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98 lines
13 KiB
Plaintext
98 lines
13 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "c9e8a83f",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"0 57.313\n",
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"1 52.632\n",
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"2 43.922\n",
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"3 44.448\n",
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"4 60.245\n",
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"5 60.305\n",
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"6 67.839\n",
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"7 60.819\n",
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"8 71.989\n",
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"9 71.939\n",
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"10 74.911\n",
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"11 76.080\n",
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"12 61.988\n",
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"13 67.846\n",
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"14 72.517\n",
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"Name: Length, dtype: float64"
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]
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},
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# importing data\n",
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"import pandas as pd\n",
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"data = pd.read_csv('results-1.csv')\n",
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"x = data['Length']\n",
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"x"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "bbb4b0d9",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[<matplotlib.lines.Line2D at 0x115566cf0>]"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"import matplotlib.pyplot as plt\n",
|
|
"plt.plot(x, '.k')"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": ".venv (3.14.2)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.14.2"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|