Entering Data

Entering Data

Source: Datalab, https://www.youtube.com/watch?v=bXdMQ-8ZDBg
This work is licensed under a Creative Commons Attribution 3.0 License.

How to Manually Enter Raw Data in R?

This article will discuss manually entering raw data in the R Programming Language. In the R Language, we work with loads of different datasets by importing them through a variety of file formats. But Sometimes, we need to enter our own raw data in the form of a character vector, a data frame, or a matrix. Multiple methods exist to enter the raw data in the R Language manually.

Enter data as a vector

To enter data as a vector in the R Language, we use the combine function i.e. c(). The c() function is a generic function that combines its arguments to form a vector. All arguments are coerced to a common type. To create a numeric vector we pass numbers as arguments to the c() function. To create a character vector we pass the strings or characters as arguments to the c() function.

Syntax: sample_vector <- c( data1, data2, ….. , datan )

where: data1, data2…: determines the numeric values that comprise the vector.

Example: Demonstrating basic character and numeric vectors.

R

# create numeric vector
numeric <- c(1,2,3,4,5)
  
# create character vector
character <- c("geeks", "for", "geeks")
  
# print vectors and their class
print("Character vector:")
character
print("Class:")
class(character)
print("Numeric vector:")
numeric
print("Class:")
class(numeric)

Output:

Character vector:
"geeks" "for"   "geeks"
Class:
"character"
Numeric vector:
1 2 3 4 5
Class:
"numeric"

Enter data as a data frame

To enter data as a data frame in the R Language, we use the data.frame() function. The data.frame() function creates data frames that are tightly coupled collections of variables. These data frames are widely used as the fundamental data structure in the R Language. A single data frame can contain different vectors of different classes together thus it becomes one data structure for all the needs.

Syntax:

data_frame <- data.frame( column_name1 = vector1, column_name2 = vector2 )

where,

• column_name1, column_name2: determines the name for columns in data frame
• vector1, vector2: determines the data vector that contain data values for data frame columns.

Example: Basic data frame that contains one numeric vector and one character vector.

R

# create data frame
data_frame <- data.frame( id = c(1,2,3),
                          name = c("geeks", "for", 
                                   "geeks") )
  
# print dataframe, summary and its class 
print("Data Frame:")
data_frame
print("Class:")
class(data_frame)
print("Summary:")
summary(data_frame)

Output:

Data Frame:
 id  name
1  1 geeks
2  2   for
3  3 geeks
Class:
"data.frame"
Summary:
      id          name          
Min.   :1.0   Length:3          
1st Qu.:1.5   Class :character  
Median :2.0   Mode  :character  
Mean   :2.0                      
3rd Qu.:2.5                      
Max.   :3.0 

Enter data as a matrix

To enter data as a matrix in the R Language, we create all the columns of the matrix as a vector and then use the column binding function that is cbind() to merge them together into a matrix. The cbind() function is a merge function that combines two data frames or vectors with the same number of rows into a single data frame.

Syntax: mat <- cbind( col1, col2 )

where, col1, col2: determines the column vectors that are to be merged to form a matrix.

Example:

Here, is a basic 3X3 matrix in the R Language made using the cbind() function.

R

# create 3 column vectors with 3
# rows each for a 3X3 matrix
col1 <- c(1,2,3)
col2 <- c(4,5,6)
col3 <- c(7,8,9)
  
# merge three column vectors into a matrix
mat <- cbind(col1, col2, col3)
  
# print matrix, its class and summary
print("Matrix:")
mat
print("Class:")
class(mat)
print("Summary:")
summary(mat)

Matrix:
    col1 col2 col3
[1,]    1    4    7
[2,]    2    5    8
[3,]    3    6    9
Class:
"matrix" "array" 
Summary:
     col1          col2          col3    
Min.   :1.0   Min.   :4.0   Min.   :7.0  
1st Qu.:1.5   1st Qu.:4.5   1st Qu.:7.5  
Median :2.0   Median :5.0   Median :8.0  
Mean   :2.0   Mean   :5.0   Mean   :8.0  
3rd Qu.:2.5   3rd Qu.:5.5   3rd Qu.:8.5  
Max.   :3.0   Max.   :6.0   Max.   :9.0