Merge pull request #7 from mehallhm/personal

Personal

blog/content/justin/phase2.md

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 # Phase 2 Dialogue Reflection
 
-During phase II, I contributed to many areas of the project. As a group, we decided to scrap the government entity persona and I helped to make the business persona with the new features and updated the ER diagram. I created the ER diagram for the government entity persona and assisted in the creation and merging of the other two. Next, I made the tables for the intermediate ER diagram so that we could translate it into actual code. With the CS members of our group, I wrote the code for the SQL DDL to create tables in SQL In terms of visual improvements to the blog, I added a group author profile which appears on the landing page with a waffle icon. I also enabled the searching by tags feature and helped to create the Google Slides wireframe. For ease of use, I added a GitHub icon to the navbar and the group author profile which links to our GitHub repository.
+There was a lot to be done in phase II of the project. First of all, as a group, we consulted with Dr. Fontenot and came to the conclusion that the government entity persona would be unrealistic and too challenging to implement specifically the policy feature. Initially, we wanted to manually put different policies into a strong entity table but this turned out to be too much work for the timespan we had. We decided it would be more beneficial and useful to instead create a business persona which could fill out a business emission calculator survey similar to the general user. I created the ER diagram for this new persona and helped come up with the new features such as also calculating the percent of country emissions. I also assisted in the creation of the wireframe with Anjola. Combining the ER diagrams was harder than anticipated because we were confused about weak entities and how they were applied. In addition, we had to fill in some attributes (survey answers) that we knew were subject to change such as aircraft type because we didn’t know what data we were going to be working (correlation to emissions uncertain). However, once we had our combined ER diagram, I created the tables (in Google drawings) for the diagram so that we could translate it into actual SQL code. It was confusing navigating all the steps in slide 10 for things like many-to-many relationships but I eventually completed the tables and helped to write the create statements. In terms of visual improvements to the blog, I looked through blowfish example sites and found a group author display feature. I added the group author profile which appears on the landing page with a waffle icon. I also enabled the searching by tags feature and helped to create the Google Slides wireframe. For ease of use, I added a GitHub icon to the navbar and the group author profile which links to our GitHub repository.
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+During the week of phase II, as a dialogue we were very busy. My favorite sight that we saw was the Brussels Atomium. It is a very iconic and weirdly appealing structure which is a lot bigger than I imagined it to be. Inside was even more intriguing with the flickering light section and also the historical section. I also enjoyed visiting Microsoft Europe and hearing about how Microsoft uses that office to mainly negotiate policy with the EU. Overall, Belgium has been a great experience and I’m excited to continue to engage with the atmosphere here.

blog/content/micha/phase2.md

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 ### Project Reflection
 
-Individually I contributed the Exploratory Data Analysis as well as the Machine Learning prototype. Being the only DS3000 kid in our group, I had a lot of work that was not necessarily hard, but rather time consuming. I spent a lot of time trying to figure out how the algorithm would work and what data would be used. This surfaced as lots of diagrams and chats with the team to continue to hone down the idea into something tangible and buildable. We went through several iterations on how to take our Phase I ideas and impliment them, with the Professors' feedback. I felt like I was always on Eurostat browsing for data that either was useful, or a stepping stone to what I needed for the model / app.
+Individually I contributed the Exploratory Data Analysis as well as the Machine Learning prototype. Being the only DS3000 kid in our group, I had a lot of work that was not necessarily hard, but rather time consuming.
 
-After getting what I wanted / needed to build down, the actually programming / data science was quite straightforward but time consuming. Finding edge cases when building the Eurostat parser (only to find out there was a library 🙃), parsing and cleaning the data, and finally pulling it into the model just took a while to manipulate the dataframe as well as write cleanish code that could be expanded to more data with minimal effort.
+The majority of this time was spent on how the algorithm would work and what data would be used; as a result there were lots of team meetings to continue to hone down the idea into something tangible and buildable. We went through several iterations on what the specifics were to take our Phase I ideas and impliment them, clarified with the Professors' feedback. I felt like I was always on Eurostat browsing for data that either was useful, or a stepping stone to what I needed for the model / app.
+
+After getting what I wanted / needed to build down, the actually programming / data science was quite straightforward but time consuming. One unit of work was building and finding all the edge cases of a Eurostat API parser (only to find out there was a library 🙃). Next, there were some challenges when parsing and cleaning the data, mostly trying to fill in missing data as well as match the datasets in order to merge them for the model. While what I did was quick and in need of much more work, it still took some time to hunt down `NaN`s that managed to sneak into odd places. This data manipulation through Pandas is not something I was great at, but through the repetition I have started noticing improvements in my ability to rearrange and navigate these larger datframes. Finally, pulling that data into the model just took a while as I wanted to write cleanish code that could be expanded to more data with minimal effort. The linear algebra was overall simple once the matricies were constructed.
 
 ### Belgium Reflection
 
-In terms of the best things that have happened since the last Phase reflection, the choclate and pastry extravagansa takes the cake(pun intended). The chaos of getting your hands messy in chocolate and cream to create delicious treats that we consumed afterwards was amazing. The atmosphere of everyone in a cramped space, covered in food, was hilarious amounts of fun. On top of that, the treats were amazing and to share them with everyone else really cemented the culture of the group where everyone is confortable being themselves.
+The largest thing I have realized throughout my stay in Europe so far was the cultural differences which are then relfected in systems such as the governmental organizations that we have spent much time talking to. In general, entities like the EU more completely flush out the rules on how everyone gets to play in the market, attempting to anticiapte cases and overall building these rules around fundamental ideas that often are quite vauge. Comparativly, the US creates the bare minimum, allowing the players in the space to sue and legally fight each other to establish the rules. Interestingly, every speaker has agreed that these rules were advocated for on both sides, private and public entities alike. That difference in creating a well defined market compared to creating the rules as they are needed illustrates this fundamental difference which proves that there is more than one way to run a country.
+
+In terms of the best activies that have happened since the last Phase reflection, the choclate and pastry extravagansa takes the cake(pun intended). The chaos of getting your hands messy in chocolate and cream to create delicious treats that we consumed afterwards was amazing. The atmosphere of everyone in a cramped space, covered in food, was hilarious amounts of fun. On top of that, the treats were amazing and to share them with everyone else really cemented the culture of the group where everyone is confortable being themselves.