Due to the objective focused on predicting air quality forecast for the next 24 hours per station, first step should be data understanding for citizen science air quality measurements to group it by station and summarize them by day.
To complete this task for inspection and pre-processing in order to find missing data, outliers and some inconsistencies datasets were loaded in IBM SPSS to perform a more efficient and fast inspection. After that, when rows for 2017 and 2018 are completed and binded a complete dataset will be exported and loaded into R for the next preprocessing task where goespacial information will be taken in consideration.
Your assignments to peer review (and give feedback below the coresponding articles) for week 1 of the Monthly challenge are the following teams:
Excellent!! But tell me, when do I have to review those articles? I am still working on mine.
Could you consider that I am 8 hours delay from you.
Thank you very much
Hi Jacob, I think you could use more detail and perhaps some of your code, or outputs from SPSS. I’m not sure if this is meant to be your final article or if you are still planning to add to it?
Hi, codes and visualizations will be helpful to do the review.
We are looking forward with sooooo much excitement of seeing your article. Usually taking more time on the assignment means high quality results, so just keep going on 🙂
Your assignments to peer review (and give feedback below the coresponding articles) for week 2 of the Monthly challenge are the following teams:
@jacobavila – I just visited the article for updates. Please drop me a comment when you are ready for me to review for week2.
Checking in again on Nov 3rd. for my part of the peer review assignment. Good luck.