diff --git a/Ejemplo_nacimientos_2005_2010/Demo_CDS_nacimientos.ipynb b/Ejemplo_nacimientos_2005_2010/Demo_CDS_nacimientos.ipynb
index c1a696c06f161d61de8c53951ba94785c1430cea..0c55c795f575af3af6aaf128301a789a7bc8509e 100644
--- a/Ejemplo_nacimientos_2005_2010/Demo_CDS_nacimientos.ipynb
+++ b/Ejemplo_nacimientos_2005_2010/Demo_CDS_nacimientos.ipynb
@@ -49,7 +49,7 @@
         "\n",
         "![image.png](data:image/png;base64,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)\n",
         "\n",
-        "Nosotros la vamos a usar para obtener ciertas columnas y no vamos a cortar filas.\n",
+        "Nosotros la vamos a usar para obtener ciertas columnas y no vamos a cortar filas, para esto se dejan los lugares al lado de los dos puntos vacíos.\n",
         "\n",
         "#groupby\n",
         "\n",
@@ -83,7 +83,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 1,
+      "execution_count": null,
       "metadata": {
         "id": "gSPpdLmni-mZ"
       },
@@ -110,7 +110,7 @@
       "metadata": {
         "id": "oanfaLLOvlVG"
       },
-      "execution_count": 2,
+      "execution_count": null,
       "outputs": []
     },
     {
@@ -133,9 +133,9 @@
           "base_uri": "https://localhost:8080/",
           "height": 357
         },
-        "outputId": "2eb9a0e0-8d5e-44f0-b0c2-725d60a3541c"
+        "outputId": "91c1ca7e-6677-4cc4-9e06-57c461fc8374"
       },
-      "execution_count": 3,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -171,7 +171,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-e1694405-9f86-4fea-afbc-9cc70615b28d\">\n",
+              "  <div id=\"df-7d1de1c7-2522-413e-8c0b-0556d63b74ba\">\n",
               "    <div class=\"colab-df-container\">\n",
               "      <div>\n",
               "<style scoped>\n",
@@ -278,7 +278,7 @@
               "  </tbody>\n",
               "</table>\n",
               "</div>\n",
-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e1694405-9f86-4fea-afbc-9cc70615b28d')\"\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7d1de1c7-2522-413e-8c0b-0556d63b74ba')\"\n",
               "              title=\"Convert this dataframe to an interactive table.\"\n",
               "              style=\"display:none;\">\n",
               "        \n",
@@ -329,12 +329,12 @@
               "\n",
               "      <script>\n",
               "        const buttonEl =\n",
-              "          document.querySelector('#df-e1694405-9f86-4fea-afbc-9cc70615b28d button.colab-df-convert');\n",
+              "          document.querySelector('#df-7d1de1c7-2522-413e-8c0b-0556d63b74ba button.colab-df-convert');\n",
               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-e1694405-9f86-4fea-afbc-9cc70615b28d');\n",
+              "          const element = document.querySelector('#df-7d1de1c7-2522-413e-8c0b-0556d63b74ba');\n",
               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -378,7 +378,7 @@
       "metadata": {
         "id": "Z9xxlqmM6kc4"
       },
-      "execution_count": 4,
+      "execution_count": null,
       "outputs": []
     },
     {
@@ -412,9 +412,9 @@
           "base_uri": "https://localhost:8080/",
           "height": 206
         },
-        "outputId": "9e0a9c67-e861-472a-8ef6-35baba76faab"
+        "outputId": "c2f2eca1-7814-459a-92c7-2312ceef12ae"
       },
-      "execution_count": 5,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -429,7 +429,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-e4ca5b3d-84c1-40f3-9d8f-3bfed5c4a12c\">\n",
+              "  <div id=\"df-1c18a0aa-fc47-4743-a828-ca1c66a0a37a\">\n",
               "    <div class=\"colab-df-container\">\n",
               "      <div>\n",
               "<style scoped>\n",
@@ -482,7 +482,7 @@
               "  </tbody>\n",
               "</table>\n",
               "</div>\n",
-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e4ca5b3d-84c1-40f3-9d8f-3bfed5c4a12c')\"\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1c18a0aa-fc47-4743-a828-ca1c66a0a37a')\"\n",
               "              title=\"Convert this dataframe to an interactive table.\"\n",
               "              style=\"display:none;\">\n",
               "        \n",
@@ -533,12 +533,12 @@
               "\n",
               "      <script>\n",
               "        const buttonEl =\n",
-              "          document.querySelector('#df-e4ca5b3d-84c1-40f3-9d8f-3bfed5c4a12c button.colab-df-convert');\n",
+              "          document.querySelector('#df-1c18a0aa-fc47-4743-a828-ca1c66a0a37a button.colab-df-convert');\n",
               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-e4ca5b3d-84c1-40f3-9d8f-3bfed5c4a12c');\n",
+              "          const element = document.querySelector('#df-1c18a0aa-fc47-4743-a828-ca1c66a0a37a');\n",
               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -586,9 +586,9 @@
           "height": 238
         },
         "id": "FbY9_hRmBDuW",
-        "outputId": "63555275-1f63-4f83-9b10-793b172deb15"
+        "outputId": "d998fa9e-dd17-4c9c-b6e1-20d89040609c"
       },
-      "execution_count": 6,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -604,7 +604,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-77b868b6-29e8-463f-980b-f45fcf4ae3ff\">\n",
+              "  <div id=\"df-142cde35-e705-451d-bdd0-6106b0147265\">\n",
               "    <div class=\"colab-df-container\">\n",
               "      <div>\n",
               "<style scoped>\n",
@@ -655,7 +655,7 @@
               "  </tbody>\n",
               "</table>\n",
               "</div>\n",
-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-77b868b6-29e8-463f-980b-f45fcf4ae3ff')\"\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-142cde35-e705-451d-bdd0-6106b0147265')\"\n",
