Josh Kirk

Results 24 issues of Josh Kirk

The Teams implementation had the keyword as `token`, however, the method requires `webhook_url`. This is a tiny change it seemed easier for me to fix rather than open an issue....

As discussed [here](https://discourse.julialang.org/t/how-to-get-a-quick-description-of-a-vector-matrix-like-pd-dataframe-describe/78013/5) currently if you pass a matrix to describe you get an error from `quantile!` ```Julia julia> describe(reshape(collect(1:100), (10, 10))) ERROR: MethodError: no method matching quantile!(::Matrix{Int64}, ::Vector{Float64}; sorted=false,...

I've read issues #278 and #279, which suggest this should have been fixed in [v0.9.0](https://github.com/jump-dev/Ipopt.jl/releases/tag/v0.9.0) but I'm finding in Ipopt.jl v1.0.3 this still not working, unless I'm doing something wrong?...

The code in this repo is considerably different to what is mentioned within the videos, with the video code sometimes having more detail and this repo sometimes having more detail....

## Details The following code doesn't have a circle for the final data point ```julia using Plots plotly() a= [1,2,3,25] b = [25,9,8,4] plot(a, b, markershape=:circle, markercolor=[1,2,3,4]) ``` ### Backends...

bug
good first issue
Plotly
PlotlyJS

I think this is similar to #161 which was closed by #162. The error experienced is the same as #161 where after drawing icons the tool doesn't reset and the...

draw

The link to the work of Beck and Schmidt was dead, have updated it.

**Is your feature request related to a problem? Please describe.** Users should be managed via LDAP, similar to [Portainer](https://docs.portainer.io/admin/settings/authentication/ldap) **Describe the solution you'd like** LDAP user management implemented **Describe alternatives...

enhancement
good first issue
help wanted
non-core

I have a non-linear program ```Julia juniper_opt = optimizer_with_attributes(Juniper.Optimizer, "nl_solver" => Ipopt.Optimizer, "mip_solver" => Gurobi.Optimizer) model = Model(juniper_opt) @variable(model, a) @NLconstraint(model, a * abs(a) >=3) @objective(model, Min, a) optimize!(model) ```...