{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "<div style=\"text-align: center; margin-bottom: 15px;\">\n",
    "        <a href=\"https://colab.research.google.com/github/wisaaco/TallerPythonFEE/blob/main/notebooks/4_PandasModificacio.ipynb\" target=\"_blank\">\n",
    "            <img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\" style=\"height: 40px; transition: transform 0.2s ease;\" onmouseover=\"this.style.transform='scale(1.05)'\" onmouseout=\"this.style.transform='scale(1)'\">\n",
    "        </a>\n",
    "</div>\n",
    "<div style=\"background: rgba(255,255,255,0.1); padding: 15px; border-radius: 8px; border-left: 4px solid #ffd700;\">\n",
    "        <p style=\"margin: 0; color: white; font-size: 13px; line-height: 1.4;\">\n",
    "            <strong>💡 Si el botó no funciona:</strong> Copia i enganxa aquesta URL al teu navegador:<br>\n",
    "            <code style=\"background: rgba(0, 0, 0, 0.01); padding: 5px 8px; border-radius: 4px; font-size: 12px; word-break: break-all;\">\n",
    "https://colab.research.google.com/github/wisaaco/TallerPythonFEE/blob/main/notebooks/4_PandasModificacio.ipynb\n",
    "           </code>\n",
    "    </p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Unitat 4. Modificació\n",
    "A més de fer seleccions, en alguns moments necessitarem incorporar nova informació a les nostres taules de dades.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df2 = pd.DataFrame([('Foreign Cinema', 'Restaurant', 289.0),\n",
    "                   ('Liho Liho', 'Restaurant', 224.0),\n",
    "                   ('500 Club', 'bar', 80.5),\n",
    "                   ('The Square', 'bar', 25.30)],\n",
    "           columns=('name', 'type', 'AvgBill')\n",
    "                 )\n",
    "df2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Afegir columnes\n",
    "\n",
    "Tenim diverses maneres d'afegir columnes a un _dataFrame_:\n",
    "\n",
    "- Mitjançant el nom de la columna que volem afegir, tal com afegim una clau nova a un diccionari.\n",
    "- `insert`: és un mètode que necessita 3 paràmetres. La posició on volem afegir la columna (`loc`), el seu nom (`column`) i la llista de valors (`value`).\n",
    "- `assign`: molt semblant a l'anterior, però permet afegir múltiples columnes.\n",
    "\n",
    "Vegem-ne alguns exemples:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df2['Day'] = \"Monday\" # Com un diccionari\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df2['Day'] = ['Monday', 'Tuesday', 'Wednesday', 'Thursday']\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Emprarem el mètode insert. Indicant on volem inserir aquesta columna amb el paràmetre loc\n",
    "\n",
    "df2.insert(loc=1, column=\"Stars\", value=[2,2,3,4])\n",
    "df2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "El mètode `assing` permet afegir múltiples columnes en una sola operació. És interessant veure que la columna anomenada _AvgHalfBill_ és el resultat de dividir una columna entre 2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df3 = df2.assign(AvgHalfBill=df2.AvgBill / 2, Michelin_Star=3)\n",
    "df3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Afegir files\n",
    "\n",
    "Per afegir files a un _dataframe_ tenim\n",
    "\n",
    "- `concat`: concatena dos o més _dataFrames_ separats per comes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_files = df2.copy() # Fem una còpia de tota la informació\n",
    "\n",
    "#Cream un diccionari\n",
    "fila = {\"name\":\"Isaacs\", \"type\":\"bar\" ,\"AvgBill\":[148.2], \"day\":\"Friday\"}\n",
    "\n",
    "nou_df = pd.concat([df_files, pd.DataFrame(fila)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "nou_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Eliminar columnes i files\n",
    "\n",
    "Molts cops tendrem la necessitat d'eliminar informació que no ens és interessant.\n",
    "\n",
    "### Columnes\n",
    "\n",
    "Tenim el mètode `drop` que ens proporciona un nou _dataFrame_ sense la(es) fila(es) o la(les) columna(es) que seleccionem.\n",
    "Si volem eliminar columnes podem fer-ho especificant la llista de columnes al paràmetre `columns` de la següent manera:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_no_michelin = df3.drop(columns=[\"Michelin_Star\"]) # Eliminamos la última columna que hemos creado\n",
    "df_no_michelin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Anem a veure com ha quedat el dataframe del qual hem eliminat una columna:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Files\n",
    "Per poder eliminar files, fem servir la mateixa funció `drop`, aquesta vegada sense el paràmetre que hem fet servir anteriorment, simplement indiquem els índexs a eliminar:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_less_rows = df_no_michelin.drop([1,3])\n",
    "df_less_rows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Feines\n",
    "Fer l'activitat 1.2 del _homework_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "my3110",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "3.11.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}