Re:Python Data Visualization 2018: Why So Many Libraries?
by dnhz on Friday November 16, 2018 @03:31PM
(#18471729)
How do you transfer data from Python to R? I like the look of ggplot2, but most of my data I keep as pickle files.
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Re:Python Data Visualization 2018: Why So Many Libraries?
by cwyers on Friday November 16, 2018 @05:52PM
(#18472598)
Feather, based on the Apache Arrow format, is a lot faster than CSVs, and there's good support in both R and Python for it, maintained by Hadley Wickham (who has developed Almost Ever R Package You've Heard Of) and Wes McKinney (who is the BDFL of pandas) respectively. It also involves less inferring of data types using heuristics.
Re:Python Data Visualization 2018: Why So Many Libraries?
by minimaxir on Friday November 16, 2018 @03:37PM
(#18471762)
Exporting as a CSV (e.g. pandas's to_csv) works fine, since R/ggplot2 expects tabular data.
You probably shouldn't be keeping data as pickles, for both compatibility and security reasons.
Re:Python Data Visualization 2018: Why So Many Libraries?
by dnhz on Sunday November 18, 2018 @08:36PM
(#18483602)
>You probably shouldn't be keeping data as pickles, for both compatibility and security reasons
It's science research. My own simulation code and data. Some of it is hdf5, but pickle files are pretty convenient. Workflow is mainly turning data into plots. Heh, I thought I was doing alright since I'm not using textfiles.