{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c9e8a83f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     57.313\n",
       "1     52.632\n",
       "2     43.922\n",
       "3     44.448\n",
       "4     60.245\n",
       "5     60.305\n",
       "6     67.839\n",
       "7     60.819\n",
       "8     71.989\n",
       "9     71.939\n",
       "10    74.911\n",
       "11    76.080\n",
       "12    61.988\n",
       "13    67.846\n",
       "14    72.517\n",
       "Name: Length, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# importing data\n",
    "import pandas as pd\n",
    "data = pd.read_csv('results-1.csv')\n",
    "x = data['Length']\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bbb4b0d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x115566cf0>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "[encoded data, 11632 characters]",
      "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
}
