Untitled1-checkpoint.ipynb
64.1 KB
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{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"id": "5e6ea3be-67e9-43ac-bed4-abbae7c4352b",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"image/png": 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]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"using CSV\n",
"using DataFrames\n",
"using Latexify\n",
"using Plots\n",
"using StatsPlots\n",
"\n",
"data = CSV.read(\"sample.csv\", DataFrame)\n",
"groups = groupby(data, :event)\n",
"totals = combine(groups, :event => length => :count)\n",
"\n",
"x = -π:0.1:π\n",
"y = sin.(x)\n",
"plot(totals.count)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e1c270c9-4270-414b-acce-33a3cc3b85c4",
"metadata": {},
"outputs": [],
"source": []
}
],
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"display_name": "Julia 1.9.3",
"language": "julia",
"name": "julia-1.9"
},
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"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
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}
},
"nbformat": 4,
"nbformat_minor": 5
}