Histogram in Julia: Distributed.ProcessExitedException

Question

I'm running Julia 1.7.2 in a Pluto notebook on an M1 chip.

I have a vector of integers between 1 and 9, and would like to make a histogram showing which integers are most frequent.

I thought I had done this successfully by using Plots and then calling histogram on the appropriate vector. At one point I had even generated a plot that I liked doing this.

I then tried to replicate this procedure (i.e. using Plots, and then call histogram) in a different Pluto notebook I had written.

I don't know if it was conflicting with other packages, but I began to get Distributed.ProcessExitedException errors in this other notebook when I ran histogram.

In another fail mode, I created a cell that contained only the following code

begin
    using Plots
    histogram(vector)
end

When I run the notebook with this code, all the other cells evaluate, but then this last cell lags forever and does not evaluate.

Frustrated, I went back to the first notebook where I had gotten the plotting to work, but now I get Distributed.ProcessExitedException error there too!

I am just posting to see if anyone has any ideas as to what might be going on.

In particular,

• is there a link between Plots and Distributed?
• is there anything that would cause an error in one notebook to cause a different notebook that had previously been working to fail?

The packages I was using in the first notebook that worked, and then didn't work) were

begin
    using DataFrames
    using BSON
    using Revise
    using FileIO
    using CSV, HDF5, NRRD
    # Statistics
    using StatsBase: mean, nquantile, percentile
    using LinearAlgebra: norm, mul!
    using HypothesisTests
    using Plots
    using Random
    # Tensors
    using Tullio: @tullio
    # Algorithms
    import Flux
    import Flux: update!
    using Flux: RMSProp
end

The packages I was using in the second notebook that never worked were

begin
    using DataFrames
    using FileIO
    using CSV, HDF5, NRRD
    # Statistics
    using StatsBase: mean, nquantile, percentile
    using LinearAlgebra: norm, mul!
    using HypothesisTests
    # Tensors
    using Tullio: @tullio
    # Algorithms
    import Flux
    import Flux: update!
    using Flux: RMSProp
end