{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dataset - Add new item\n",
    "\n",
    "A common workflow is to create a new item based on existing items in a dataset.\n",
    "\n",
    "This can be in done in several ways. Let's try one of the options."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import mikeio\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mikeio.Dataset>\n",
       "dims: (time:67, element:958)\n",
       "time: 2017-10-27 00:00:00 - 2017-10-29 18:00:00 (67 records)\n",
       "geometry: Dfsu2D (958 elements, 570 nodes)\n",
       "items:\n",
       "  0:  Surface elevation <Surface Elevation> (meter)\n",
       "  1:  Wind speed <Wind speed> (meter per sec)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = mikeio.read(\"../tests/testdata/NorthSea_HD_and_windspeed.dfsu\")\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Create a copy of the DataArray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAEHCAYAAABMRSrcAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAAYBUlEQVR4nO3dfbRddZ3f8ffHIIwVlSiRFQEniMEOoo2SIj6WGSpGsAanDsLqSHxYRkeY6nLaMY5dhdFhNT6gUzoOipoSOgoyIpIlaIyUESsguSDlSZGAYUiM5AoqMjoo8O0f+3frIdyn3HMfk/drrbPuPt/99NvnrHs+Z//2PnunqpAk7d4eN9MNkCTNPMNAkmQYSJIMA0kShoEkCdhjphswUfvuu28tWrRoppshSXPKdddd95OqWrBjfc6GwaJFixgYGJjpZkjSnJLkruHqdhNJkgwDSZJhIEnCMJAkYRhIkjAMJEkYBpIkDANJEoaBJIk5/AtkaSyLVl06I+vdvPq4GVmv1A/3DCRJhoEkyTCQJGEYSJIwDCRJGAaSJAwDSRKGgSQJw0CShGEgScIwkCRhGEiSGEcYJFmTZHuSm3tqX0hyQ3tsTnJDqy9K8quecZ/smefwJDcl2ZTkrCRp9acm2ZDk9vZ3/hRspyRpFOPZMzgXWNZbqKo3VNWSqloCXAR8qWf0HUPjquodPfWzgbcBi9tjaJmrgMurajFweXsuSZpGY4ZBVV0J3DfcuPbt/gTg/NGWkWQh8OSquqaqCjgPOL6NXg6sbcNre+qSpGnS7zGDlwP3VNXtPbWDknw3yTeTvLzV9ge29EyzpdUA9quqbW34x8B+I60sycokA0kGBgcH+2y6JGlIv2FwEo/eK9gGPLOqXgC8B/h8kiePd2Ftr6FGGX9OVS2tqqULFiyYaJslSTuY8J3OkuwB/CFw+FCtqh4EHmzD1yW5AzgE2Aoc0DP7Aa0GcE+ShVW1rXUnbZ9omyRJE9PPnsG/Bb5fVf+/+yfJgiTz2vCz6A4U39m6ge5PcmQ7znAycEmbbR2wog2v6KlLkqbJeE4tPR+4GnhOki1J3tpGnchjDxy/ArixnWr6ReAdVTV08PmdwGeATcAdwFdbfTXwyiS30wXM6olvjiRpIsbsJqqqk0aov2mY2kV0p5oON/0AcNgw9XuBo8dqhyRp6vgLZEmSYSBJMgwkSRgGkiQMA0kShoEkCcNAkoRhIEnCMJAkYRhIkjAMJEkYBpIkDANJEoaBJAnDQJKEYSBJwjCQJGEYSJIY3z2Q1yTZnuTmntrpSbYmuaE9ju0Z974km5LcluRVPfVlrbYpyaqe+kFJvtPqX0iy52RuoCRpbOPZMzgXWDZM/eNVtaQ9