Update comparing_numeric_values.md

Author: bradleyboehmke

numbers/comparing_numeric_values.md

@@ -8,11 +8,10 @@ There are multiple ways to compare numeric values and vectors.  This includes [l
 
 <br>
 
-{#numeric_comparison}
-## Comparison Operators
+## Comparison Operators {#numeric_comparison}
 The normal binary operators allow you to compare numeric values and provides the answer in logical form:
 
-{linenos=off}
+
 ```r
 x < y     # is x less than y
 x > y     # is x greater than y
@@ -24,7 +23,7 @@ x != y    # is x not equal to y
 
 These operations can be used for single number comparison:
 
-{linenos=off}
+
 ```r
 x <- 9
 y <- 10
@@ -35,7 +34,7 @@ x == y
 
 and also for comparison of numbers within vectors:
 
-{linenos=off}
+
 ```r
 x <- c(1, 4, 9, 12)
 y <- c(4, 4, 9, 13)
@@ -46,7 +45,7 @@ x == y
 
 Note that logical values `TRUE` and `FALSE` equate to 1 and 0 respectively.  So if you want to identify the number of equal values in two vectors you can wrap the operation in the `sum()` function:
 
-{linenos=off}
+
 ```r
 # How many pairwise equal values are in vectors x and y
 sum(x == y)    
@@ -55,18 +54,19 @@ sum(x == y)
 
 If you need to identify the location of pairwise equalities in two vectors you can wrap the operation in the `which()` function:
 
-{linenos=off}
+
 ```r
 # Where are the pairwise equal values located in vectors x and y
 which(x == y)    
 ## [1] 2 3
 ```
 
-{#numeric_exact}
-### Exact Equality
+<br>
+
+## Exact Equality {#numeric_exact}
 To test if two objects are exactly equal:
 
-{linenos=off}
+
 ```r
 x <- c(4, 4, 9, 12)
 y <- c(4, 4, 9, 13)
@@ -75,7 +75,7 @@ identical(x, y)
 ## [1] FALSE
 ```
 
-{linenos=off}
+
 ```r
 x <- c(4, 4, 9, 12)
 y <- c(4, 4, 9, 12)
@@ -84,10 +84,12 @@ identical(x, y)
 ## [1] TRUE
 ```
 
-### Floating Point Comparison
+<br>
+
+## Floating Point Comparison {#numeric_near}
 Sometimes you wish to test for 'near equality'.  The `all.equal()` function allows you to test for equality with a difference tolerance of 1.5e-8.
 
-{linenos=off}
+
 ```r
 x <- c(4.00000005, 4.00000008)
 y <- c(4.00000002, 4.00000006)
@@ -98,7 +100,7 @@ all.equal(x, y)
 
 If the difference is greater than the tolerance level the function will return the mean relative difference:
 
-{linenos=off}
+
 ```r
 x <- c(4.005, 4.0008)
 y <- c(4.002, 4.0006)