C02.6 Pandas (Uniones de tablas).ipynb

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   "source": [
    "# Concatenados y uniones\n",
    "\n",
    "Generalmente las bases de datos están formadas por diversas tablas donde la información está repartida. En esta sección aprenderemos a relacionar tablas entre sí.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Concatenación\n",
    "\n",
    "Supongamos que tenemos dos dataframes:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.DataFrame({\n",
    "    \"A\":[\"A0\",\"A1\",\"A2\",\"A3\"],\n",
    "    \"B\":[\"B0\",\"B1\",\"B2\",\"B3\"],\n",
    "    \"C\":[\"C0\",\"C1\",\"C2\",\"C3\"],\n",
    "    \"D\":[\"D0\",\"D1\",\"D2\",\"D3\"],\n",
    "})\n",
    "\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.DataFrame({\n",
    "    \"A\":[\"A4\",\"A5\",\"A6\",\"A7\"],\n",
    "    \"B\":[\"B4\",\"B5\",\"B6\",\"B7\"],\n",
    "    \"C\":[\"C4\",\"C5\",\"C6\",\"C7\"],\n",
    "    \"D\":[\"D4\",\"D5\",\"D6\",\"D7\"],\n",
    "})\n",
    "\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = pd.DataFrame({\n",
    "    \"A\":[\"A8\",\"A9\",\"A10\",\"A11\",\"A12\"],\n",
    "    \"B\":[\"B8\",\"B9\",\"B10\",\"B11\",\"B12\"],\n",
    "    \"C\":[\"C8\",\"C9\",\"C10\",\"C11\",\"C12\"],\n",
    "    })\n",
    "\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cocatenamos por columnas\n",
    "\n",
    "df_columnas = pd.concat([df1,df2,df3],axis = 0,keys = [\"df1\",\"df2\",\"df3\"])\n",
    "df_columnas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_columnas.loc[\"df2\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_filas = pd.concat([df1,df2,df3],axis = 1,keys = [\"df1\",\"df2\",\"df3\"])\n",
    "df_filas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3.index = [2,5,3,4,10]\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_filas = pd.concat([df1,df2,df3],axis = 1,keys = [\"df1\",\"df2\",\"df3\"])\n",
    "df_filas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Joins\n",
    "\n",
    "Veremos ahora una forma muy importante de relacionar tablas en una base de datos.\n",
    "\n",
    "<img src=\"joins.png\" width=\"400\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "izquierda = pd.DataFrame({\n",
    "    \"A\":[\"A0\",\"A1\",\"A2\",\"A3\"],\n",
    "    \"B\":[\"B0\",\"B1\",\"B2\",\"B3\"],\n",
    "    \"C\":[\"C0\",\"C1\",\"C2\",\"C3\"],\n",
    "    },index = [\"clv0\",\"clv1\",\"clv2\",\"clv3\"])\n",
    "\n",
    "derecha = pd.DataFrame({\n",
    "    \"D\":[\"D0\",\"D1\",\"D2\",\"D3\",\"D4\"],\n",
    "    \"E\":[\"E0\",\"E1\",\"E2\",\"E3\",\"E4\"]\n",
    "    },index = [\"clv0\",\"clv2\",\"clv1\",\"clv5\",\"clv6\"])"
   ]
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   "execution_count": null,
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    "izquierda"
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   "execution_count": null,
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    "derecha"
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   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "izquierda[\"Id\"] = izquierda.index\n",
    "derecha[\"Id\"] = derecha.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": [
    "derecha"
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   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "join_interno = izquierda.join(derecha.set_index([\"Id\"]),on = [\"Id\"],how = \"inner\")\n",
    "join_interno"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "join_izquierdo = izquierda.join(derecha.set_index([\"Id\"]),on = [\"Id\"],how = \"left\")\n",
    "join_izquierdo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "join_derecho = izquierda.join(derecha.set_index([\"Id\"]),on = [\"Id\"],how = \"right\")\n",
    "join_derecho"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "join_completo = izquierda.join(derecha.set_index([\"Id\"]),on = [\"Id\"],how = \"outer\")\n",
    "join_completo"
   ]
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