LgNIcihwIvDcNs/fJpmXZB7wCeDVwKHASW1agA+1ZT0b+Cnw1n42SJK088YMg6q6ErhvnMtbDlxQVQ9W1Q+BTcAR7bGpqu6sql8DFwDLkwT4A+CLbf61wPE7twmSpH71c8zg1CQ3tm6k+a22P3B3zzRbWm2k+tOAn1XVQzvUh5VkZZKBJAODg4N9NF2S1GuiYXA2cDCwBNgGnDlZDRpNVZ1TVUuraumCBQumY5WStFvYYyIzVdU9Q8NJPg18pT3dChzYM+kBrcYI9XuBfZLs0fYOeqeXJE2TCe0ZJFnY8/R1wNCZRuuAE5PsleQgYDFwLbARWNzOHNqT7iDzuqoq4Arg9W3+FcAlE2mTJGnixtwzSHI+cBSwb5ItwGnAUUmWAAVsBt4OUFW3JLkQuBV4CDilqh5uyzkVWA/MA9ZU1S1tFe8FLkjyV8B3gc9O1sZJksZnzDCoqpOGKY/4gV1VZwBnDFO/DLhsmPqddGcbSZJmiL9AliQZBpIkw0CShGEgScIwkCRhGEiSMAwkSRgGkiQMA0kShoEkiQletVQar0WrLp3pJkgaB/cMJEmGgSTJbiJp0s1k19jm1cfN2Lo1t7lnIEkyDCRJhoEkCcNAksQ4wiDJmiTbk9zcU/tIku8nuTHJxUn2afVFSX6V5Ib2+GTPPIcnuSnJpiRnJUmrPzXJhiS3t7/zp2A7JUmjGM+ewbnAsh1qG4DDqur5wA+A9/WMu6OqlrTHO3rqZwNvAxa3x9AyVwGXV9Vi4PL2XJI0jcYMg6q6Erhvh9rXq+qh9vQa4IDRlpFkIfDkqrqmqgo4Dzi+jV4OrG3Da3vqkqRpMhnHDN4CfLXn+UFJvpvkm0le3mr7A1t6ptnSagD7VdW2NvxjYL+RVpRkZZKBJAODg4OT0HRJEvQZBkneDzwEfK6VtgHPrKoXAO8BPp/kyeNdXttrqFHGn1NVS6tq6YIFC/pouSSp14R/gZzkTcBrgKPbhzhV9SDwYBu+LskdwCHAVh7dlXRAqwHck2RhVW1r3UnbJ9omSdLETGjPIMky4M+B11bVL3vqC5LMa8PPojtQfGfrBro/yZHtLKKTgUvabOuAFW14RU9dkjRNxtwzSHI+cBSwb5ItwGl0Zw/tBWxoZ4he084cegXwgSS/AR4B3lFVQwef30l3ZtIT6I4xDB1nWA1cmOStwF3ACZOyZZKkcRszDKrqpGHKnx1h2ouAi0YYNwAcNkz9XuDosdohSZo6/gJZkmQYSJIMA0kShoEkCcNAkoRhIEnCMJAkYRhIkjAMJEkYBpIkDANJEoaBJAnDQJKEYSBJwjCQJGEYSJIwDCRJGAaSJMYZBknWJNme5Oae2lOTbEhye/s7v9WT5Kwkm5LcmOSFPfOsaNPfnmRFT/3wJDe1ec5Ku7GyJGl6jHfP4Fxg2Q61VcDlVbUYuLw9B3g1sLg9VgJnQxcewGnAi4AjgNOGAqRN87ae+XZclyRpCo0rDKrqSuC+HcrLgbVteC1wfE/9vOpcA+yTZCHwKmBDVd1XVT8FNgDL2rgnV9U1VVXAeT3LkiRNg36OGexXVdva8I+B/drw/sDdPdNtabXR6luGqUuSpsmkHEBu3+hrMpY1miQrkwwkGRgcHJzq1UnSbqOfMLindfHQ/m5v9a3AgT3THdBqo9UPGKb+GFV1TlUtraqlCxYs6KPpkqRe/YTBOmDojKAVwCU99ZPbWUVHAj9v3UnrgWOSzG8Hjo8B1rdx9yc5sp1FdHLPsiRJ02CP8UyU5HzgKGDfJFvozgpaDVyY5K3AXcAJbfLLgGOBTcAvgTcDVNV9ST4IbGzTfaCqhg5Kv5PujKUnAF9tD0nSNBlXGFTVSSOMOnqYaQs4ZYTlrAHWDFMfAA4bT1skSZPPXyBLkgwDSZJhIEnCMJAkYRhIkjAMJEkYBpIkDANJEoaBJAnDQJKEYSBJwjCQJGEYSJIwDCRJGAaSJAwDSRKGgSQJw0CShGEgSaKPMEjynCQ39DzuT/LuJKcn2dpTP7Znnvcl2ZTktiSv6qkva7VNSVb1u1GSpJ2zx0RnrKrbgCUASeYBW4GLgTcDH6+qj/ZOn+RQ4ETgucAzgG8kOaSN/gTwSmALsDHJuqq6daJtkyTtnAmHwQ6OBu6oqruSjDTNcuCCqnoQ+GGSTcARbdymqroTIMkFbVrDQJKmyWQdMzgROL/n+alJbkyyJsn8VtsfuLtnmi2tNlL9MZKsTDKQZGBwcHCSmi5J