> Can you imagine what data science/analysis would feel like with multiple low-level Pandas competitors, from different corporations? Each one would feel consis

> Can you imagine what data science/analysis would feel like with multiple low-level Pandas competitors, from different corporations? Each one would feel consistent, but none would work together (and imagine building an ML platform which supported multiple dataframe sources). > I do sometimes miss working in R - yes, R takes flexibility to a fault, but there's a consistent set of primitives that mostly get reused. Perhaps R gives off that impression because of the work done by Hadley and others to build tooling according to the tidyverse principles. I wonder if Julia will combine the best of these worlds in the future. Funny that you mention R, which has exactly what you criticized before (base R data.frame, tidyverse/tibble, data.table), not to mention at least 6 different packages/datastructures to represent time series.