Making Dataframe Analysis faster
Most probably it doesn't matter because pandas stores each column separately anyway (DataFrame is a collection of Series). But you might get better data locality (all data next to each other in memory) by using a single frame, so it's worth trying. Check this empirically.
I am using three dataframes to analyze sequential numeric data - basically numeric data captured in time. There are 8 columns, and 360k entries. I created three identical dataframes - one is the raw data, the second a "scratch pad" for analysis and a third dataframe contains the analyzed outcome. This runs really slowly. I'm wondering if there are ways to make this analysis run faster? Would it be faster if instead of three separate 8 column dataframes I had one large one 24 column dataframe?