density plot for different groups in the same dataframe

Question

I have a df with IDs and values and I would like to generate a density plot for every unique ID and check about the distributions if its normal or skewed.There are also NA values and i am not sure how to treat them. Should i just remove them and create the density plot? Also the range of the values between the IDs is different.

| ID       |  Values |
| -------- | ------- |
| F1       | 45      |
| F1       | 56      |
| F1       | NA      |
| F1       | 68      |
| F1       | 55      |
| F2       | 23      |
| F2       | 44      |
| F2       | 34      |
| F2       | NA      |
| F2       | NA      |
| F2       | 34      |
| F3       | 5055    | 
| F3       | 4567    |
| F3       | NA      | 
| F3       | 4789    |
| F3       | 5567    |
| F3       | 6002    |
| F4       | 9045    |
| F4       | 9500    | 
| F4       | 9760    |
| F4       | NA      |
| F4       | 9150    |

Please help as I am beginner in the visualizations

Answer 1

You don't need to remove the NAs, they are ignored in the plot. You have at most 5 values per ID in your dataset so a density plot is not so useful. So for your example above, we can take the log10 and try a density:

ggplot(df,aes(x = Values,y=ID)) + geom_jitter(width=0.1) + scale_x_log10()

A stripchart might be more useful:

ggplot(df,aes(x = Values,y=ID)) + geom_jitter(width=0.1) + scale_x_log10()