               "              title=\"Convert this dataframe to an interactive table.\"\n",
               "              style=\"display:none;\">\n",
               "        \n",
@@ -706,12 +706,12 @@
               "\n",
               "      <script>\n",
               "        const buttonEl =\n",
-              "          document.querySelector('#df-77b868b6-29e8-463f-980b-f45fcf4ae3ff button.colab-df-convert');\n",
+              "          document.querySelector('#df-142cde35-e705-451d-bdd0-6106b0147265 button.colab-df-convert');\n",
               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-77b868b6-29e8-463f-980b-f45fcf4ae3ff');\n",
+              "          const element = document.querySelector('#df-142cde35-e705-451d-bdd0-6106b0147265');\n",
               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -760,15 +760,15 @@
           "base_uri": "https://localhost:8080/",
           "height": 459
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-        "outputId": "3e79072f-6636-4bd8-c7a8-53e00888fb5a"
+        "outputId": "c992d64b-5c86-461f-a177-b7b2267985a3"
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       "outputs": [
         {
           "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "<matplotlib.legend.Legend at 0x7f410a37e150>"
+              "<matplotlib.legend.Legend at 0x7fb578ea6e10>"
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@@ -810,15 +810,15 @@
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         {
           "output_type": "execute_result",
           "data": {
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-              "<matplotlib.legend.Legend at 0x7f410a25f8d0>"
+              "<matplotlib.legend.Legend at 0x7fb578d6e390>"
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@@ -864,7 +864,7 @@
       "metadata": {
         "id": "glA4XLTT86wg"
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-      "execution_count": 9,
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     {
@@ -884,7 +884,7 @@
       "metadata": {
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-      "execution_count": 10,
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@@ -908,9 +908,9 @@
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@@ -926,7 +926,7 @@
             ],
             "text/html": [
               "\n",
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@@ -980,7 +980,7 @@
               "  </tbody>\n",
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-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4c53efc7-6bfd-410d-87a6-77f248590026')\"\n",
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@@ -1031,12 +1031,12 @@
               "\n",
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-              "          document.querySelector('#df-4c53efc7-6bfd-410d-87a6-77f248590026 button.colab-df-convert');\n",
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               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
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               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -1084,9 +1084,9 @@
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@@ -1112,7 +1112,7 @@
             ],
             "text/html": [
               "\n",
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@@ -1220,7 +1220,7 @@
               "  </tbody>\n",
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-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-980e42d5-acf7-48de-8355-91402ac243b6')\"\n",
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@@ -1271,12 +1271,12 @@
               "\n",
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               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
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               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -1321,18 +1321,18 @@
       "metadata": {
         "colab": {
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         {
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           "data": {
             "text/plain": [
-              "<matplotlib.legend.Legend at 0x7f4109d19dd0>"
+              "<matplotlib.legend.Legend at 0x7fb57882c110>"
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@@ -1379,7 +1379,7 @@
       "metadata": {
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     {
@@ -1399,7 +1399,7 @@
       "metadata": {
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@@ -1423,9 +1423,9 @@
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@@ -1438,7 +1438,7 @@
             ],
             "text/html": [
               "\n",
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@@ -1477,7 +1477,7 @@
               "  </tbody>\n",
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@@ -1528,12 +1528,12 @@
               "\n",
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               "        const buttonEl =\n",
-              "          document.querySelector('#df-fd245acd-1b8b-450e-aa88-f6d8315a5067 button.colab-df-convert');\n",
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               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-fd245acd-1b8b-450e-aa88-f6d8315a5067');\n",
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               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -1581,9 +1581,9 @@
           "height": 143
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       "outputs": [
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@@ -1596,7 +1596,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-855c79c2-a37a-493f-815f-f45d40225ca4\">\n",
