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{
  "metadata": {
    "language_info": {
      "codemirror_mode": {
        "name": "python",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8"
    },
    "kernelspec": {
      "name": "python",
      "display_name": "Python (Pyodide)",
      "language": "python"
    }
  },
  "nbformat_minor": 4,
  "nbformat": 4,
  "cells": [
    {
      "cell_type": "markdown",
      "source": "#Experimento guia",
      "metadata": {}
    },
    {
      "cell_type": "markdown",
      "source": "Servilleta Cerrada",
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": "import numpy as np\n",
      "metadata": {
        "trusted": true
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": "import matplotlib.pyplot as plt",
      "metadata": {
        "trusted": true
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": "a = np.loadtxt('tiempos.txt')\nprint(a)\na.shape",
      "metadata": {
        "trusted": true
      },
      "execution_count": 3,
      "outputs": [
        {
          "name": "stdout",
          "text": "[[0.    0.    0.    0.    0.    0.    0.    0.    0.    0.   ]\n [0.033 0.033 0.035 0.033 0.033 0.033 0.031 0.033 0.034 0.034]\n [0.067 0.066 0.07  0.066 0.065 0.067 0.062 0.066 0.069 0.067]\n [0.1   0.099 0.105 0.099 0.098 0.1   0.093 0.099 0.103 0.101]\n [0.134 0.132 0.14  0.132 0.131 0.133 0.124 0.132 0.137 0.134]\n [0.167 0.165 0.175 0.165 0.164 0.167 0.155 0.164 0.172 0.168]\n [0.201 0.198 0.21  0.197 0.196 0.2   0.186 0.197 0.206 0.201]\n [0.234 0.231 0.245 0.23  0.229 0.233 0.217 0.23  0.24  0.235]\n [0.268 0.264 0.28  0.263 0.262 0.266 0.248 0.263 0.275 0.268]\n [0.301 0.297 0.315 0.296 0.295 0.3   0.279 0.296 0.309 0.302]\n [0.334 0.33  0.35  0.329 0.327 0.333 0.31  0.329 0.344 0.335]\n [0.368 0.363 0.385 0.362 0.36  0.366 0.341 0.362 0.378 0.369]\n [0.401 0.396 0.419 0.395 0.393 0.4   0.371 0.395 0.412 0.402]\n [0.435 0.429 0.454 0.428 0.426 0.433 0.402 0.428 0.447 0.436]\n [0.468 0.462 0.489 0.461 0.458 0.466 0.433 0.461 0.481 0.469]\n [0.502 0.495 0.524 0.494 0.491 0.5   0.464 0.493 0.515 0.503]\n [0.535 0.528 0.559 0.527 0.524 0.533 0.495 0.526 0.55  0.536]\n [0.569 0.561 0.594 0.559 0.556 0.566 0.526 0.559 0.584 0.57 ]\n [0.602 0.594 0.629 0.592 0.589 0.6   0.557 0.592 0.618 0.604]\n [0.635 0.627 0.664 0.625 0.622 0.633 0.588 0.625 0.653 0.637]\n [0.669 0.66  0.699 0.658 0.655 0.666 0.619 0.658 0.687 0.671]\n [0.702 0.693 0.734 0.691 0.687 0.7   0.65  0.691 0.721 0.704]]\n",
          "output_type": "stream"
        },
        {
          "execution_count": 3,
          "output_type": "execute_result",
          "data": {
            "text/plain": "(22, 10)"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": "prom_Tiempos = a.mean(axis=1)",
      "metadata": {
        "trusted": true
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": "prom_Tiempos",
      "metadata": {
        "trusted": true
      },
      "execution_count": 5,
      "outputs": [
        {
          "execution_count": 5,
          "output_type": "execute_result",
          "data": {
            "text/plain": "array([0.    , 0.0332, 0.0665, 0.0997, 0.1329, 0.1662, 0.1992, 0.2324,\n       0.2657, 0.299 , 0.3321, 0.3654, 0.3984, 0.4318, 0.4648, 0.4981,\n       0.5313, 0.5644, 0.5977, 0.6309, 0.6642, 0.6973])"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": "prom_Tiempos.shape",
      "metadata": {
        "trusted": true
      },
      "execution_count": 18,
      "outputs": [
        {
          "execution_count": 18,
          "output_type": "execute_result",
          "data": {
            "text/plain": "(22,)"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": "b= np.loadtxt('alturas1.txt')\nb=np.loadtxt('alturas1.txt', dytype=\"int\")\nb=np.loadtxt(dtype=\"int\" ,usecols = (1,10))\nprint (b)",
      "metadata": {
        "trusted": true
      },
      "execution_count": 35,
      "outputs": [
        {
          "ename": "<class 'ValueError'>",
          "evalue": "could not convert string '8,05E+00' to float64 at row 1, column 1.",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "Cell \u001b[0;32mIn[35], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m b\u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloadtxt\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43malturas1.txt\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      2\u001b[0m b\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39mloadtxt(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124malturas1.txt\u001b[39m\u001b[38;5;124m'\u001b[39m, dytype\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mint\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      3\u001b[0m b\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39mloadtxt(dtype\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mint\u001b[39m\u001b[38;5;124m\"\u001b[39m ,usecols \u001b[38;5;241m=\u001b[39m (\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m10\u001b[39m))\n",
