I liked all answers, make me more motivated to begin On Wed, Jul 22, 2020 at 9:24 AM Fernando Santagata < nando.santag...@gmail.com> wrote:
> Since you listed R among the other languages, I guess that you're > interested in statistical functions too. If not, discard the rest of this > email :-) > Not only, but also. Actually, recently I prepared a Jupiter Notebook with Raku kernel just to play with. Then, in another thread, I saw the implementation of the inner and outer join operation, then I 'm trying to do the left and right join too. I also thought to implement other relational operations (functions) to add columns, transform columns, summarize, filter, arrange, all common in data wrangle, and data manipulation, I know all these operations s easy doable in Raku but the Idea is to make it easy as possible as dictated by Hardley Wickham <https://r4ds.had.co.nz/index.html> and implemented in dplyr <https://github.com/tidyverse/dplyr>. The idea is to prepare a comfortable environment to do data analysis, resume some data in a good plot <https://github.com/tidyverse/ggplot2>, and etc. Since Raku deal really nice with rationals and natively deal with async and concurrency, this language might be wonderous to data analysis and data science. > I'm working now on the statistical functions of the GSL: mean, variance, > standard deviation, etc. Those functions are not based on the GSL > vector/matrix interface, so that module will not depend on any other Raku > module. > The functions provided by the library accept arrays in every native data > type[¹] available in Raku (int8, uint8, int16, … num32, num64). > If you're planning to use the fastest approach available, I can split the > module and publish the raw interface separately from the higher level one, > so you'll be able to use NativeCall internally and have the minimal set of > external code. > > [¹] libgsl has different functions for each data type. > > On Wed, Jul 22, 2020 at 1:42 AM Aureliano Guedes < > guedes.aureli...@gmail.com> wrote: > >> Hi all, >> >> I'd like to learn Raku deep enough to build a data structure. I have >> experience with Perl5, Python, R, and even C/C++, then I get boring >> feelings to learn something new from the beginning. Also, I prefer learning >> a new language by applying f to something. >> >> Since I work with data analysis and data science, I'd like to try to >> develop a data structure to dataframe in pure Raku. And if I do a basic but >> useful thing capable to load a field delimited file (as CSV or TSV) into a >> dataframe, I'll transform in a package and upload it to GitHub to >> comparatively enhance the package. >> What I need is suggestions for how do I start it. >> - How I define a data structure: an array of arrays? >> - Given the raku itself (and maybe some already existing packages) what >> the structures and functions I may use. >> >> I got these ideas to start: >> >> The dataframe should support columns name to be called as: >> >> df.column1 >> >> and it should return a list of values on this column. >> Also, when it read the delim file it should check each column type. >> >> >> All suggestions are welcome. >> >> >> >> -- >> Aureliano Guedes >> skype: aureliano.guedes >> contato: (11) 94292-6110 >> whatsapp +5511942926110 >> > > > -- > Fernando Santagata > -- Aureliano Guedes skype: aureliano.guedes contato: (11) 94292-6110 whatsapp +5511942926110
