I’m a diehard user of the “PyData” toolchain (pandas, numpy, seaborn, sklearn, etc). Models become too much for Excel when either (a) you want to incorporate live updating datasets, (b) you want multiple users to be able to query the model simultaneously without affecting each other, or (c) you want to incorporate probabilistic calculations i.e. your inputs and/or outputs are distributions. Python blows Excel out of the water in these cases, it’s not a question of speed or ease of use.
However, I think Python’s biggest current weakness is the lack of a general purpose plotting library with good defaults or GUI-based tweaking. Matplotlib “can do anything”, provided you’re willing to google how to rotate axis labels and 20 other things to get legible styling. Seaborn is an improvement but still takes re-writing about 10-20 lines of code for each plot. As far as interactive libs, I prefer bokeh but it’s still too low level and missing fundamental capabilities like histograms. Holoviews is an interesting wrapper but still suffers the same limitations. Plotly... is popular, which is about all I can say for it. I find that I hit random walls and inflexibilities often bc it tries to be too one-size-fits-all. I understand ggplot from R is kind of the gold standard. Wish someone would do a carbon copy port to python.
Final random thought: my feeling is that white collar industries like insurance that are built around a network of Excel jockeys are in for a major disruption. If you built these companies from the ground up with a software dev team and mindset you could probably cut headcount 5x. It might not make business sense for a company deeply rooted in Excel to make that transition, but then again, that’s exactly why and how disruption happens.
However, I think Python’s biggest current weakness is the lack of a general purpose plotting library with good defaults or GUI-based tweaking. Matplotlib “can do anything”, provided you’re willing to google how to rotate axis labels and 20 other things to get legible styling. Seaborn is an improvement but still takes re-writing about 10-20 lines of code for each plot. As far as interactive libs, I prefer bokeh but it’s still too low level and missing fundamental capabilities like histograms. Holoviews is an interesting wrapper but still suffers the same limitations. Plotly... is popular, which is about all I can say for it. I find that I hit random walls and inflexibilities often bc it tries to be too one-size-fits-all. I understand ggplot from R is kind of the gold standard. Wish someone would do a carbon copy port to python.
Final random thought: my feeling is that white collar industries like insurance that are built around a network of Excel jockeys are in for a major disruption. If you built these companies from the ground up with a software dev team and mindset you could probably cut headcount 5x. It might not make business sense for a company deeply rooted in Excel to make that transition, but then again, that’s exactly why and how disruption happens.