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               "    <div class=\"colab-df-container\">\n",
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@@ -1635,7 +1635,7 @@
               "  </tbody>\n",
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-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-855c79c2-a37a-493f-815f-f45d40225ca4')\"\n",
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               "              title=\"Convert this dataframe to an interactive table.\"\n",
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@@ -1686,12 +1686,12 @@
               "\n",
               "      <script>\n",
               "        const buttonEl =\n",
-              "          document.querySelector('#df-855c79c2-a37a-493f-815f-f45d40225ca4 button.colab-df-convert');\n",
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               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-855c79c2-a37a-493f-815f-f45d40225ca4');\n",
+              "          const element = document.querySelector('#df-c71c4cb1-cea1-48d3-8439-2f4bdf0adda1');\n",
               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -1739,15 +1739,15 @@
           "base_uri": "https://localhost:8080/",
           "height": 879
         },
-        "outputId": "a3969900-f8f3-4a4a-8f59-f58742025aa3"
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-      "execution_count": 18,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "<matplotlib.legend.Legend at 0x7f4109cbc810>"
+              "<matplotlib.legend.Legend at 0x7fb5787ce990>"
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@@ -1795,9 +1795,9 @@
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       "outputs": [
         {
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@@ -1812,7 +1812,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-d1ab74c6-68f7-4347-842d-9635d531afbd\">\n",
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               "    <div class=\"colab-df-container\">\n",
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@@ -1871,7 +1871,7 @@
               "  </tbody>\n",
               "</table>\n",
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-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d1ab74c6-68f7-4347-842d-9635d531afbd')\"\n",
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               "              title=\"Convert this dataframe to an interactive table.\"\n",
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               "        \n",
@@ -1922,12 +1922,12 @@
               "\n",
               "      <script>\n",
               "        const buttonEl =\n",
-              "          document.querySelector('#df-d1ab74c6-68f7-4347-842d-9635d531afbd button.colab-df-convert');\n",
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               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-d1ab74c6-68f7-4347-842d-9635d531afbd');\n",
+              "          const element = document.querySelector('#df-febd9050-c339-440e-bbba-1d647cfda90d');\n",
               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -1973,12 +1973,12 @@
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 206
+          "height": 215
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         "id": "don6Rac5TPkY",
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+        "outputId": "bcba689b-0288-4564-e8ff-76b9367d6121"
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-      "execution_count": 20,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -1993,7 +1993,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-ba440466-a30c-4cad-af18-52e08d309203\">\n",
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               "    <div class=\"colab-df-container\">\n",
               "      <div>\n",
               "<style scoped>\n",
@@ -2052,7 +2052,7 @@
               "  </tbody>\n",
               "</table>\n",
               "</div>\n",
-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ba440466-a30c-4cad-af18-52e08d309203')\"\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f3bf9808-69b0-42d6-8ec8-7f23ed41b02c')\"\n",
               "              title=\"Convert this dataframe to an interactive table.\"\n",
               "              style=\"display:none;\">\n",
               "        \n",
@@ -2103,12 +2103,12 @@
               "\n",
               "      <script>\n",
               "        const buttonEl =\n",
-              "          document.querySelector('#df-ba440466-a30c-4cad-af18-52e08d309203 button.colab-df-convert');\n",
+              "          document.querySelector('#df-f3bf9808-69b0-42d6-8ec8-7f23ed41b02c button.colab-df-convert');\n",
               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-ba440466-a30c-4cad-af18-52e08d309203');\n",
+              "          const element = document.querySelector('#df-f3bf9808-69b0-42d6-8ec8-7f23ed41b02c');\n",
               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -2156,9 +2156,9 @@
           "height": 238
         },
         "id": "0oQCwFn2TSd5",
-        "outputId": "66d8920f-2e9d-48f1-d6b8-abfa7d0de2a2"
+        "outputId": "8ade4190-9f50-4ef9-8d2c-50776ae80bcf"
       },
-      "execution_count": 21,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -2174,7 +2174,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-beae7ea2-8b01-42de-9372-475013eeb418\">\n",
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               "    <div class=\"colab-df-container\">\n",
               "      <div>\n",
               "<style scoped>\n",
@@ -2228,7 +2228,7 @@
               "  </tbody>\n",
               "</table>\n",
