Lecture 4: Database
What we covered in lecture¶
Why data structure choices matter in materials informatics.
Core database concepts: table, index, key-value, and query flow.
Common data formats used in class and research workflows.
Materials databases and what each is good for.
Practical data work with Pandas and Materials Project API outputs.
What you should be able to do¶
Explain the difference between relational and non-relational storage in practical terms.
Read JSON/CSV data into Pandas and inspect shape, columns, and missing values.
Filter, sort, and aggregate a DataFrame for a materials question.
Extract nested dictionary fields from API-style data.
Build one simple plot from processed tabular data.