Very nice assignment and interesting to look at how GDP changes when the share of work force changes in agriculture. The code works as it should but in the first interactive plot, the GDP per capita line is missing and the employment in agriculture is a straight downward sloping line which is wrong. As you write, it can be solved by selecting the countries manually, so it’s not really a problem.
It’s nice you have a small text above each line of code that explains what you are doing, but we feel like having it on the sideline as when you create the list of the 10 biggest countries by area of arable land, it can benefit the overview more. It would be nice if the sideline text was implemented more because we think the code is easier to understand by doing it in that way. Of course, there can be different options on that, but for someone who hasn’t coded the lines, it was a faster way to understand it.
We think the text suits the code very well. It’s good to see an explanation of what you do when there is missing data in the dataframe as when you calculate the absolute amount of people working in the agriculture sector per country and the percentage afterwards. We found two spelling errors in which you can correct. It’s in the read data text where you have written “countrys” instead of “countries” and after your first figure you have written “wworkers” instead of workers. You can just easily correct them if you want to. 😊
The Downward code was an elegant way to show the GDP per capita, employment in agriculture and Cereal Yield for different countries as its easy for the reader to select the figures you want to see.
When you go through the second plot, it’s a bit harder to understand what exactly is going on and a text to the lines would be a nice improvement.
As an extension of the assignment, it could be interesting to see how the wages in the agriculture has changed over the years, to see if it has dragged people from the agriculture and into other industries.
In general, it’s an intriguing topic and the pots you have made are very nice.
Very nice assignment and interesting to look at how GDP changes when the share of work force changes in agriculture. The code works as it should but in the first interactive plot, the GDP per capita line is missing and the employment in agriculture is a straight downward sloping line which is wrong. As you write, it can be solved by selecting the countries manually, so it’s not really a problem.
It’s nice you have a small text above each line of code that explains what you are doing, but we feel like having it on the sideline as when you create the list of the 10 biggest countries by area of arable land, it can benefit the overview more. It would be nice if the sideline text was implemented more because we think the code is easier to understand by doing it in that way. Of course, there can be different options on that, but for someone who hasn’t coded the lines, it was a faster way to understand it.
We think the text suits the code very well. It’s good to see an explanation of what you do when there is missing data in the dataframe as when you calculate the absolute amount of people working in the agriculture sector per country and the percentage afterwards. We found two spelling errors in which you can correct. It’s in the read data text where you have written “countrys” instead of “countries” and after your first figure you have written “wworkers” instead of workers. You can just easily correct them if you want to. 😊
The Downward code was an elegant way to show the GDP per capita, employment in agriculture and Cereal Yield for different countries as its easy for the reader to select the figures you want to see.
When you go through the second plot, it’s a bit harder to understand what exactly is going on and a text to the lines would be a nice improvement.
As an extension of the assignment, it could be interesting to see how the wages in the agriculture has changed over the years, to see if it has dragged people from the agriculture and into other industries.
In general, it’s an intriguing topic and the pots you have made are very nice.
Good job!