6jsMkuwJvBb4+1Y6GziYrgtpG3Bmv+sYUlXnVNXSqlq6YMGCyVqsJO32JqOb6NXA9VV1D8DQX4Aknwa+0p5uBQ7sme+AVmOUuiRpGkxGN9FJ9HQRJVnYM+51wM1teB1wYpK9khwELAauBTYCi5Mc1PYyTmzTSpKmSV97BkmeSHcW0Nt7yh9OsgQoYPPQuKq6JcmFdAeGHwJOqaqH23JOBdYD84A1VXVLP+2SJO2cvsKgqv4JeNoOtTeOMv0ZwBnD1C8DLuunLZKkifMXyJIkw0CSZBhIkjAMJEkYBpIkDANJEoaBJInJu2qppFlg0apLZ2S9m1cfNyPr1eRxz0CSZBhIkgwDSRKGgSQJDyDvNmbqwKKkucE9A0mSYSBJMgwkSRgGkiQMA0kSkxAGSTYnuSnJDUkGWu2pSTYkub39nd/qSXJWkk1Jbkzywp7lrGjT355kRb/tkiSN32TtGfx+VS2pqqXt+Srg8qpaDFzengO8GljcHiuBs6ELD+A04EXAEcBpQwEiSZp6U9VNtBxY24bXAsf31M+rzjXAPkkWAq8CNlTVfVX1U2ADsGyK2iZJ2sFkhEEBX09yXZKVrbZfVW1rwz8G9mvD+wN398y7pdVGqj9KkpVJBpIMDA4OTkLTJUkwOb9AfllVbU3ydGBDku/3jqyqSlKTsB6q6hzgHIClS5dOyjIlSZOwZ1BVW9vf7cDFdH3+97TuH9rf7W3yrcCBPbMf0Goj1SVJ06CvMEjyxCRPGhoGjgFuBtYBQ2cErQAuacPrgJPbWUVHAj9v3UnrgWOSzG8Hjo9pNUnSNOi3m2g/4OIkQ8v6fFV9LclG4MIkbwXuAk5o018GHAtsAn4JvBmgqu5L8kFgY5vuA1V1X59tkySNU19hUFV3Av9qmPq9wNHD1As4ZYRlrQHW9NMeSdLE+AtkSZJhIEkyDCRJGAaSJAwDSRKGgSQJw0CShGEgScIwkCRhGEiSMAwkSRgGkiQMA0kShoEkCcNAkoRhIEnCMJAkYRhIkugjDJIcmOSKJLcmuSXJu1r99CRbk9zQHsf2zPO+JJuS3JbkVT31Za22Kcmq/jZJkrSz+rkH8kPAn1XV9UmeBFyXZEMb9/Gq+mjvxEkOBU4Engs8A/hGkkPa6E8ArwS2ABuTrKuqW/tom6RptGjVpTO27s2rj5uxde9KJhwGVbUN2NaGf5Hke8D+o8yyHLigqh4EfphkE3BEG7epqu4ESHJBm9YwkKRpMinHDJIsAl4AfKeVTk1yY5I1Sea32v7A3T2zbWm1keqSpGnSdxgk2Ru4CHh3Vd0PnA0cDCyh23M4s9919KxrZZKBJAODg4OTtVhJ2u31FQZJHk8XBJ+rqi8BVNU9VfVwVT0CfJrfdgVtBQ7smf2AVhup/hhVdU5VLa2qpQsWLOin6ZKkHv2cTRTgs8D3qupjPfWFPZO9Dri5Da8DTkyyV5KDgMXAtcBGYHGSg5LsSXeQed1E2yVJ2nn9nE30UuCNwE1Jbmi1vwBOSrIEKGAz8HaAqrolyYV0B4YfAk6pqocBkpwKrAfmAWuq6pY+2iVJ2kn9nE30f4AMM+qyUeY5AzhjmPplo80nSZpa/gJZkmQYSJIMA0kS/R1A1k6ayZ/sS9Jo3DOQJBkGkiTDQJKEYSBJwjCQJGEYSJIwDCRJ+DsDSXPcTP1+Z1e73aZ7BpIkw0CSZBhIkjAMJEkYBpIkPJtIkiZkVzuLyT0DSdLs2TNIsgz478A84DNVtXqq1uV9BSTp0WbFnkGSecAngFcDhwInJTl0ZlslSbuPWREGwBHApqq6s6p+DVwALJ/hNknSbmO2dBPtD9zd83wL8KIdJ0qyEljZnj6Q5F7gJ1PfvFljX3av7QW3eXfhNo9TPtT3en93uOJsCYNxqapzgHOGnicZqKqlM9ikabW7bS+4zbsLt3nmzZZuoq3AgT3PD2g1SdI0mC1hsBFYnOSgJHsCJwLrZrhNkrTbmBXdRFX1UJJTgfV0p5auqapbxjHrOWNPskvZ3bYX3Obdhds8w1JVM90GSdIMmy3dRJKkGWQYSJLmZhgkWZbktiSbkqya6fZMhySbk9yU5IYkAzPdnqmQZE2S7Ulu7qk9NcmGJLe3v/Nnso2TbYRtPj3J1vZe35Dk2Jls42RKcmCSK5LcmuSWJO9q9V32fR5lm2fV+zznjhm0S1f8AHgl3Y/TNgInVdWtM9qwKZZkM7C0qnbZH+YkeQXwAHBeVR3Wah8G