How do I explain the relationship between Health and Weight? I have two columns in my dataset:  Health and Weight,  both being of numeric type:

    Health&lt;-number of days when health is not good,
    Weight&lt;-weight 


All I want to check if there  is a relationship between Health and Weight. In other words, does a Weight increase yield an increase of the number of days  where Health is not good, or the  converse?  I just want to check the relation between those two columns in dataset by plotting some graphs. 

Here my sample dataset: 

| Health     | Weight      | 
|:-----------|------------:|
| 0          |      30     |        
| 3          |      63     |        
| 2          |      31     |          
| 10         |      169    |            
| 1          |      9      |    
|0           |     139     |
Suggestion

You could bin the 'Health' vector to make a categorical variable (ideally consisting of similar number of observations, for example : 2-bin would be median-split of 'high' and 'low', 3-bin would be tertiles of 'high', 'medium' and 'low', and so on), and then do box plots of 'Weight' per bin. You might see that the bin of 'low' is different from the bin of 'high'. 
The number of bins you choose depends on the distribution of the 'Health' variable and you can play around with that.

Implementation

library(dplyr) # for modifying datasets 
library(ggplot2) # for plotting 
library(magrittr) # for piping
stackodato &lt;- data.frame("Health" = sample(0:10, 10), "Weight" = sample(0:200, 10)) # creating a pseudo dataset

stackodato %&gt;% 
mutate(binnedHealth = factor(dplyr::ntile(Health, 2), labels=c("low", "high"))) %&gt;% # add "binnedHealth" column which has the "Health" variable categorized into two factors : "high" and "low"
ggplot()+geom_boxplot(aes(x=binnedHealth, y=Weight)) # boxplot showing the distribution of "Weight" split by the "binnedHealth" factor




You can also try this : 

stackodato %&gt;% mutate(binnedHealth = factor(dplyr::ntile(Health, 2), labels=c("low", "high"))) %&gt;% ggplot()+geom_boxplot(aes(x=Health, y=Weight, group = binnedHealth))