[Python] The mean of my aggregated values seems incorrect (dataset cleaned with pandas)

I am using pandas to clean a global coral bleaching dataset. I want to get the Percent_bleaching, Temperature_Mean and Date column for all the countries in the Caribbean and have been trying to find the mean to make a final CSV that has the Year, Temperature_Mean and Percent_Bleaching, for my Arduino project.

I have gotten rid of any rows with NaN values with left me with a dataframe looking like attached example of values of all the Caribbean before being aggregated (an example being, Country_Name = Cuba, Percent_Bleaching = 50.2, Temperature_Mean = 300.67, Date = 2005-09-15).

I found the mean to get one value per year (this is where I Think I must've done something wrong) the Temperature_Mean column seems okay with values such as 299-301 Kelvin, but the Percent_Bleaching is all over the place with a lot of values incredibly small i.e. 2.24% in 2016. (attached Screenshot) My final dataset (cleaned), but with a clearly inaccurate Percent_Bleaching column



Asker please put your code here instead of using an image!


I'm really new to this, so any help would be appreciated! My aim for the final uni project is to take this data, map the percentages to different light (white == severely bleached, blues and pinks == healthy) for an interactive coral bleach sculpture that allows you to time scrub through different years, and with a switch see current data to! (thanks to NOAA's API)

Thank you so much!!

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