hw02 ready for grading

[susannaelsie]

@vincenzocoia @gvdr @ksedivyhaley @joeybernhardt @mynamedaike @pgonzaleze @derekcho

Link to hw02 folder Link to hw02.md file Latest commit

[yuanjisun]

Hello Susanna,

I appreciate your efforts in hw02 and it is really a good homework (check plus). Below are my comments.

General Issues (check plus) Pros

1. Named the repo and files correctly.
2. Well organized and look great.
3. Added a link to the hw02 in the main README. There is also a README with detailed information of this homework.

Cons Not found yet. I don't think there is any con in this part.

Report Process (check plus) Pros

1. Very detailed information about how this homework is finished.
2. Mentioned what problems you had and provided very useful resources in learning R programming. You are a great learner.
3. Used citations. This is very important in academic research. You already realize that.

Cons I really cannot find any cons.

Main Part of the Homework (check plus) Pro

1. Confirmed that gapminder is both a data.frame and a list. This is great!
2. Used R codes for each question.
3. In some questions, you used more than one method to give the answer. This is really helpful in mastering R programming. I like that.
4. Plotted very nice figures and many skills are not mentioned in class yet. You are really a good learner and have great passion in R programming!
5. Tried different figure type, changed colors, used log _10 scaled data, added title (also centered) and axis labels, tried geom_smooth(), etc. Wonderful!
6. Explored this data in various ways, making numbers more meaningful.
7. Used piping, fitler and other functions correctly. Using piping in plotting, making your work more efficient!
8. Tried “I want more” question. You are thinking in a correct way. In this question, %in% should be used instead of ==. I am not very sure why but using == will make a loop between these two countries when selecting data.
9. Answered all questions accurately. Please see my suggestions below.

Cons (Suggestions)

1. In section 1.3, you mentioned that the classes of country and continent are integers. I do not agree with you. I think they should be factors. If you type gapminder (as you did at the beginning), you can see the class of each variable.
2. You mentioned that “cannot make a histogram of country to see the distribution”. Actually, you can. Country and continent are factors, and you can make a histogram. Please try again. I plotted using continent, here is my code.

   (q1 <- ggplot(gapminder, aes(x = continent)) +
       geom_histogram(stat="count") +
       labs(x="Continent", y="Counts"))

3. In section 3, there is no need to make an empty figure and then plot again with points. Showing the final figure would be better.

Yuanji

[ksedivyhaley]

Smell test of data: Yes, see comments re typeof() Explores at least one categorical/quantitative variable: Yes Uses various ggplot types: Yes (scatterplot, bar plot, density plot, boxplot) Uses filter(), select(), and %>%: Yes Bonus (evaluate code, tables, more dplyr): Partial (attempt code evaluation) Reflection on process: Yes

Comments:

• typeof() produces odd results with factors – it's calling $country and $continent integers because they are stored as integers under the hood, but it's important to be able to distinguish that from actual numeric data like $lifeExp. The 'class()' function will tell you when something is a factor.
• The histogram of life expectancy is very well done, but try it in ggplot instead of base!
• Your scatterplot exploration is disorganized. You're redefining p several times in such a way that it's unclear what p actually contains and what changes you're making. For example, why are you transforming a plot of life expectancy over time to use a log scale (p + geom_point() + scale_x_log10() # transforms the scatterplot to log scale)?
• Good variety of plots
• Good job piping into ggplot!
• # altered figure width so we could see the lines better : cool, but how? The code not in the chunk I'm seeing.

Your mark will be distributed later. If you would like more feedback, please feel free to message me on slack.