{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0254e3fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     60.1290\n",
       "1     52.4911\n",
       "2     53.6475\n",
       "3     52.5073\n",
       "4     46.0789\n",
       "5     57.7730\n",
       "6     68.2315\n",
       "7     68.2315\n",
       "8     58.9383\n",
       "9     57.1548\n",
       "10    65.9820\n",
       "11    56.5718\n",
       "12    78.1363\n",
       "Name: Length, dtype: float64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "data = pd.read_csv('example.csv')\n",
    "x = data['Length']\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2eb98515",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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, 'ok')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  }
 ],
 "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
}