look through and understand entire pipeline in data loading and cleaning folder, add more prints/checks
delete any unnecessary files (this is git, so no risk of losing anything here)
no need to document number of rows, column names, etc. but it might be useful to update README.md to have the sequence in which code files need to be run to build the base + what datasets each file produces. creating a dependency graph/flowchart might be the best way to do this (each node is a script and any datasets it produces, edges/arrows connecting the nodes that input to other scripts/datasets)
look through and understand entire pipeline in data loading and cleaning folder, add more prints/checks
delete any unnecessary files (this is git, so no risk of losing anything here)
no need to document number of rows, column names, etc. but it might be useful to update
README.mdto have the sequence in which code files need to be run to build the base + what datasets each file produces. creating a dependency graph/flowchart might be the best way to do this (each node is a script and any datasets it produces, edges/arrows connecting the nodes that input to other scripts/datasets)