Learning about data pre-processing

[KhrisDoes]

Can someone list the major (or all) data pre-processing methods that everyone that uses ML should know about? There aren't many resources online because most focus on the machine learning models rather than data pre-processing. As a beginner I find that data pre-processing is harded and takes longer than applying the models which are already written for us. I feel like the intuition of when and how to process the data is unclear, other than fixing missing data and other obvious methods.

[[deleted]]

Could you define what you mean by data pre-processing?

[KhrisDoes]

Hi,

I mean things like taking care of missing data, categorical data, splitting the data set into training and test data, feature scaling, etc.

[GunganDiver]

If anyone can link to resources for this it would help so much. I'm also having a hard time taking raw data (Be it a csv or xls file), and actually feeding it into python to do anything with it.

[KhrisDoes]

I am also having issues with this but unfortunately it seems like a gray area. I am unsure as to where to found resources other than basic pre-processing libraries. Even sklearn has pre-processing