Indexes are a data structure that contains pointers to the contents of a table arranged in a specific order, to help the database optimize queries. They are similar to the index of book, where the pages (rows of the table) are indexed by their page number.
Several types of indexes exist, and can be created on a table. When an index exists on the columns used in a query's WHERE clause, JOIN clause, or ORDER BY clause, it can substantially improve query performance.
Various examples showing how Tensorflow supports indexing into tensors, highlighting differences and similarities to numpy-like indexing where possible.
A more versatile alternative to VLOOKUP. An Index Match packs the power of a Vlookup and Hlookup in one formula. You also do not need to know which number column/row the information is. Due to this, deleting columns/rows will not mess up the formula.