hw07 ready for grading

[vmichalowski]

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

Here's a link to my process report, in which you will find all of the links needed to access the different scripts used and the final report md file.

[Tangjiahui26]

Peer Review:

Hi, @vmichalowski You did a really perfect homework and fully understood how to automate the pipeline. I really enjoyed browsing your Scripts and comments. You downloaded a set of valuable and meaningful data online and then tidied and plotted it. Actually I also met the problem that the link of gapminder was expired, but I finally found it on Jennybc's Github. Since there are so many interesting data on the official website of gapminder, I think I could use those data in the future homework.

The process of clearing and trimming data is rich. You appliedgather()to change the wide data into long data, also used some functions to convert the data type. You created scripts used both R and make, and finally realized the automation of pipelines.

Process as well as all the files you used are mentioned, I really like your report because it is clear and comprehensive, also has detailed descriptions of your thinking.

Actually, if you have the time, you can consider including an image showing a graphical viewof your pipeline using makefile2graph. I think it is easy for you since you just need to download the package and then run several lines of code on the terminal. But I think it is optional, your reports and codes are good enough.

Overall, I think your homework was really well done and hope you can keep it up!

Regards, Jiahui Tang

[rishadhabib]

Hi Victoia

Your homework 7 was very well done and very well explained; I learnt a lot from reading about your process and looking through your code. Everything was commented clearly. You explained how you broke down your pipeline and used interesting data that is relevant to your research for your analysis. I especially liked how your broke down the data cleaning process which was very important with your outside dataset. You also explored this data first before moving onto your final analysis. One thing I was wondering is why you chose to give such large names to your variables (e.g.p3_CO2_time_series_plot_Qatar_vs_Canada) - I can see that they are informative but must involve a lot of typing. I agree that with Jiahui above that a diagram of your pipeline would have been great but without it your process was still clear. Overall, I think you did a great job!