SQL has no row/record names, only column/field names, in proper SQL most of the naming would go inside field values. Doing numerically intensive work this way u

SQL has no row/record names, only column/field names, in proper SQL most of the naming would go inside field values. Doing numerically intensive work this way usually requires both a lot more code (long queries with lots of joins) and a huge performance costs, unless your problems are pretty small. Pandas is somewhere halfway that and raw matrix/numpy math, automatically aligning dataframes by row and column names first before doing computations. Even though performance is usually closer to numpy than SQL, the extra overhead is sometimes large enough for people to drop down to plain numpy.