We can use

**dist**function in R to calculate distance matrix with Manhattan method - which simply sum the differences of points observed.

Let's follow the examples below to understand how to use it. Along the example, we will use data frame variable named

**datatocalculate**.

> datatocalculate <- data.frame( x = c(3, 1), y = c(2, 4) )

> datatocalculate

x y

1 3 2

2 1 4

Now, let's calculate the distance matrix

**.**

> dist(datatocalculate, method="manhattan")

1

2 4

The calculated distance from 1 to 2 is 4, comes from the following formula:

|1-3| + |4-2|

|-2| + |2|

2 + 2

4

We will modify

**datatocalculate**variable with the following new values.

> datatocalculate <- data.frame( x = c(3, 2, 1), y = c(2, 4, 8) )

> datatocalculate

1 3 2

2 2 4

3 1 8

Calculate the distance matrix again.

> dist(datatocalculate, method="manhattan")

2 3

3 8 5

The calculated distance from 1 to 2 is 3. It is a result of the following calculation:

|2-3| + |4-2|

|-1| + |2|

1 + 2

3

The calculated distance from 1 to 3 is 8. It is a result of the following calculation:

|1-3| + |8-2|

|-2| + |6|

2 + 6

8

The calculated distance from 2 to 3 is 5. It is a result of the following calculation:

|1-2| + |8-4|

|-1| + |4|

1 + 4

5

**dist**function with Manhattan method in R.

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