In pandas you could/should use dataframe index and column labels that way, it automatically aligns by column and index names before arithmetic, unlike raw numpy

In pandas you could/should use dataframe index and column labels that way, it automatically aligns by column and index names before arithmetic, unlike raw numpy arrays which aligns by position. It takes more discipline and some performance hit though. You could even do it with SQL field (column) names and natural joins. The performance hit is even bigger and discipline/retraining is even bigger, as few SQL users are used to thinking about column names (rather than types) as type definitions. Further, this would only catch a class of bugs that are relatively easy to spot manually. The difficult case is when the processes that generated the numbers have slowly changed in time (e.g., you have a very different mix of visitors/customers now than during model training).