A well-structured analysis with dynamic visualization and detailed explanation! Here is my feedback:
Introduction and motivation
• Background, motivation, and the problem of interest are clearly displayed.
• Also, it explains the four research questions in the next analysis. These four questions are following the order of Consumption – Production – Sustainable issue – Alternative supply step by step, which is well organized.
Data description
• Source and the structure of the data are clearly explained.
• Detailed variables with their types and definition, excellent!
o Suggestion:
• A data cleaning by exploring missing data, duplicate or incomplete value and outliers, may help reader better understand the data.
Questions of interest
• 20 open-ended questions with highlighted questions to further explore. Good job!
Expected findings
• Explained expected finding for each selected question.
• All expected findings are reasonable.
Analysis and findings
5.1 What has been the trend of seafood consumption of each country over the years?
• A nice line graph with details clearly displayed the trend of world’s yearly seafood consumption.
• The ggplotly helps reader easily grabs the yearly figures on one the red line. Nice choice!
• A brief explanation of the reason of decline in certain years.
• R code is reproducible and works well.
• The method to answer the question is explained.
• The tables 5.1 and 5.2 point out the highest and lowest with quantity and rank.
• Another line chart with animation to explore the changes in seafood consumption over time in the 10 countries with the highest average seafood consumption. In comparison, the next facet-warp graph is a great support to this analysis. After this, a convincing explanation. Well done!
o Suggestion:
• For tables 5.1 and 5.2, perhaps using a bar chart could better visualize the difference in size between countries.
5.2 What has been the trend of captured vs farmed production of each country over the years?
• Figure 5.5: Captured fishery production VS Aquaculture in the world, animation helps reader better grab the trend of time series data.
• Following this, 5.2.1 and 5.2.2, two tables show up the top 10 largest aquaculture producers from year 2000 onwards and comparing with the quantity of wild capture. Good idea!
• 5.2.3 uses lines to compare visualize the quantity comparison in previous. Also, an explanation provided. Excellent!
• R code is reproducible and works well.
o Suggestion:
• The information of percentage in Table 5.4 could be better displayed by a pie chart or bar graph.
5.3 What is the contribution of each country in the global fishery sector?
• Figure 5.7 gives readers a big picture of fish production.
• A very interesting explanation by linking the production with geography. Nice!
• Figure 5.8 focus on type of fish. A scatter plot points out the trend of each type of fish production.
• R code is reproducible and works well.
o Suggestion:
• For this question, we could not only use quantity figure but also the percentage contribution.
• In this case, Table 5.4 may help to answer this question.
5.4 What has been the trend of sustainable levels of fish stocks in the world?
• A data cleaning prior to analysis, which make the analysis more accurate and convincing.
• Table 5.5 compares the two types of fishing by quantity.
• Figure 5.9 analyses the same matter but in term of trend. A good way to help reader having a full picture.
• R code is reproducible and works well.
o Suggestion:
• Figure 5.9, the proportion of sustainable and overexploited could be visualized by a pie or bar graph to show the information in another way.
A well-structured analysis with dynamic visualization and detailed explanation! Here is my feedback:
Introduction and motivation
• Background, motivation, and the problem of interest are clearly displayed. • Also, it explains the four research questions in the next analysis. These four questions are following the order of Consumption – Production – Sustainable issue – Alternative supply step by step, which is well organized.
Data description
• Source and the structure of the data are clearly explained. • Detailed variables with their types and definition, excellent!
o Suggestion: • A data cleaning by exploring missing data, duplicate or incomplete value and outliers, may help reader better understand the data.
Questions of interest
• 20 open-ended questions with highlighted questions to further explore. Good job!
Expected findings
• Explained expected finding for each selected question. • All expected findings are reasonable.
Analysis and findings
5.1 What has been the trend of seafood consumption of each country over the years? • A nice line graph with details clearly displayed the trend of world’s yearly seafood consumption. • The ggplotly helps reader easily grabs the yearly figures on one the red line. Nice choice! • A brief explanation of the reason of decline in certain years. • R code is reproducible and works well. • The method to answer the question is explained. • The tables 5.1 and 5.2 point out the highest and lowest with quantity and rank.
• Another line chart with animation to explore the changes in seafood consumption over time in the 10 countries with the highest average seafood consumption. In comparison, the next facet-warp graph is a great support to this analysis. After this, a convincing explanation. Well done!
o Suggestion: • For tables 5.1 and 5.2, perhaps using a bar chart could better visualize the difference in size between countries.
5.2 What has been the trend of captured vs farmed production of each country over the years? • Figure 5.5: Captured fishery production VS Aquaculture in the world, animation helps reader better grab the trend of time series data. • Following this, 5.2.1 and 5.2.2, two tables show up the top 10 largest aquaculture producers from year 2000 onwards and comparing with the quantity of wild capture. Good idea!
• 5.2.3 uses lines to compare visualize the quantity comparison in previous. Also, an explanation provided. Excellent! • R code is reproducible and works well.
o Suggestion: • The information of percentage in Table 5.4 could be better displayed by a pie chart or bar graph.
5.3 What is the contribution of each country in the global fishery sector? • Figure 5.7 gives readers a big picture of fish production. • A very interesting explanation by linking the production with geography. Nice! • Figure 5.8 focus on type of fish. A scatter plot points out the trend of each type of fish production. • R code is reproducible and works well.
o Suggestion: • For this question, we could not only use quantity figure but also the percentage contribution. • In this case, Table 5.4 may help to answer this question.
5.4 What has been the trend of sustainable levels of fish stocks in the world? • A data cleaning prior to analysis, which make the analysis more accurate and convincing. • Table 5.5 compares the two types of fishing by quantity. • Figure 5.9 analyses the same matter but in term of trend. A good way to help reader having a full picture. • R code is reproducible and works well.
o Suggestion: • Figure 5.9, the proportion of sustainable and overexploited could be visualized by a pie or bar graph to show the information in another way.
References.
• It is detailed and well organized. Good job!