Question: I have a data frame,in which, two of the columns are Age and Income. I have clustered the data Using Kmeans. Now I want to plot between Age and Income distinguishing the data points based on Clusters (By Colours)

df

```
Age    Income    Cluster
20      10000     1
30      20000     2
40      25000     1
50      20000     2
60      10000     3
70      15000     3

```

.

```
plot(df$Age,df$Income)

```

I want to plot the datapoints between Age and Income and Each datapoint should be coloured based on clusters

Answer: 
You could use `ggplot()` for this:

```
ggplot() +
  geom_point(mapping = aes(x = Age, y = Income, color = Cluster))

```

Here it is creating the aesthetics based on the values in the data (x position of the point is based on age, y position on the income, and colour of the point on the variable "cluster").

You could also add this using base R, here's an example using the mtcars dataset...

```
plot(x = mtcars$wt, y = mtcars$mpg, col = mtcars$cyl)

```
I found one Using plot function

df

Age Income

20 10000  

30 20000  

40 25000  

50 20000  

60 10000  

70 15000 

clust <- kmeans(df,centers = 3) *# df without the last "Cluster" Column as in the Question*

plot(df,col=clust$cluster, color=TRUE,las=1,xlab ="Age",ylab="Income") *# df containing only Columns Age and Income.* *#Cluster is one of the components of Class Kmeans*

*If your data frame contains more than two Columns, subset it to the two Columns you want to plot between.*