            "File \u001b[0;32m/lib/python3.11/site-packages/numpy/lib/npyio.py:1356\u001b[0m, in \u001b[0;36mloadtxt\u001b[0;34m(fname, dtype, comments, delimiter, converters, skiprows, usecols, unpack, ndmin, encoding, max_rows, quotechar, like)\u001b[0m\n\u001b[1;32m   1353\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(delimiter, \u001b[38;5;28mbytes\u001b[39m):\n\u001b[1;32m   1354\u001b[0m     delimiter \u001b[38;5;241m=\u001b[39m delimiter\u001b[38;5;241m.\u001b[39mdecode(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlatin1\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m-> 1356\u001b[0m arr \u001b[38;5;241m=\u001b[39m \u001b[43m_read\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcomment\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcomment\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdelimiter\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdelimiter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1357\u001b[0m \u001b[43m            \u001b[49m\u001b[43mconverters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconverters\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mskiplines\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mskiprows\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43musecols\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43musecols\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1358\u001b[0m \u001b[43m            \u001b[49m\u001b[43munpack\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43munpack\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mndmin\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mndmin\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1359\u001b[0m \u001b[43m            \u001b[49m\u001b[43mmax_rows\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmax_rows\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquote\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquotechar\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1361\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m arr\n",
            "File \u001b[0;32m/lib/python3.11/site-packages/numpy/lib/npyio.py:999\u001b[0m, in \u001b[0;36m_read\u001b[0;34m(fname, delimiter, comment, quote, imaginary_unit, usecols, skiplines, max_rows, converters, ndmin, unpack, dtype, encoding)\u001b[0m\n\u001b[1;32m    996\u001b[0m     data \u001b[38;5;241m=\u001b[39m _preprocess_comments(data, comments, encoding)\n\u001b[1;32m    998\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m read_dtype_via_object_chunks \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 999\u001b[0m     arr \u001b[38;5;241m=\u001b[39m _load_from_filelike(\n\u001b[1;32m   1000\u001b[0m         data, delimiter\u001b[38;5;241m=\u001b[39mdelimiter, comment\u001b[38;5;241m=\u001b[39mcomment, quote\u001b[38;5;241m=\u001b[39mquote,\n\u001b[1;32m   1001\u001b[0m         imaginary_unit\u001b[38;5;241m=\u001b[39mimaginary_unit,\n\u001b[1;32m   1002\u001b[0m         usecols\u001b[38;5;241m=\u001b[39musecols, skiplines\u001b[38;5;241m=\u001b[39mskiplines, max_rows\u001b[38;5;241m=\u001b[39mmax_rows,\n\u001b[1;32m   1003\u001b[0m         converters\u001b[38;5;241m=\u001b[39mconverters, dtype\u001b[38;5;241m=\u001b[39mdtype,\n\u001b[1;32m   1004\u001b[0m         encoding\u001b[38;5;241m=\u001b[39mencoding, filelike\u001b[38;5;241m=\u001b[39mfilelike,\n\u001b[1;32m   1005\u001b[0m         byte_converters\u001b[38;5;241m=\u001b[39mbyte_converters)\n\u001b[1;32m   1007\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   1008\u001b[0m     \u001b[38;5;66;03m# This branch reads the file into chunks of object arrays and then\u001b[39;00m\n\u001b[1;32m   1009\u001b[0m     \u001b[38;5;66;03m# casts them to the desired actual dtype.  This ensures correct\u001b[39;00m\n\u001b[1;32m   1010\u001b[0m     \u001b[38;5;66;03m# string-length and datetime-unit discovery (like `arr.astype()`).\u001b[39;00m\n\u001b[1;32m   1011\u001b[0m     \u001b[38;5;66;03m# Due to chunking, certain error reports are less clear, currently.\u001b[39;00m\n\u001b[1;32m   1012\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m filelike:\n",
            "\u001b[0;31mValueError\u001b[0m: could not convert string '8,05E+00' to float64 at row 1, column 1."
