Data Science
Data Acquisition
From given data source, we can extract raw data and transform into tidy data so that it can be used for data analysis and business communication. Our data extraction and cleaning processes strictly follow principles of tidy data i.e.
- Each measurable variable has its own column
- Each observation is in different row
- Table for each object represented by related variable
- Each of multiple but related tables must has a column to linked them
Tidy data always comes with a code book – describing variables and their data types.