hw02 ready for grading

[arthursunbao]

@vincenzocoia @gvdr @ksedivyhaley @JoeyBernhardt @mynamedaike @pgonzaleze @derekcho

[Maria815]

Hi Jason,
Good job on gapminder exploration. You clearly showed all the processes and use many functions to solve problems. Also filter, select and piping are well used. I would suggest trying optional questions to have more idea about ggplot. For the coding, I would suggest using a separate line for each aurgument/function, therefore it's easier to track back. Also good navigation in readme file. Very nicely done!

Regards,
Maria

[OliviaTabares]

Peer review assesment:
Hello Jason, you did a good work covering all the elements for the homework and making a repository that is easy to navigate, your code has useful annotations that reveal your process, although a more detailed process report might be useful to address problems encountered.
some small details:

• year is not a categorical variable, it is a quantitative (although discrete in this case) one, categorical variables are those that take on values that are labels or categories, such as "red" "blue", "male", "female" and in the case of gapminder that would be the country and the continent
• It might have been useful to explore different data using the dplyr function as you are exploring what you have already plotted in the previous graph.

[mynamedaike]

Hello @arthursunbao ,

1. Smell test the data
   You answered all the questions and got the number of variables and observations in more than one way. You should also have used class() to each variable, then you would have seen how the results are different from using typeof().

2. Explore individual variables
   You explored year and lifeExp using functions like summary(), table() and hist(). I think it is better to choose a more typical categorical variable like continent to explore.

3. Explore various plot types
   You explored several kinds of plots such as histogram, scatter plot, and line plot.

4. Use filter(), select() and %>%
   Yes. You used all of these. I suggest you arrange your code in a more stylish way. For example:

ggplot(gapminder %>% filter(country == "Canada"), aes(x = year, y = lifeExp)) + geom_line() + geom_point()

should be

gapminder %>% 
  filter(country == "Canada") %>% 
  ggplot(aes(x = year, y = lifeExp)) +
  geom_line() +
  geom_point()

5. Bonus
   No bonus task has been done.

6. Report your process
   You reported your reflections about this assignment briefly.

Good job. Your repository is well organized. The markdown file is easy to find. You explored several kinds of plots and used filter(), select() and %>% to tidy the data. Try to explore more plot types and dplyr functions such as mutate(), group_by(), summarize().