               "</div>\n",
-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-beae7ea2-8b01-42de-9372-475013eeb418')\"\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-26b14687-8de9-4394-864e-6d07365b3aab')\"\n",
               "              title=\"Convert this dataframe to an interactive table.\"\n",
               "              style=\"display:none;\">\n",
               "        \n",
@@ -2279,12 +2279,12 @@
               "\n",
               "      <script>\n",
               "        const buttonEl =\n",
-              "          document.querySelector('#df-beae7ea2-8b01-42de-9372-475013eeb418 button.colab-df-convert');\n",
+              "          document.querySelector('#df-26b14687-8de9-4394-864e-6d07365b3aab button.colab-df-convert');\n",
               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-beae7ea2-8b01-42de-9372-475013eeb418');\n",
+              "          const element = document.querySelector('#df-26b14687-8de9-4394-864e-6d07365b3aab');\n",
               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -2332,9 +2332,9 @@
           "height": 269
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         "id": "hHta7iM9T0B2",
-        "outputId": "4800091b-82d7-4679-c223-1858cf69cdaa"
+        "outputId": "4017426a-ab33-47e4-ad10-d70045e890d6"
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-      "execution_count": 22,
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       "outputs": [
         {
           "output_type": "execute_result",
@@ -2360,7 +2360,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-1dd72794-d713-4ffd-83fa-201567dcf36b\">\n",
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               "    <div class=\"colab-df-container\">\n",
               "      <div>\n",
               "<style scoped>\n",
@@ -2468,7 +2468,7 @@
               "  </tbody>\n",
               "</table>\n",
               "</div>\n",
-              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1dd72794-d713-4ffd-83fa-201567dcf36b')\"\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6ff622db-99e1-46aa-a35a-416ebcc0b585')\"\n",
               "              title=\"Convert this dataframe to an interactive table.\"\n",
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               "        \n",
@@ -2519,12 +2519,12 @@
               "\n",
               "      <script>\n",
               "        const buttonEl =\n",
-              "          document.querySelector('#df-1dd72794-d713-4ffd-83fa-201567dcf36b button.colab-df-convert');\n",
+              "          document.querySelector('#df-6ff622db-99e1-46aa-a35a-416ebcc0b585 button.colab-df-convert');\n",
               "        buttonEl.style.display =\n",
               "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "        async function convertToInteractive(key) {\n",
-              "          const element = document.querySelector('#df-1dd72794-d713-4ffd-83fa-201567dcf36b');\n",
+              "          const element = document.querySelector('#df-6ff622db-99e1-46aa-a35a-416ebcc0b585');\n",
               "          const dataTable =\n",
               "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                     [key], {});\n",
@@ -2570,17 +2570,17 @@
         "id": "bf6v9x7gAwku",
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 725
+          "height": 946
         },
-        "outputId": "aa1e3e8d-a00d-4745-f892-892e42bedc49"
+        "outputId": "7f8bec90-7f0c-462d-877f-42317d86ee19"
       },
-      "execution_count": 23,
+      "execution_count": null,
       "outputs": [
         {
           "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "<matplotlib.legend.Legend at 0x7f4108425fd0>"
+              "<matplotlib.legend.Legend at 0x7fb576ec7650>"
             ]
           },
           "metadata": {},
diff --git a/ejemplos-jupyter/Ejemplo_Nutricion/EjemploNutricion.ipynb b/ejemplos-jupyter/Ejemplo_Nutricion/EjemploNutricion.ipynb
index f0d47002edb1be2d8d49af8245d672e7c238f9ba..d338a1524f0e801a20d799c59d11b7cebbf9bdb8 100644
--- a/ejemplos-jupyter/Ejemplo_Nutricion/EjemploNutricion.ipynb
+++ b/ejemplos-jupyter/Ejemplo_Nutricion/EjemploNutricion.ipynb
@@ -470,7 +470,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "id": "337dfd9e",
    "metadata": {},
    "outputs": [
@@ -480,7 +480,7 @@
        "(8618, 45)"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -499,7 +499,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "id": "dd1a163c",
    "metadata": {
     "scrolled": true
@@ -521,7 +521,7 @@
        "      dtype='object')"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -532,9 +532,145 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c3a07104",
+   "id": "e8366b10",
    "metadata": {},
-   "source": []
+   "source": [
+    "## Realizamos nuestro primer grafico usando MatPlotLib"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53d6cd80",
+   "metadata": {},
+   "source": [
+    "Ahora realicemos un grafico para poder saber la proporcion de grupos de alimentos que hay en este dataset\n",
+    "Para esto, primero debemos importar la libreria que nos va a facilitar la realizacion de estos graficos.\n",
+    "Esta libreria se llama MatPlotLib, y es una de las mas conocidas dentro de Python para realizar distintos tipos de graficos.\n",
+    "\n",
+    "Se importa de la siguiente forma:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "551b3ef4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib import pyplot as plt #Esta linea basicamente significa: \"De matplotlib(libreria),\n",
+    "                                    #traeme solamente pyplot(la parte que usaremos de la libreria), y nombrala como plt\n",
