Specific case for Joining multiple datasets
Hi everyboday,
In a data science project I have recieved 4 cleaned datasets on an intersting topic healthy diet to protects ourselselves against Covid-19. I have already imported these 4 data sets in Rapidminer Studio. before I analyse them with machine learning, modelling and statistical preditions I would like to join and aggrgate those 4 datasets into one single dataset. This is where I ahve encountered an underestanding problem how to go further....
All of those 4 cleaned datasets have exact the same 32 Columns and 170 rows. Only the information delivered in these tables as following are different in their %-value:
1. Fat_Supply_Quantity_Data.csv
2. Food_Supply_kcal_Data.csv
3. Food_Supply_Quantity_kg_Data.csv
4. Protein_Supply_Quantity_Data
How do you see a possibility to join those 4 datasets to one single datase,t although all have the same number of 32 columns and same 170 rows OR should I look at each of 4 datasets separately and process them seperated from eachtother? Can you support me with your insights?