Page 212 - Data Science class 11
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3. my var <- " Sapna"
Because is a space in between two words.
4. _my_var <- " Sapna"
Because it starts with underscore. See rule 1.
5. my_v@ar <- " Sapna"
Because it contains a special character @.
6. TRUE <- " Sapna"
Because it is a reserved word.
7. var_name%
Invalid because it contains the character ‘%’. Only dot(.) and underscore allowed.
8. 2var_name
Invalid as it starts with a number
9. .2var_name
Invalid as the starting dot is followed by a number.
10. _var_name
Invalid as it starts with _ which is not valid.
6.5 oBjects in r Programming
In contrast to other programming languages like C and Java, in R, the variables are not declared as some data type.
The variables are assigned as R-objects and the data type of the R-object becomes the data type of the variable. There
are many types of R-objects. The most frequently used ones are:
• Vectors
• Lists
• Matrices
• Arrays
• Factors
• Data Frames
You will be introduced to all these objects a little later.
The simplest of these objects is the vector object.
6.6 Vectors
Vectors are the most basic data objects. A vector is a basic data structure that plays an important role in R programming.
In R, a sequence of elements that share the same data type is known as a vector. A vector is a combination of multiple
values (numeric, character, or logical) in the same object. In this case, you can have numeric vectors, character
vectors, or logical vectors.
The R manual defines a vector as "a single entity consisting of a collection of things." A collection of numbers, for
example, is a numeric vector—the first five integer numbers form a numeric vector of length 5.
210 Touchpad Data Science-XI