+    "                                    # (por lo que cada vez que quiera usar esta parte de la libreria, lo voy a invocar como plt)\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a0859e5f",
+   "metadata": {},
+   "source": [
+    "Primero, agrupamos los elementos con los que vamos a trabajar para realizar el grafico. En este caso, yo quiero ver la proporcion de grupos de alimentos en el dataset. Por lo que voy a contar cuantos alimentos pertenecen a cada grupo"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "94540e23",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Beef Products                          946\n",
+       "Vegetables and Vegetable Products      828\n",
+       "Baked Products                         797\n",
+       "Soups, Sauces, and Gravies             452\n",
+       "Lamb, Veal, and Game Products          438\n",
+       "Poultry Products                       390\n",
+       "Legumes and Legume Products            389\n",
+       "Fast Foods                             371\n",
+       "Breakfast Cereals                      363\n",
+       "Baby Foods                             362\n",
+       "Sweets                                 347\n",
+       "Fruits and Fruit Juices                346\n",
+       "Pork Products                          343\n",
+       "Beverages                              315\n",
+       "Finfish and Shellfish Products         267\n",
+       "Dairy and Egg Products                 264\n",
+       "Sausages and Luncheon Meats            244\n",
+       "Fats and Oils                          219\n",
+       "Cereal Grains and Pasta                183\n",
+       "Snacks                                 171\n",
+       "American Indian/Alaska Native Foods    165\n",
+       "Nut and Seed Products                  133\n",
+       "Meals, Entrees, and Side Dishes        113\n",
+       "Restaurant Foods                       108\n",
+       "Spices and Herbs                        64\n",
+       "Name: FoodGroup, dtype: int64"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "proporcion=df['FoodGroup'].value_counts() #cuento cuantos alimentos pertenecen a cada grupo de alimentos\n",
+    "proporcion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fe02a389",
+   "metadata": {},
+   "source": [
+    "Ahora vamos a separar los valores que necesitamos para hacer el grafico. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "55b80832",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'PROPORCION DE GRUPOS DE COMIDAS')"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "proporcion=df['FoodGroup'].value_counts() #cuento cuantos alimentos pertenecen a cada grupo de alimentos\n",
+    "\n",
+    "data=proporcion.values #guardo la cantidad de veces que aparece cada elemento\n",
+    "keys=proporcion.keys() #guardo el nombre de los grupo de alimentos\n",
+    "explode=[1 for i in range(0,25)] #agrego en una lista 25 veces el valor 1 (que sera la separacion entre las partes de la torta)\n",
+    "plt.pie(data,explode=explode,shadow=True, autopct='%1.1f%%', labeldistance=5) #asigno los valores que defini previamente\n",
+    "plt.legend(keys, bbox_to_anchor=(1,0)) #determino como se veran las claves\n",
+    "plt.title('PROPORCION DE GRUPOS DE COMIDAS') #Asigno el titulo del grafico\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3c8b92b6",
+   "metadata": {},
+   "source": [
+    "## Filtrando elementos y generando un nuevo archivo"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -1583,17 +1719,17 @@
    "metadata": {},
    "source": [
     "### Agrupando\n",
-    "Si yo quiero saber el promedio de grasa de cada grupo de alimentos puedo hacerlo de la siguiente forma:"
+    "Si yo quiero saber el promedio de proteinas de cada grupo de alimentos puedo hacerlo de la siguiente forma:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 55,
    "id": "1f1e84ae",
    "metadata": {},
    "outputs": [],
    "source": [
-    "grouped=df.groupby(\"FoodGroup\").agg({'Fat_g':'mean'}) #agg es la funcion para aplicar a cada columna la operacion que deseemos"
+    "grouped=df.groupby(\"FoodGroup\").agg({'Protein_g':'mean'}) #agg es la funcion para aplicar a cada columna la operacion que deseemos"
    ]
   },
   {
@@ -1601,12 +1737,12 @@
    "id": "373d4fb7",
    "metadata": {},
    "source": [
-    "Lo que estoy haciendo aca, es que con el groupby elijo el criterio por el cual voy a agrupar a los elementos, y luego con la funcion agg indico que quiero que de la grasa me informe el promedio. Los elementos se pueden agrupar por el elemento que quiera y en vez de indicar el promedio de grasa, podria haber decidido indicar la suma total de grasa de todos los productos de un mismo grupo. Ej:"
+    "Lo que estoy haciendo aca, es que con el groupby elijo el criterio por el cual voy a agrupar a los elementos, y luego con la funcion agg indico que quiero que de la grasa me informe el promedio. Los elementos se pueden agrupar por el elemento que quiera y en vez de indicar el promedio de proteina, podria haber decidido indicar la suma total de grasa de todos los productos de un mismo grupo. Ej:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 56,
    "id": "a1dc092f",
    "metadata": {},
    "outputs": [],
@@ -1626,7 +1762,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 57,
    "id": "16222dfc",
    "metadata": {},
    "outputs": [
@@ -1820,7 +1956,7 @@
        "Vegetables and Vegetable Products      815.77      57.47"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 57,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1830,6 +1966,47 @@
