "8" "4" "0" # # [[3]] # [1] "x3" "5" "3" "v" "half dozen"
data2 <- browse("data.txt", what = listing("", "", "")) # Read txt file into list data2 # Impress scan output to RStudio panel # [[1]] # [1] "x1" "four" "4" "1" "9" # # [[2]] # [1] "x2" "ane" "8" "4" "0" # # [[3]] # [1] "x3" "v" "3" "v" "vi"
Notation: The column names are kept again. So what if we want to get rid of them? That's what I'grand going to show you adjacent.
Example three: Skip Lines with Scan Function
The scan functions provides many additional specifications – And one of them is the skip option. The skip choice allows to skip the first n lines of the input file. Since the cavalcade names are usually the starting time input lines of a file, we can just skip them with the specification skip = 1:
data3 <- scan( "information.txt", skip = 1 ) # Skip first line of txt file data3 # Print scan output to RStudio console # [ane] 4 one 5 4 8 3 1 4 5 9 0 6
data3 <- scan("data.txt", skip = one) # Skip starting time line of txt file data3 # Print browse output to RStudio console # [one] iv 1 five 4 8 3 ane 4 5 9 0 6
Annotation: Of crusade we could skip even more than lines, in instance we are not interested in the first n rows of our data.
Example 4: Browse Excel CSV File
So far, nosotros have only read txt files into R. However, based on the scan role we can besides read many other file formats. Let's create a csv file for the side by side case:
write. table (data, # Write data as csv file to directory file = "information.csv", row. names = FALSE )
write.table(data, # Write data equally csv file to directory file = "data.csv", row.names = FALSE)
If yous get to your currently used directory, there should be a file with the proper noun data.csv.
Nosotros tin now utilize the scan function to this csv file as we did earlier:
data4 <- scan( "data.csv", what = "grapheme" ) # Apply browse function to csv file data4 # Print scan output to RStudio console # [one] "x1" "x2" "x3" "4" "ane" "5" "4" "8" "3" "1" "four" "five" "9" "0" "vi"
data4 <- browse("data.csv", what = "character") # Apply browse role to csv file data4 # Print browse output to RStudio console # [1] "x1" "x2" "x3" "four" "i" "5" "4" "8" "3" "1" "4" "5" "nine" "0" "6"
As you can encounter: Exactly the same output every bit in Case i.
Instance v: Scan RStudio Console
Some other useful functionality of scan is that the function is able to read input from the RStudio console. In social club to do that, we first demand to execute the following line of code:
data5 <- scan( "" ) # Browse RStudio console input
data5 <- browse("") # Scan RStudio console input
And and so we can write whatsoever input to the RStudio panel, e.yard.:
If we now impress data5, we get exactly the input that nosotros have written to the panel before:
data5 # Print scan output to RStudio console # v 7 xx 8 13 2 2 2 5
data5 # Print browse output to RStudio console # 5 7 xx 8 13 2 2 ii 5
Video: Alternatives to the scan Function
In general, there are many dissimilar ways to read data into R. If you want to read a structured csv file, the almost common functions are read.csv and read.table. If you want to read (unstructured) text data, and so you could also have a look at functions such as readLines, n.readLines, and readline.
Furthermore, yous could too accept a look at the following video of the Docworld Academy YouTube aqueduct. In the video, the speaker explains how to use the readline function in a live R programming example. Have fun with the video and let me know in the comments, in case you have further questions or any feedback on the tutorial.
Farther Reading
- R Error in scan: Line 1 did non accept Ten Elements
- readLines, n.readLines & readline R Functions
- Listing of Useful R Functions
- The R Programming Linguistic communication
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Source: https://statisticsglobe.com/r-scan-function-example
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