hello dear julia developers
i’m new to julia and i’m fascinated by the power and performance of this great language
i’m trying to convert my notebooks in R to Julia to help me learn it but the issue is that i’m stuck with a small issue
i have a dataframe that i need to select all columns except few ones
@select df $(Not([:Label, :Local]))
but i always get this error message
ArgumentError: Expressions not of the form `y = f(:x)` are currently disallowed.
despite that i followed exactly what is written in the documentations
thank you for the response dear @bkamins
i’m at version 0.7.1, i will try to update DataFramesMeta
btw, i’m very fan of you and i started learning watching your tutorials
it seems like the issue is related to the outdated package of DataFramesmeta, i tried to upgrade it but i failed and i received an error related to some precompiled packages or something
i’m so sorry for bothering you all, but this is what i got unfortunately
i think tensorflow is the cause of the issue
ERROR: Unsatisfiable requirements detected for package DataFrames [a93c6f00]:
DataFrames [a93c6f00] log:
├─possible versions are: 0.11.7-1.5.0 or uninstalled
├─restricted to versions * by an explicit requirement, leaving only versions 0.11.7-1.5.0
├─restricted by compatibility requirements with DataFramesMeta [1313f7d8] to versions: 1.0.0-1.5.0
│ └─DataFramesMeta [1313f7d8] log:
│ ├─possible versions are: 0.4.0-0.13.0 or uninstalled
│ └─restricted to versions 0.13 by an explicit requirement, leaving only versions 0.13.0
└─restricted by compatibility requirements with Compat [34da2185] to versions: 0.11.7-0.21.8 or uninstalled — no versions left
└─Compat [34da2185] log:
├─possible versions are: 1.0.0-4.6.0 or uninstalled
└─restricted by compatibility requirements with TensorFlow [1d978283] to versions: 1.0.0-2.2.1
└─TensorFlow [1d978283] log:
├─possible versions are: 0.10.2-0.11.0 or uninstalled
└─restricted to versions * by an explicit requirement, leaving only versions 0.10.2-0.11.0
The reason is that last release of this package was in 2019 and it is currently significantly outdated. Most of the packages (not only DataFramesMeta.jl) will not work correctly when TensorFlow.jl is installed.
I even see on its website that its developer recommends switching to Flux.jl.
thank you so much sir, it looks like TensorFlow and Torch were holding the updates for many packages and after removing them all packages got updated successfully
My advice is not to put anything substantive into the global environment. It should contain only a few packages useful for things like debugging. Such as Revise or Infiltrator or similar. Any substantive package for a project should go in an environment for that project.