Hi, taha-junaid3000 🙂
tomislavk is right… Splitting the work with someone would help you to achive better results and to learn much more while collaborating with others 🙂
Keeping in mind your work I would focus more on the analysis and conclusions regarding the data quality, variables for modelling, etc. This would be helpful to make next steps.

Hi team :), Good work!!!
You are right that the issue with missings should be solved in a better way (but not replacing with last known value). If there is one or a few neighbour missings, we may replace them without distorting the data, but in the case of long missing interval, Instead of replacement, we may use the data sets separately… There are ways to concatenate data from different data sets even when build dynamic models…

Not more to add after Agamemnon 🙂
I also like your validation approach, keeping in mind the small number of data, also introducing different scenarios related to the forecasts.

In many cases the data prep is a key step and in this case the data engineering and data cleaning and the related analysis that you mane are very important steps.  
In addition to that I appreciate your attempt to use sentiment analysis.
And finally I like your well structured work :).

I appreciate very much your attempt to find segments of similar nft-s and believe that after appropriate data prep the results would be better. 
After that additional modelling step could be made within each segment.