     "                                                                            #la cantidad de proteinas maxima por grupo de alimentos"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "6caae58d",
+   "metadata": {},
+   "source": [
+    "Ahora vamos a realizar otro tipo de grafico a partir de la agrupacion que realizamos por grupo de alimento, comparando el promedio de proteina entre cada grupo. Para esto, lo podemos elegir facilmente con la siguiente linea de codigo \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "0fb6c9fc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='FoodGroup'>"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "grouped['Protein_g'].plot(kind='bar')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "56030a02",
@@ -1842,7 +2019,9 @@
    "cell_type": "code",
    "execution_count": 4,
    "id": "6484e601",
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "data": {
@@ -1888,64 +2067,12 @@
     "grasa_mayor80"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "b0d80de6",
-   "metadata": {},
-   "source": [
-    "Importo la libreria matplotlib con la que voy a hacer los graficos"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "551b3ef4",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from matplotlib import pyplot as plt\n",
-    "%matplotlib inline"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "661dccf2",
    "metadata": {},
    "source": [
-    "Si quiero imprimir un grafico que muestre la diferencias de promedio de grasa entre los diferentes grupos de comida, usando la agrupacion realizada anteriormente, puedo crear este grafico."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "0fb6c9fc",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<AxesSubplot:xlabel='FoodGroup'>"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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U1eR71a6ri9+qSV21719TGvalrttX9WHWk3vRxEi9FxswL73uAXwbWBy4oaTMDel1a+BS3HX/6rIygICN0/v9gIurtA+30nke8CfgO8CvK5RbB1gyvd8G+AiwYq/rAs4F9gFuAV4O/Aj4Rp/uRZP73vT+XZ9eX42bpW4MXNeH+9e4XzTot3PT67uBg/L3tA/fq3ZdXfxWjeqqe//S+bsCy6X3XwBOBTbrR19q2L6LgOWBlYG7gDnAt/tRV34bpgplcUmLA7sAp5vZf4Ayk5in0usOwJFmdjqwREmZ+eZ3aWfgcDM7HFiuQvueNrP5wBuAw8zsY8DqFcqdAjwl6XnAMcBawPF9qOsZZnYM8B8zu9jM3gVsVVKm6b1oct+b3j+l19cBx5rZ9bljvayr6b1o12/LWEzS6sBuwFkVzs9o8r2a1NX0t2pSV5P7B/BFM3tM0ta4QJ4FHFlSpklfaiKXAFYws0eBN6a6Ngde2aCuWgxTgP8AuANYBrgkTV8fLSnzF0k/wDvMr9O0r+w7PCbps8CewK/kURQXr9C+/0jaHdiLsc5ZpVyTP0OTurIf+15JO0jaFPeGLaLpvWhy35vevzmSzsX/dOck1c3Tfair6b1o128fKSnzZdxf4k9mdq2ktYHbKtTV5HsdlOr6Y426mv5W2feqU1eT+wfNBhFN+lITuQTNHmZN78UYdYbr/d6AxUo+Xxp/wq2b9lcHXlVS5pnAx4H/SvtrAO+o0JYNgP8Bdk/7awH7Vyh3NbA7cBOwVjp2U6/rAnYEVgA2BC7Ep2yv79O9aHLfm96/KcBmJLUT8Axgoz7cv6b3Yq2WfWX3pddbw+/10irHevFbNfxOje4fLhR/gKt4VgSWJKlIetmXOlynUC6lc96Mq+L+N+2vDZzS777U8x+owhf9eNHWoczKRVtJfRP0wu2OtTlnvyrH2pwzkD9Dwz9qrXvRzX3v4nudX+VYm3OWAtavUU/TfjFBhwrMKSmzHnA+6UEObAR8oUJdE/pbWR/s0L4yvW+teoAjUh9vu/X6/qVzmgwihM+wvpT21wC2LCnzjPQ9rsMHRYfj6sqy9jX5Pza6F/lt4J6Ykg5Ib9cHtmAsfsrrgUsshadtKfNnXA8l/Ed4KL1fEbjLzNYqqO86M9us5dgNZla4Styh3Fwz27SoXDpvKWANM+sUOjc770YK9GtFbezQvgnHKpTpeC+a3Pem30nSNPxPeiG++JvpKpcHfmNmLyj4Xq8HDgWWMLO1JG0CfNnMdiooU/dePB/4f8AhQN5SYHngU2b2/wrqujiV+UHWfyTdZGYbdipT0Ma2fVDSi4GXAB/FFyHz7XuDmW3ci3rSZ3ulty/FByw/T/u74gLoY23KNL5/qfw+5ms++WMHm9n+BWWOxFUmrzCzF0haCTjXzLYoKHMecAnw03RoD2AbMyvUZ9f5P3Z7L/IMPCu9mR0EkHRTm5nZY2n/QODkDmXWSud8HzjDzH6d9l9Lh4UCSe8HPgCsI+mG3EfLAVd0al/SBb4NWEtSPjjXcsDfy75fXpika2xCZ2GyY9n12lw/+6NOl/Tx3EfL4zFp2pVpdC+a3HcafKfEe3Hh8yx85JMJ8EfxzE9FHIgnGLkotXuepLYP9ab3Ah9w7Ig/vF6fO/4Y8J6S9i1tZtdI49bP5nc6uWEfXAJYFv9P5xdjH8Wn972qBzOblcq/E9jW0uJb6ifndijWzf0DeLOkJ8zsZ6mu/8XVKEW8yMw2kzQ3tfsheeC9IlY2s6/k9r8qaZdOJzf5P9L9vVjAwAV4jjWAJ3P7TwIzSspsYWbvy3bM7DeSvtLh3OOB3wBfB/JP6cfM7B8FdVwB3IsHV/9Wvhyu4yrjQCoKEzO7s8L1Wqn9R6X5vciofN8bfifMrUAOl/RhMzuiZvH5ZvZIi4DsNAtodC/MF81Ol/RiM7uyZvv+JmmdrE3yZCj3Fpxfuw+a2cXAxZJ+XOM36LavPwvvg9l9WzYda9e+bu4fuPrkDElP42kc/2FmHygp85+0OJ3d9+mUL2JeKOmtwElp/81A50S3Df6PPbgX4y42lA34PG78f2Da5gGfLSlzDm4DOgNYM13jnJIyW5HsR9P+cviTuax9awPTcvtLATMqlLs6vc7NHSuzjd0KD8/7f/iD7Cng0ZIya+beTwGWr9C2pvei8n0HLkuvj+GdeNxrhbo+SM5uHlgJ+EBJmWPwkeQNwLq4jvb7fboXs9q070cV+tJvgceBvwCXVexLtfsgcF6b9pX9R5r29b2BO4Efp+3PwF4lZaal3/h/cd+FHxXdP8avu6wJzAW+S7X1rz1wFe09wNfwbGC7djg330+fxq28/pPeV+m3a6bXZcrO7aYvTbhGnZN7veErxPvhzi6bVjh/ZXxRYW7aDq/wI84lRV1M+1MoWdRJ583GdarZ/hLAtRXKNREms3Enirn4tGtv4GslZY7Hp2nLALfiI6lP9ele1L7vXfSJee3aXVJm6fQHvTZtX80LpB7fiwltKWtf7rxlyD00+tEHm7SvaV9P5z4Tt6XfCXhmhfNPBr6CW5PshatcDi84/8/A7S2v2XZ7hfqejz8wPgS8oORc4WtXTfrti3FvyrvS/sYki5R+9KVsG6YKBXyk+TQ+xSmb2mA+xd1PHjPgaTP7vwp1yNKdSdd4WlKV772YmS1Q8ZjZkxX0ZwAfxkeo/wZOwEevndQ8CzCzP0qaamZP4S7JRfpYgA3M7FFJewC/Bj6D646/WVCm0b1oct8lbYsv1Bhws5ldVFYmMUXSgnamKXDhfTezx/F7/vmKdUDzfjFF0kpm9lBq38qUqCLldvNvwmcwi2WqHjP7ckldTfrg05LWMLO7Ut1rUu6I0rSvg6sL/ysrCpxZcv7zzGxXSTub2SxJx+P/kbZYgYFCJyQtn/4bKwMP4P/D7LOVrYOqzMxM0mnA5nXrBA5jzOMTM7te0stKytTuSxMu0KChPUHSfsDPcP3bqsBPJX24pMwL04LEjcDNkuZIKlzJB26Xx3ZYPG374U/yMh6UtGDhUdLOVEhSamaPm9nnzWwLM5uZ3j9RUuzx9IeZJ+kQSR/DR2tFNPEYa3Qv6tx3Sc+WdDWuFlsbn1kcJOkaSc8uqwv/M58kaTtJr8D/fGeXtO885WJ3yGNRdBQKiab94lvAFZK+ktYBrsCtCYo4HR+lzgf+mdvKaNIHPw9cJuk4ScfhFhWf7UM9SDoYn0H/Lm0fkfT1kmKZA9rDqQ+tQPnaF5I+2OY37qQDzzyf5+Czi2zL9ou4SlJHK5UizOzulkNPtT1xjCZ9aUKlQ9lwFcMyuf1lKNcVX4Gvemf72wBXlJRZFTgRfxLfj/+4q1Zo3zrAVXhcg7tT3c+rUO5M/Cmc347DO3rbaT2u25uGq0QOwOMiFNaFq53+go++la5xaZ/uReX7DpwGvLPN8XfgD5qyuqYA7wd+gYcleC8wtaTM3CrHenEvUtkN8Cn5h/GZUNn5hY5cfeiDq+BWDq8HVuljPTcAU3L7Uyv8h9+N63pfjj8wHwDeV6GueXV/44b3/He44P1T+n43ln2nVO4XuDXKdfiM8ZPAib3uS63b0DLyyO2Ft7A0OpXbAV9rZi8sKHO9tdiztjvW43Yui0+3H6t4/uHAdMambW8B7sMXhpY3s7d3KFfJdryk7sXM3fh7Sp37Lun3ZrZ+h+t0/KzL9s3BbZ3zaoPTrMAmvou61mh3PKu7Q5mjgCPM7MaGdVbug52m7WZ2SS/rSeffgNtI/yPtrwxcZCU+Fk1IdW1sSWAl1doNVmx/fzr+kD7dXM1WpZ412x23EsseSavga0OvxAdU5+LOUB3NMZv0pVaGqQM/Frg66ZyETzGPKS7C7ZK+iI9owb2s/lxUQNKxtFEtmAd/Kir3pZb9rFyZ3nJTM8v/ic6UdImZvUxS25yhqmc7ni+3A65nnpY73LF9Te8F9e57J1v0KZ0+aznvzx3auHZBsUxtcHHafxmwb0k9Te/Fr3LllsI9bX+P/w6tdWROTYsBe0u6HV8bkVdV6kzWpA/mHUOm4TrqOcArelwPuCnmXEkX4t/pZZSoayStBvw38Cwze62kDYAXW4uTThsy1dr38Xv6PkpUa/hM9i3AwZKuwR2OzrIClaaZ3SkPmLWumR0rNz1ctqQezOxvuNVLHSr3pU4MTYCb2bclXYSHKAXY28zmlhR7Fx6s51S8w1yCW2wUkQ8sMw0PMvXXCk3M6yin4VPSWyqUm67xi0hr4FNaGG/3nudAJtqOzyiqJHXkpYFtgaNxm9NrStrW9F7Uue9nSvoh8FEz+2dq6zKkEKUV6prZ0sZdcSuYjpjZ2fL45Ful9n0s/aGKaHQvWmeIqd73dji9qVNTRu0+aGZ5xxAkPZdyvWqjvm5mJ6T/8Bb4ff+Mmd1XUuzH+OAtW3D+Ay5YywT4Z/D7/H7GRrhHl7Qvs42fij/A3oObLXZMnCD3FJ+JO9sciwf1+inuddoRSevh0RFXM7MN5fHAdzKzrxa0r05f6niRoW24qc2HcR3QxjXKLQ8s27DOKcAFDcotSYk9bTrvdbgu8UJcIN+JR1BbBhdq7co0sR2/oeV1WdxNuG/3osp9xzv8ofgiWLZo9CBjru5NfrPLOhx/fnrdrN02iH6RypbFGqkdI76bPthSRsCN/aoHNx88NG2FwdTS+dem17m5Y/Oa3PeK7VsKjxB4Cj5rPKLk/HnpnuXbV0UHfjE+CMuXq732UdaXWrehjcDTqv978Bsr3ArlKCvwwpP0QuAnpBGZpL/hjgM31ah6XdwLtC5L41YVhZjZryWti9ufCrjVxqZsh3UodpOktwFTU9mPUOzWDZBd83FJz8Jdn+uaXFW6F3Xuu7k1zCeTyuV5+D34o1XXQeb11lPw0VCnON0fx1Ul32rzmVGgNmhD1XuRd5eegj8sHiwpdgowU2Mx4s/AF01fV6N9UKEPSjqCsWn5FGAT3GGup/Wkug7GR98/S4c+IuklZlakRvmnpGdkbZS0FRVCqKb/xdfxRb8FKkMrUK1J+jnwIlzV8j1cP19mrvykmZmkrH1l1mAZtcIlpGs36UvjGKYOfB/c8y2bZn8DuBJ3fOnED/CIhRemMtsAR+Grv22R9BhjAZkMX1D8TFnjND4o01R8YbJMJ5ixLj4FmwZsJAkz+0nB+Xnb8cwutuPUK3FmMqv6Jr7ybcAPiwo0vRc0uO9m9i98Bb8ueWE8H4+XvFuHOvZNr9vWraSLe5F/mMzH9ZinlJR52szmS3ojHiP+CKX4HCVtbNIH82Zy84ETzOzyPtQD/gDaJBOKkmbhDlJFAvzj+ANsHUmXp7o6hYDIcyxuofUdXG24N5QmZzgWeJu5b0VVTpLHvl9R0ntw9WHh/ypRN1wCNOtL4wgrlM515Vej5wP3WwULj6RD2wYfKfwaj9twmZl1Cig0FZ+ulmXvyJfZFJ+W32xmt8gdRaaZWb1g8NXrG7j1Tx0kvaPd8ZKH5sCQ28Ufhj+kX29mf1a1aISN+mCD9jXt642sUOQOU+vjAvj3ViETjaQ5Zra5pBszGSHpUjP7r5JyGzJx1F7YLyRtD7wqte8cMzuvQvvWZmxQ8xCurtnDGsYGqspksUIBd0jpmRWKSpLumtl1HcplC2atplTLp5F0WfCnN+O6/blmtndade+42GJmT0l6XNIKVQRwshjYE9cvHyLp62b2Q3z03qlMo3uRo7b1T11appMTMLOiZLl5x4tpwHb4rGTCH7WLfnEmxWFyiyyG9satJr6WhPdajIUrbVdX7T6oBmF8e9DXK1uhpNlHO9ZLdZ1aUtcTckum2yR9CPeBWLWoQKfBFG36RZ4ksEuFdkuZ24FXJpXLFCswxeyyL42/1rBG4LDgz7Q1ybLBSqxQ5PF8D2LMcuUSPJnqQ23OvTC9nYbrUa9P9WyELxpu3VomlcvM2GrHHk/lrzGzLeW2ydvif46brNhe9STcguI8chYBZvaRNufejM9cHk+6xLOtIL5xKtPoXuTK17nvTQXkAelt5TjxBe1dATiu3R+hi37x8vT2jXj8j0wA7w7cYWafq9q+Cu2v3Qdzo+gPptfsYbsH8Li1MQnstq+na6zOmBXK1dbBCkUeRXBe2mC8+sOs3Kx3C9wyZkU8NMUKwCFmdlVBmRsZG0xtnA2mrMVSJ52bqdQmfJTa19FyJZX/E+4MdSneX39XcG7v+lLdVdJuN+DHufd7VSzzxtz7lWrWdyLwwtz+hvk2FJT7PvC63P5rgW9VKPe/eCd7H54fcC6e5LSozF7ttg7nzina7+W9aHLfceubC/H1jP8w5sL8HzpYk7SUP5eJUQLPrvmbLw7c0qd+cUmVY+n4Sen1Rtyrb9zWjz4IXF7lWDf1kLN2oiSCaO68N6R7Phv4IhU8PbvdgGvS6xzcgkq42rGs3NwGdS2Jz0A+j4/2b8edyXrSlzpeo983sejmUNFkJn9e1TK58+dVOdbmnAmCEZhdUkbAc3P7M6iYg4+KKcGAhxlz0T+zZf+MXt6LLu97UwF5K8nkLu0viVvyFJXJhy84K/15Du5Tv7gFWDu3vxYdHhbA6ul1zXZbn/rgPGDr3P5Lyr5X3Xqa/Idz5y+DR+s8HVdnvLxiufXwxcRzgQuyraRM7cFUk++UyiyGRyTcP/XBK/EMTD3pS522YejAm+hs1OF9FW6RdDQ+TTFcf1vFIedvkr7QUq4wI4+ZmaRfkqKZmdkdVRqoep6YO7fsH1qljkTde9HNfX++5VzHzeym9L3KOA64pmVtZFZJmfw9mA/caWb3lJRp2i8+Blwk96oEf0i39fo0s8wK4RHcMgngD1Z9sbl2H8Stu36U1EjgD/gy79K69TT5D2c8gd+PR3G1zbTi0xdwMj5T+CHlQaKQ2/N93cweBr4v6Ww8lMUNTRpdgUfxmda3gR9agQt9jsp9qRPDyIn5AD46E+7memL+c2uv970V1w9NwTvZ28gJFCtYhEvWLe/Hpzfg+tsjrSRCYFrgOaCl3EFWsrAj6Xv4SPPaovNaymSuzhfZWM7EBavtvaLuvejyvp+A6/PzQmFZM9u9Qjs3w0OUGh6ga27pl6tJ036Ryi6J2/mDzw7aLiDLI0wehT+E/gwLgo6dhgdw6uSZm5Vv1AdT2eXx/3eVhfFa9Uh6OJ0j/HcaF2el3cBDHl54d9zZ5bd4oKeyyID58nPMrFaY1zplWhZZD8WDUS3AShZZ5REct8a/35O4H8clZnZ+SblKfalj+SEI8L2KPreUb6+lzIXFRazQYSP9kdbHBUIls6Vc2Tqxx5H0u1TXHbgAK417IelqM3uRcolkVSHxchPq3Itu7nuXAnLjVC4T4G0dUQoWnsCtcv4EfL7Tn6hJv5CH8M1/r4vwqfKEspK+jJt7vs/Gcr8uhzuV3GlmXyyrL5WpE4d9BcYL44vx2VwVQV6pntwiXFvMXdhbyzyN6/4vw++3tZSZMHBrKX8gHrnwNHIWV0UPszqDKXlsnE6YlcfIya7zfHwN4aN4dMulCs6t3Jc6XmPQAnzQyJ1OZuECVcBz8QXCwuhsavE+xF3D97ISr081iGYm6RjgfFx/9ibcE3Nxy+Wh7AVN78Ug0UQP3TcAhR66Ha4zFde7/8za2Ft30S+OxhdJs4HG24GnrI2VjKSbgC2txQtVHvXvqnbtajmvdh+UdApwU0v7NjazTmZ8jft6HZoM3FrK/zk7taVckSfm73Dd+Z1UHEw1Jd33TYA/kixR8EXUjgOWOn2pI3UU5qO44SvQ6+f216OC5QYNYo/nzt0aD84F7mm2Vsn5tVOCDfJeNKzrpbhZ5B/wRcXbqZYC6wZqxokvud57e9wvrq9yLPsuBdcpjU/SpA/SYHG2m77e7w03UXxmbn8vfLH6fyhPp9ho8bhJ+9Lr1Jrtq9yXOm3DTqk2CBa3XIxtM/tDmrqUsYwl1/FU7iJViIugGtHMkpphOTN7kFxKsGSv2un63TgBNL0XTTgGX6SZQ4VFpxxqOf8p6i+gLsDMftDho6b34ilJ65jZn4DMA6/T97NkQ9+u/aUpBGnWB/8laWszuyy176XAv/pQz6D4AR5jG3ms86/joSc2wdcXOrrhW5r1yjNBZaGMq0TfrN0+M7u2bvuo15fasigI8DlJRZF3bJhToVxT78M3AJvinoCY2V+T3rMd/4MH2mldIHklPop/f5symcVFWyeAkrY1vRdNeMTMftOg3I+o76HbhKb34pPAhclyIFuU7BRad4V0zXYCvIruskkffB/wk5wVykP4qLDX9SBpVzM7uexYl0y1MT33W3B12inAKZLmdWjXZ/EHdOa8dCVujbMErq4oS/vW1/blqNOX2jPEqdF6uN73prS/EfCFkjKn4KFZp9SoZ0k8gM6p+ALIx8jZGReUWwkXsNel7TAqOLMw5jxwXXrtqAIAfldwnUKHAxo4AXRxL86vcqzl84PxQFsvpmKIV9za5SXp3I/gaeg2rdC+b1Q51u29wEdxH0tlN8K9/ErvX9Otbh9M7ftmer88bjbX83py5SbYS7c71uU9uAlPugzuI/Cy/Ged2sV4Ndzc3P3pFJr4jUVbL9vXy740zBH4D/HsIT8AMLMb5Bmqi6LwHYk/of5H0sn4CvOtnU6Wx06YY75YVBRLo7XcVOBkqxFgKkedaGZFqoEpJfVMl7S2eQwG5PE1pnc6ucm9SCqepYFVWlQBywPPKin+ovSaT9BgFIR4Nc8M/y0zezFpBlOR7ZkYSfC1bY4BzfuFedyanczsO7iuvm806YOpfZkPwqP9qkfSa/FIhM+W9D+5j5anPITqdHyRegY5DYB1tvI4AU/K8DdcFXRpus7zKAhDaynKaeLwdOwpeerCdmTu9avig4gL0v62uHVIJzPCpu3rSV8apgCvHT/XzH4L/DZND3cHzpN0Ny4gf2ot5jdJIFyvXIacKljNAFMtZQ+VRzN7FNeDf8k6RzN7QNKWZjYuk4487kNZXOB2TgAds3k0vBfvxc2hnsV4VcCjuClcR6xBiNfEuZLeBJxqaajSCUnvBz4ArC2PjJexHNAxhGrTfpG4QtJ38Swy+bg1dR44pXTRB+dKOgN3fMm3r60AaljPX3GX+J0Yr3Z6DO+XRZyOC7nfUkHfa2Zfk3Q+sDruwp/1iSm4rrkdy0paPJMHZvZjWGBz3TamiZntnc45C08ufG/aX52Cvt6wfRld96VhhpP9DZ6J52Qz20weP3cfM3ttSbln4Dq6t+Md6We4vviFZrZNm/MvwFeIr2H8TSqM+KUaAaZayn0sfacyT0AkbQmchKeZyv4IM/EM7m81s6tLytdyAujiXnzYaprxpXITcnZaSZ5FuW33MvjD/AnoHEwoPchXwnWa++c+eszKHa6a3ot2tvFmJb4ITWjSB9XentkKRrjd9PUFQrIqkuaZ2SZ1ytRF0n/j60MfsmTCmRZlvwvcZwUJJ9QS5jfN1m6wEpPPhu3sui8NcwT+QXyV9vmS/kKKn1tUQNKpuMA6Do+rnLkq/1xSJ6+ugxq271dpq8vywDmS/oF7mf7CzO5vd2KagWyJ34t3psM344kuHqhQ1+aMTUU3VnniiKb34j5Jy5nZY3KX682ArxaNFNQsZydm1mnBt8PpdoekD7Z+IGnlEiHe9F7sauX5NiegNolyzaxsobBWH0zX/R