Biodiversity Project: Investigating Animals' Safety

Hey everyone,

I just finished the Biodiversity project. I found it quite interesting, and it provided some good practice to what was covered in the course.
This is my first post here, I hope I’m doing it right :smile:

This is my code:


I have nearly finished my project as well, but not really done. I like some of your visualization idea such as number of observations based on categories and conservation status. However, the dataset should be cleaned before using them. There are some notices I found as followings:

  • Observations.csv
    • This file’s got duplicated rows (completely duplicated in every column)
    • There are also some duplicated rows with the same scientific_name and park_name but different observations
  • Species_info.csv
    • This file also has duplicated rows
  • Once you merged data, the merged dataset should be checked if it has the same number of rows as observations
  • The visualization that shows the percentage of “Endangered” animals under each “category” . This is such a good idea to know. But, the title of diagram did not tell us clearly that the bar graphs inside are of “Endangered” conservation status. (You can also improve by creating a function so that you can reuse it for every conservation status)
  • Last but not least, it’d better have the summary for all you’ve found.

Enjoy coding!

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Thank you so much for taking the time and going through my project! You provide really good points.

I totally missed the duplicated rows in the data, I will analyze the data and deal with the duplicated rows.

You’re absolutely right about the title of the diagram. Initially, I was going to plot a different diagram, but I then changed my mind and decided to plot the current diagram, but forgot to rename it.

I agree, a conclusion at the end can definitely improve the project.

Again, I really appreciate you reading my work, and the notes you gave are really helpful and you must have read the project closely to spot these notes, so thank you again.

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