Hi all,
I am sharing my completed guided project using SQL. This is my first time using SQL and I would love feedback on improving the readability and efficiency of my queries .
Link to last screen: https://app.dataquest.io/m/257/guided-project%3A-analyzing-cia-factbook-data-using-sql/8/next-steps
Basics.ipynb (47.7 KB)
Looking forward to your comments and contributions.
Thanks,
Austin.
Click here to view the jupyter notebook file in a new tab
Good work @austin-deccentric though it is your first time using SQL you’ve made you project to be more interesting and informative as an experienced person. Thanks for Sharing.
Happy Learning!
@info.victoromondi thanks for the feedback I really appreciate. The improvements can be attributed DQ!
Thanks for posting, this really helped me a lot…
Hi, @austin-deccentric.
When looking through your project I noticed that in the “Further Analysis” section you misinterpreted the population_growth field. If I am correct, this is a percentage.
I will use the output of the query in this section to provide examples. Focusing on the India record first, you interpreted the population_growth (a value of 1.22 for India) as meaning a 22% increase in the population. In reality, the population only increased by 1.22%. This means that your calculation should have looked more like the following:
new_population = old_population + (old_population * 0.0122)
or
new_population = old_population * 1.0122.
This is why you have some very large numbers for new_population and pop_diff. In your calculations the population in both Ethiopia and Iraq nearly tripled in size; for Uganda it more than tripled.
You may have already caught this but I figured I should comment on it in case you haven’t.
Best,
JesĂşs
Jesus saves the day! I did not see that. Thanks for pointing it out.