Histogram in Julia: Distributed.ProcessExitedException - julia

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