          ],
          "output_type": "error"
        }
      ]
    },
    {
      "cell_type": "code",
      "source": "prom_Altura = b.mean(axis=1)\nprom_Altura",
      "metadata": {
        "trusted": true
      },
      "execution_count": 32,
      "outputs": [
        {
          "execution_count": 32,
          "output_type": "execute_result",
          "data": {
            "text/plain": "array([0.    , 0.0332, 0.0665, 0.0997, 0.1329, 0.1662, 0.1992, 0.2324,\n       0.2657, 0.299 , 0.3321, 0.3654, 0.3984, 0.4318, 0.4648, 0.4981,\n       0.5313, 0.5644, 0.5977, 0.6309, 0.6642, 0.6973])"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": "plt.plot(prom_Tiempos, prom_Altura) ",
      "metadata": {
        "trusted": true
      },
      "execution_count": 20,
      "outputs": [
        {
          "ename": "<class 'NameError'>",
          "evalue": "name 'prom_Altura' is not defined",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "Cell \u001b[0;32mIn[20], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(prom_Tiempos, \u001b[43mprom_Altura\u001b[49m) \n",
            "\u001b[0;31mNameError\u001b[0m: name 'prom_Altura' is not defined"
          ],
          "output_type": "error"
        }
      ]
    },
    {
      "cell_type": "code",
      "source": "prom_Altura = b.mean(axis=1)\nprom_Altura",
      "metadata": {
        "trusted": true
      },
      "execution_count": 8,
      "outputs": [
        {
          "ename": "<class 'NameError'>",
          "evalue": "name 'b' is not defined",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "Cell \u001b[0;32mIn[8], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m prom_Altura \u001b[38;5;241m=\u001b[39m \u001b[43mb\u001b[49m\u001b[38;5;241m.\u001b[39mmean(axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m      2\u001b[0m prom_Altura\n",
            "\u001b[0;31mNameError\u001b[0m: name 'b' is not defined"
          ],
          "output_type": "error"
        }
      ]
    },
    {
      "cell_type": "code",
      "source": "b = np.loadtxt('alturas.txt')\nprint(b)\n\n",
      "metadata": {
        "trusted": true
      },
      "execution_count": 9,
      "outputs": [
        {
          "ename": "<class 'ValueError'>",
          "evalue": "could not convert string '5,55E-14' to float64 at row 0, column 1.",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "Cell \u001b[0;32mIn[9], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m b \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloadtxt\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43malturas.txt\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28mprint\u001b[39m(b)\n",
            "File \u001b[0;32m/lib/python3.11/site-packages/numpy/lib/npyio.py:1356\u001b[0m, in \u001b[0;36mloadtxt\u001b[0;34m(fname, dtype, comments, delimiter, converters, skiprows, usecols, unpack, ndmin, encoding, max_rows, quotechar, like)\u001b[0m\n\u001b[1;32m   1353\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(delimiter, \u001b[38;5;28mbytes\u001b[39m):\n\u001b[1;32m   1354\u001b[0m     delimiter \u001b[38;5;241m=\u001b[39m delimiter\u001b[38;5;241m.\u001b[39mdecode(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlatin1\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m-> 1356\u001b[0m arr \u001b[38;5;241m=\u001b[39m \u001b[43m_read\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcomment\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcomment\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdelimiter\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdelimiter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1357\u001b[0m \u001b[43m            \u001b[49m\u001b[43mconverters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconverters\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mskiplines\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mskiprows\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43musecols\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43musecols\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1358\u001b[0m \u001b[43m            \u001b[49m\u001b[43munpack\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43munpack\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mndmin\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mndmin\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1359\u001b[0m \u001b[43m            \u001b[49m\u001b[43mmax_rows\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmax_rows\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquote\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquotechar\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1361\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m arr\n",