7quq1S3451fVe2eynZNphG0+HXigqj46k22bCkkWAgur6vokTwKuA44H3sQu+j6Pss0nMIve57m4Z+ClK3ZRVXUlcN8O5eXA2ja8lu6faJcxwjbvsqpqW1Vd34Z/AXyP7goEu+z7PMo2zypzMQyGu3TFrHthp0ABX09yXbssx+5iv6ra1oZ/DOw3k42ZRqcmubF1I+0yXSa9kiwCXgB8h93kfd5hm2EWvc9zMQx2Vy+rqhfSXdn1lNa9sFuprk9zbvVrTszZwMHAEmAbcOaMtmYKJNkbuAh4d1Xd3ztuV32fh9nmWfU+z8Uw2C0vXVFVW9vf7cDFdN1lu4N7Wp/rUN/r9hluz5Srqnuq6uGqegT4NLvYe53k8XQfip+rqi+18i79Pg+3zbPtfZ6LYbDbXboiyRPbgSeSPBE4Brh59Ll2GeuAFW14BXDJDLZlWgx9KDavYxd6r5ME+Czwvar6WM+oXfZ9HmmbZ9v7POfOJgJop2D9Nb+9dMUZM9uiqZXkWXR7A9BdQuTzu+I2JzkfOIru0r73AKcBXwYuBJ4J3AWcUFW7zAHXEbb5KLqugwI2A2/v6U+f05K8DPgWcBPwSCv/BV0f+i75Po+yzScxi97nORkGkqTJNRe7iSRJk8wwkCQZBpIkw0CShGEgScIwkCRhGGiCknw8ybt7nq9P8pme52cmeU+S1+7sZcaTnJvk9ZPY3J2W5E1J/maY+tBlhz8wiet5xmQsa7ZKcnC7RPMDM90Wjcww0ER9G3gJQJLH0f1o6rk9418CXFVV66pq9Qy0byp9vKr+6yQt603AToVBkkm/d/lULHNIVd1RVUumavmaHIaBJuoq4MVt+Ll0P6X/RZL5SfYCfg+4vvcbdvvGf1aSq5LcOfTtP52/SXfDom8ATx9uhUn+Y7tByI1JLmi105P8ryRXtxujvK1n+v+cZGOb/i976n+c5Nr2bfVT7R4ZJHlzkh8kuRZ46XhehLb+tUm+leSuJH+Y5MPpbkT0tXZNGpIcnuSb7aqz65MsbNu/FPhca8sThpuuzf8PSf463Y2N3jVCW85N8skkA207XtPq85J8pOe1eHurH9XavQ4Y9n4g7VIolyb5v0luTvKGkban1Z+d5Btt+uuTHDye11Ezb8q+DWjXVlU/SvJQkmfS7QVcTXcp8RcDPwduqqpfJ9lx1oXAy4B/SXc9mi/SXZflOcChdJcuvhVYM8xqVwEHVdWDSfbpqT8fOBJ4IvDdJJcChwGL6S7+FWBduiu9DgJvAF5aVb9J8rfAf0iyAfhL4PDW/iuA747z5TgY+P3W/quBf19Vf57kYuC41p7/ASyvqsH2gXpGVb0lyanAf6qqgRYcj5kOeEtbz55VtXSMtixq23wwcEWSZwMnAz+vqn/dgvrbSb7epn8hcFhV/XCE5S0DflRVxwEkecoY7fwcsLqqLk7yO/iFc84wDNSPq+iC4CXAx+jC4CV0H6bfHmGeL7erNN6aZOia9a8Azq+qh4EfJfnfI8x7I9236C/TXbNoyCVV9SvgV0muoPswfBndBf2GPtD3pguH59N94G9sQfUEuitkvgj4h6oaBEjyBeCQ8b0MfLUFy01018v6WqvfRPfh/By6cNrQ1jmP7pLFOxprui+Moy0Xttf39iR30oXuMcDz89vjME+hey1+DVw7ShAMbcOZST4EfKWqvpXksOHame5iivtX1cUAVfXP42ivZgnDQP0YOm7wPLpuoruBPwPuB/7nCPM82DP8mN2GMRxHFxz/Dnh/kue1+o4X2Kq27P9WVZ/qHZHkT4G1VfW+HerH72Rbej0IUFWPJPlN/faCX4/Q/Y8FuKWqXjzSAoaaMcZ0/zSOtoz0WvxpVa1/1MqSo8ZaZlX9IMkLgWOBv0pyOd1FEx/TzhYGmqPchVM/rgJeQ3fv2ofbVSb3oesqumonlnMl8IbWt72QrsvlUdIdpD6wqq4A3kv37XbvNnp5kt9J8jS6K35uBNYDb0l3QxGS7J/k6cDlwOvb8NCN2H+X7qqZ/ybJ01o3yB/tzAsxhtuABUle3Nb5+CRDB9t/ATxpHNON1x8leVzrq39WW+Z64E96jl8cku5S6GNKd6bTL6vq74CP0HUrDdvOdkvHLUPBmmSvJP9iJ9uvGeKegfpxE91ZRJ/fobZ3Vf1kJ5ZzMfAHdMcK/pGu331H84C/S/IUum+6Z1XVz1o3xY10ffz7Ah+sqh/RdTf9HnB1m+YB4I+r6tYk/4XuFqKPA34DnFJV16S7Ef3VwM+AG3ai/aNqx05eD5zV2r8H3SXYbwHOBT6Z5Fd0ITrSdOP1j8C1wJOBd1TVP6c75XcR3QH90B03OX6cy3se8JEkj9C9Vn8yxva8EfhUulNvf0MXqnfuRPs1Q7yEtea09gH+QFV9dFdc385Ici5dv/4XZ7otw0nyQFXtPfaUmgl2E0k75wFgZSbpR2e7g7QfndHdvEezlHsG0hyT5P089pjG3/dz97t2vOXyYUYdXVX3TnS5mjsMA0mS3USSJMNAkoRhIEnCMJAkAf8PAkyyd4dwJvwAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ws2 = ds.Wind_speed.copy()\n",
    "ws2.plot.hist();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Make some modifications"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ws2.values = np.clip(ws2.values, 1,18)\n",
    "ws2.plot.hist();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. Assign it to a new name in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds[\"Wind speed 2\"] = ws2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mikeio.Dataset>\n",
       "dims: (time:67, element:958)\n",
       "time: 2017-10-27 00:00:00 - 2017-10-29 18:00:00 (67 records)\n",
       "geometry: Dfsu2D (958 elements, 570 nodes)\n",
       "items:\n",
       "  0:  Surface elevation <Surface Elevation> (meter)\n",
       "  1:  Wind speed <Wind speed> (meter per sec)\n",
       "  2:  Wind speed 2 <Wind speed> (meter per sec)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Reorder items if necessary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mikeio.Dataset>\n",
       "dims: (time:67, element:958)\n",
       "time: 2017-10-27 00:00:00 - 2017-10-29 18:00:00 (67 records)\n",
       "geometry: Dfsu2D (958 elements, 570 nodes)\n",
       "items:\n",
       "  0:  Wind speed 2 <Wind speed> (meter per sec)\n",
       "  1:  Surface elevation <Surface Elevation> (meter)\n",
       "  2:  Wind speed <Wind speed> (meter per sec)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds2 = ds[[\"Wind speed 2\",\"Surface elevation\", \"Wind speed\"]]\n",
    "ds2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds2.to_dfs(\"modified.dfsu\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "9f8901c748ef3afaefd0447d5e27e03ab26b5b9cbaa046ec14504d27e1b48e82"
  },
  "kernelspec": {
   "display_name": "Python 3.9.6 64-bit",
   "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": "3.9.6"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}