La tacuen

Cafeteros .ipynb

{
 "cells": [
  {
   "cell_type": "code",
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   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lista de deudores del Caldo de Gallina "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "cafeteros = pd.DataFrame({\n",
    "    \"Nombres\": [\"Renzo\",\"J Guillermo\",\"Fabricio\",\"Diego\",\"Carlos\",\"Fernando\",\"Halley\"],\n",
    "    \"Alias\": [\"Telenta\",\"Guishe\",\"Fabric\",\"Mr. D\",\"Charlitos\",\"Nando\",\"Cometa\"],\n",
    "    \"Monto\": [10,10,10,10,13,10,10],\n",
    "    \"Estado\": [\"Pago\",\"Debe\",\"Debe\",\"Pago\",\"Debe\",\"Debe\",\"Debe\"]\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nombres</th>\n",
       "      <th>Alias</th>\n",
       "      <th>Monto</th>\n",
       "      <th>Estado</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>J Guillermo</td>\n",
       "      <td>Guishe</td>\n",
       "      <td>10</td>\n",
       "      <td>Debe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Fabricio</td>\n",
       "      <td>Fabric</td>\n",
       "      <td>10</td>\n",
       "      <td>Debe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Carlos</td>\n",
       "      <td>Charlitos</td>\n",
       "      <td>13</td>\n",
       "      <td>Debe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Fernando</td>\n",
       "      <td>Nando</td>\n",
       "      <td>10</td>\n",
       "      <td>Debe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Halley</td>\n",
       "      <td>Cometa</td>\n",
       "      <td>10</td>\n",
       "      <td>Debe</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Nombres      Alias  Monto Estado\n",
       "1  J Guillermo     Guishe     10   Debe\n",
       "2     Fabricio     Fabric     10   Debe\n",
       "4       Carlos  Charlitos     13   Debe\n",
       "5     Fernando      Nando     10   Debe\n",
       "6       Halley     Cometa     10   Debe"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cafeteros.loc[cafeteros['Estado'] == \"Debe\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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