            "File \u001b[0;32m/lib/python3.11/site-packages/numpy/lib/npyio.py:999\u001b[0m, in \u001b[0;36m_read\u001b[0;34m(fname, delimiter, comment, quote, imaginary_unit, usecols, skiplines, max_rows, converters, ndmin, unpack, dtype, encoding)\u001b[0m\n\u001b[1;32m    996\u001b[0m     data \u001b[38;5;241m=\u001b[39m _preprocess_comments(data, comments, encoding)\n\u001b[1;32m    998\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m read_dtype_via_object_chunks \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 999\u001b[0m     arr \u001b[38;5;241m=\u001b[39m \u001b[43m_load_from_filelike\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1000\u001b[0m \u001b[43m        \u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdelimiter\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdelimiter\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcomment\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcomment\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquote\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquote\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1001\u001b[0m \u001b[43m        \u001b[49m\u001b[43mimaginary_unit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mimaginary_unit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1002\u001b[0m \u001b[43m        \u001b[49m\u001b[43musecols\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43musecols\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mskiplines\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mskiplines\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_rows\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmax_rows\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1003\u001b[0m \u001b[43m        \u001b[49m\u001b[43mconverters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconverters\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1004\u001b[0m \u001b[43m        \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfilelike\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilelike\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1005\u001b[0m \u001b[43m        \u001b[49m\u001b[43mbyte_converters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbyte_converters\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1007\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   1008\u001b[0m     \u001b[38;5;66;03m# This branch reads the file into chunks of object arrays and then\u001b[39;00m\n\u001b[1;32m   1009\u001b[0m     \u001b[38;5;66;03m# casts them to the desired actual dtype.  This ensures correct\u001b[39;00m\n\u001b[1;32m   1010\u001b[0m     \u001b[38;5;66;03m# string-length and datetime-unit discovery (like `arr.astype()`).\u001b[39;00m\n\u001b[1;32m   1011\u001b[0m     \u001b[38;5;66;03m# Due to chunking, certain error reports are less clear, currently.\u001b[39;00m\n\u001b[1;32m   1012\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m filelike:\n",
            "\u001b[0;31mValueError\u001b[0m: could not convert string '5,55E-14' to float64 at row 0, column 1."
          ],
          "output_type": "error"
        }
      ]
    },
    {
      "cell_type": "code",
      "source": "prom_Altura.shape",
      "metadata": {
        "trusted": true
      },
      "execution_count": 10,
      "outputs": [
        {
          "ename": "<class 'NameError'>",
          "evalue": "name 'prom_Altura' is not defined",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "Cell \u001b[0;32mIn[10], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mprom_Altura\u001b[49m\u001b[38;5;241m.\u001b[39mshape\n",
            "\u001b[0;31mNameError\u001b[0m: name 'prom_Altura' is not defined"
          ],
          "output_type": "error"
        }
      ]
    },
    {
      "cell_type": "code",
      "source": "plt.plot(prom_Tiempos, prom_Altura) ",
      "metadata": {
        "trusted": true
      },
      "execution_count": 11,
      "outputs": [
        {
          "ename": "<class 'NameError'>",
          "evalue": "name 'prom_Altura' is not defined",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "Cell \u001b[0;32mIn[11], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m plt\u001b[38;5;241m.\u001b[39mplot(prom_Tiempos, \u001b[43mprom_Altura\u001b[49m) \n",
            "\u001b[0;31mNameError\u001b[0m: name 'prom_Altura' is not defined"
          ],
          "output_type": "error"
        }
      ]
    },
    {
      "cell_type": "code",
      "source": "",
      "metadata": {},
      "execution_count": null,
      "outputs": []
    }
  ]
}