root_base (conda): Almost everything in ROOT should be supported in this Conda package; ROOT was built with lots of options turned on. Here are a few things to try:  * `root`: you can start up a session and see the splash screen; Control-D to exit. * `python` followed by `import ROOT` will load PyROOT. * `root --notebook` will start a notebook server with a ROOT kernel choice. * `rootbrowse` will open a TBrowser session so you can look through files. * `root -l -q $ROOTSYS/tutorials/dataframe/df013_InspectAnalysis.C` will run a DataFrame example with an animated plot. * `root -b -q -l -n -e "std::cout << TROOT::GetTutorialDir() << std::endl;"` will print the tutorial dir. * `root -b -l -q -e 'std::cout << (float) TPython::Eval("1+1") << endl;'` will run Python from C++ ROOT.  See the post [here](https://iscinumpy.gitlab.io/post/root-conda/) for more information about using this Conda package.  The ROOT package will prepare the required compilers. Everything in Conda is symlinked into `$CONDA_PREFIX` if you build things by hand; tools like CMake should find it automatically. The `thisroot.*` scripts should not be used and are not provided. Graphics, `rootbrowse`, etc. all should work. OpenGL is enabled.  There is also a `root_base` package, with minimal dependecies, that libraries should depend on this to avoid having a runtime dependency on the `compilers` package. `root-dependencies` and `root-binaries` are also available. In most cases users should use the `root` package directly, since it adds both of these, along with compilers, Jupyter, and a few other things to facilitate using ROOT or PyROOT.  ROOT was built with and will report `-std=c++17` from `root-config`.
Keywords: c-plus-plus|cling|data-analysis|geometry|graphics|hacktoberfest|interpreter|machine-learning|mathematics|parallel|physics|python|root|root-cern|statistics|visualization