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I've been shifting a bunch of data analysis out of spreadsheets (and some adhoc SQL) to Jupyter/Pandas, and we've found some unexpected tradeoffs on both sides.
by mattbowen 11y ago
I've been shifting a bunch of data analysis out of spreadsheets (and some adhoc SQL) to Jupyter/Pandas, and we've found some unexpected tradeoffs on both sides.
The lack of testability and version control (and really, long-term maintainability) is what drove us out of spreadsheets into Jupyter. We've found though that the workflow in Jupyter, even with Pandas, is not great for exploring and getting a feel for data --- we end up missing the very quick "poking around" you can do in excel or in a good sql client.
I'd have to use Stencila more to know if it strikes the right balance for the kind of analysis work I do, but I'm glad to see such a thoughtful attempt to try a new balance.
- Mikeb85 11y agoTry R and RStudio. It excels at 'poking around' data. In addition, you can show any data frame as a spreadsheet of data, import/export CSV files, etc... Knitr, Shiny, Plotly and other technologies also make producing documents, graphs and whatnot super easy. This Stencila also looks cool though. Spreadsheet + R....
- maxpupmax 11y agoShout out to Rodeo IDE as well -- they're doing a great job at making an "Rstudio for Python"
- dgudkov 11y agoMatt, check out my EasyMorph (http://easymorph.com http://easymorph.com) -- it's like Excel for tabular data with a comprehensive set of pre-built transformations to replace Python scripting. It's intended for both "quick poking around" and doing complex analysis.