6eAenhGs1r2te3lDvYrIn3wexh29E2GzhL0uvMrEp+1KZ8ETfLvUtS5n+xBr4YXuY8dZGkc3DViAFvxYOz9YNGfSnPMEfgU9P0rTR+bq7MK8zsgrLz0rnT8BX55+ExCo6xisHwJe2SlTOzc6qUaXONjfBV6TcB9zTUpxdd/zjcy28eY1NRazdq6uZepPI3mNlGSQh9HbeE+ZyZvahCmex1WVwt8qoO56+brrsOrhP8lJn9paRdZ5nZjhofFjWjrSBpei/k8Wp+hEdVfBrYzczK0t5lZReYlprZevIUeCebWcdEuXX7oKR349ne/4QHRdrXzM4oLtVdX5eHWphgKmoFcUByM6wn8XuZihSHa21C0nc/L+3+0TxLVJVyb8RDBIAbBpxWdH6DdjXuSxOwPq2gl2144t+j8OD7qlhmGmOWA6fgnaetwwuuV/oprsf9JXB4xTr+F3c//jo+Yvxiw+/3TFwHdjldOKIUXP+WGvet0b3IlZ+bXr+Op6hacKygTJao+Spch74kcFvB+Zfii1vr44vbp/ap3zXtFzcwlkT5RcDFNeqcB9UT5Tbpg7g1xPT0fm3gygpluurr2W8cW+0+2LgvTbjWEL9Eli36VNx++bvkwmB2KHMSPg3aNm1H4SOZdufemHu/GNVD196E23aCqwBqeSrittsX4aqQg/AFkX7cv5NJ4UornNvoXuTKnIVbC/0JD8+5JCUeY/hUdUV8BnIfnh/wywXnz2vZr9xGPJbEhK3H/eK6LtpX2bS0aR9s0r4e9PXapqKp3E6MZbLfsU6d/d5ws8HbGIuY+BjwaI/raNyXWreh6cDNpzMn4WZ3K+GmPhcz5jHVjvVtfB7GCyW1DXTE2PQM84SyVZv2pKUkqOZZb+p6Aa4JfNTM5lUtoGYOEasAv5N0DeOD+7RbhGt6LzJ2A14DHGpmD6eV+U8VFTCzr6S3p6SV/bKcndPkuT6zxi2V37filfl8W6bhEeGyCI+tNL0Xq2p82rdx+1ac8q1uotwmffA5Gm/SN27f2i9IdtvXa5uKamIm+/3knqP7dyozYA7B19eqhBZuSjd9aRzDTqn2clxP/Fo8BsjPzb2YOp3/Y+D7ltIoSXoRHnTnA23OfYqxFXXhI/7HKbBqSOUexwPSZOXWSfuVA+HUXbCSdJ2ZbVZ2rOXzl7c7bu0jwTW6F22usyrjLUrqmuAVXbtoocisxsq8pOfi6bYmhK7tol8cUFSnmRUuiqpGotwmfVDNonx23dfrIjf33MTGMtlPxVVLPatLXeSAlXS5FaxN9IJu+9K4aw1LgKeFp3n4KPwMG29433pulrB1cVxHelfaXxP3ZuyZiY86RBPMsJIs03UWrDTmELEbrpvNWB5XvWxZt/39QNJOwLdwXfYD+Ir+rVaQ53OYpJHkDdbjeOqDots+OMh66pqKqmEm+zqoixywkg7H169+yfiZbWE88GExTDPCja2itxiwY19bkqMHf446sVAaO0RI2go4AngBHuNhKvDPqqPpmnwFtxP+rZltqrHg/JMCSUcwFltkCh5IqJNqbWCoOF45nX6rXgnoMrqtp6GpaOVM9k2x5EQm6UTcGufGtL8hLYka2rA8PiPLW0sZnT0xh8rABbikT5vZIcDXJE3o3O10da0drXUqP8l40sws+24qiOpmnqjgeknHW3KISOsBz7U2Gd9b+C5uo3oyY84/6xaWaM5/zOzvkqZImmJmF0r6RlEBeRS8eWb2T0l74gtch/dJOOV9AOYDJ5hZR0/MQWHJpl2e2OE+3H9BuL9DHXv3ycpLbMxU9CBJ36JE0JnZCZIuYiyT/WesQyb7HlA7rZ8lj8xRYRgj8GxxoHI6pYw2U/k10/Um01S+7oIVeEiAnfDfYx7woKSLzezjRYXM7I9K9vTAsZKa2ZKW83Cy474E+Jk8LV6Z7fSRuHPRxsCnceuhnwBtdfdNSTrU7c1sz15et8e82sbbzB8p6Wp8waynqI0Dk6S1itZguiBLVvB4UhX+HbdBL2qfcNPhtc3sy5LWUJtwEj2idt5TuZ/APkxUC1XKyDNoygIm9RwzOzO9fdzMZuU3fOpSRDaV/4OZrYV3hJ6OtORxDSgbYXbCzA4FfoHbqWexUMrc0FdI6qQ34lmzNyfFQC7gcXlKsHmSDpG78Pc0hrOkNdLbnfHf5mN4+Ns/MRb8pxPzzRdYdsZH3odTcdQp6dmSXiLpZdnW6dz08Jqe7kUtJK0pKYs1vVSBqitfZjVJx8hDQSBpA0n7lBR7StIekqamWcwe1Iz7XIMz5anRsvZuAJxZcD6SdpS7jDepa0XclPA63Bz4hJIy/4ubHWYquMcoiavTBXvj5rz74TF9fkd5uNbjcB34q3GruOekNvachn1pPDY8e8vaoSiB2en1elJIWZKNbZtzH8PtONtuBXX8Dh8l3oLrsjejho1ry7VWoYKzDe4RuDpwLrBFOlbo/IPPPqbhOrsD8Kh6zysp0+6e3I2HU1276PcATqn53S/GdZt/wP8QU6mWheYbuCD4NS54zsQXuYvK/AC3Yvoi7uj1ceDjJWXek8r8Ke2vS0mI3HTeb/BF5+vT/mJl3wsPd3A6nqrsQXyBbEZJf7ih01ZS1w7p3i+Lh1q4Gbf6KCrzU/yhfAjwgoq/7xRchZLtL4kPRCr97xnv1FQrC00/N8ac1m5Ir4sDF/Sprtp9qXUbhg68cShKakzlrbn+8Ut4YKTnMDHUaEcb17SoeDDwD3ymcBwuwKdIeoeZnV1Q55eBc/BYxdfKM3PcVnA+NqZLfoLqcT2+jS+cHo/fi7fiwvX3uGvvNq1fK/e+KL5FO96CZ7Hfx8zuS6P5b1YotwtuwVMnO/df0zaF6rrlD+L24lcDmNltaW2ljFXM7CR50gDMbckLR9Nmdgc+E6lKtmifxXjJJ50onKWa2a/kmYXOxe/FLmZW1pf2TKP23XFVnOHZpE6wDiEuLIX+xUfTpN+rym/2n6T2ytaIplMtO1Ft0jrMgYzFagHAimO1ZH4CD6dFz/vwB3A/qN2XJjCEJ9zGeIaQO9Nrtr2RkiDyuIpgCv5j7IUH/X9GSZkJ7r7tjrU5p65b8Wx85XpXPAvKVun48ylxOx/gvW93L65Kr+3y813X7n3FumonWUjn/Aa3m69Sx49z7/dqci8YG3EtRoWQB7iX7TMYG0luRQdXaODT6fUIPGHCuK1CXZdXOdahjpsYy81YWle6xiq4quGO9DvcBny44PyDcE/bSiEdUpk9UrvuwQNO/R4P6tSP/n4r7mOyavrNnlFBXrwbj3D5MjyP6wN0yKvag/ZV7kudtoGPwK2N5UWNspmt+NOSfgX83dI3L+CppHM8EX/q7041/ePXkvXEgsUWPLlqp8WWxczsXPBRvyVnIzO7VSUObgNcOHla0m64jh7G5+trdx83lvQoyeElvYdqDkB1kyxkpoCP43r98xlvh9vOkzDvlbsfY9m9q3CxpM/h32t7PK54oa448XFcAK0j6XI8iUanvIeNF+wTy2h8fsuX0Hmdo7WOyqny0gL63rgjz3HAlmb2gKSl8e/QaQ3n46k98yUVhv7NMLOfSZpDioGEzxD65fVYO62fmR2d3l5C/VlnXer0pbYM05FnXdwmdAPGC612EeQ6qieAQvWEpBm4m/5LcQFxOe7qfkdJ+47Ep3avMLMXJPO+c81siw7nL/CcVIsXZet+m7In46OFt+HqlD2AW8xsv6I25spPwUethXb1STVzOD7tNTzQ1MeAvwCbZ4KiG5RLsoDrVTOWwzOdtw0ZrGaehB3veYV2TsEfmgu8I4GjKwwIkLQYvkAt4Pd1BiKpHz1csZ7NcdXWCvjv9QjwLuvgSZhUE7OspkWOpFl4VMZL2ny2nZmdX+d6FeqbCqzGeLVGz7x6c/UcjK+9nMr4wUBPk290Qzd9CYYrwC/DF9++g1s07J3ac0Cbc2cDn8M78lHAa83sKknPx/V0m/ahfdeZJ5qYm11f0vU2PhZL/vzMRTvvnk3an2ZmHTOeZ3VoLPTq4ri7dVFMiePxsKhP4aOtFYBvm1kVPXPfUBdJFtpcK7OJv6HD5w/gMyvhOvcT8593GLV3RRI+OzAxJdiE+BWSvgSclGZhS+JqiU3wdZu3mWeYqlLn8vh/oyiWTHbuOXgsjycrXnsq3tdqhzvuZB3U7kGQK/Nh/H9/P953++m2f2Gbw1b0vxoE8nC1HbEaXp/D9MRcyszOlyTzBbkDJV2K/7itdKOeWA+3SV7NzDaUx+neycyKcm9CzcUWMysKwlVGk4WTDczs0aQe+jWumphDwUJhy6JxxiO4dc/ptVvdhiRkHiGZiWnM6WpZScuWjbTkTh5VbeLzQaxqqSkk7YjP5rIFrqpxYc7EF45vpHzx7S2pDvA1G+HT5PVwdU+hAJe0Gh7j+1lm9tpkEvhiMzumoNgdwOXytGr57DptAyRZF+kDqRdELGM/fJG6Y8zwXmHN0/r1myITXKOG1+cwBfgTaRp7m6QP4dP4TlYA+T9Ka1D2silEk+TJ4Is/pwGrSfoarpv6QkmZphyVRptfwHViy1KeOWTxNFLfBfiumf1HbTxbW5iGL6pmUQ7fhJuZ7SNpWzP7aMP2T0AetP7b1He6WiE9mN6N28QfoPH5LhfQTq1Sg8PwhfMbq6gzcjynxmjxydy1Xw2caG63fkuaOpfxY9wa5PNp/w94zJwiAd7EIucJ4EZJtVKqmdk4QaQURKykrrspSPbba1Q/VsuuwNlWI/tUXayH3p7DFOAfxeMofAQfpbwCH6W0o2gxrcylvnbyZBjMYouk/cwdXG4xd52vs3DyA3y0dT1wiTwwUVlsmefhOv35qf4jcXOz7fERZS/5Ks3ipywmD1e7G2OCqx/cDdxUU3gD/EbSq7IZYQn/TjOq+/F4Ifk4HEtXKN/EZPEgALlTkpnZ/1Wop11KtSa61XuAtoHlNBYu9XY8bdmvGK+XrhxCtSpqFqvli2Z2sjyi6KvxmOVHMhY6t5ftewaucdgav9+X4THzK89OhhkP/Nr09v8o8Y7qUj3xN0nrMKYKeTOeXKAKq+Aeo8dKmq7euyTvjS8qHoE/6StjZpm5WMadSUgW8WzcaiAbAS2DT8+fklTH7roKteOnJGrbxDfk08CvJV1MPUFyFXBamj3+h2LVy364xc904DtZ35H0OmBuhTb+M/3Js767FSWj1/TAOA5YOe3/DV/ov7mg2IppIJG/TukCuuoFEctmA3elbYm09ZPasVoYs1DbATjSzE6X5/3sByfig7Y3pf098BlW5fWIgS9iyrNmd6rUzKyeK2l5fWvjC58vwe2z/wzsYT0MC9tF207ALUKmM95io3RhJy2KvYmJi2lF08N9cDXNRamOl+E61hOAA82sMElDHST9FlfvfB1/ED6Ae5m+pFd1dIOkc/HBwzhdtpXH9b4d/151VS9N2rgZ/nDfkJQyDXhzp0XdVOYK4PNmdmHa3wb476L7rvbx6Bcs3heUy8+Y5wN32CQIIpYh6Woze5Gkq3B12d/xWVfHoG/y5CN/wYXo5rjK9ppOxgtdtm+OediM/LHZZjazU5kJ1xiCAH9Tm8Nr4CqVqWb2nB7Xt7mZzVEuebKk19tYTJZO5eaRwsLamBXKDb1eLZf0THzEOSGTTtFDRtLZ+GisNaHst0rqWx1fbBLeMf/arOUdr7+Gmd2V7ve/8JHZHriVzM86TQ+VolS2jOoW0E4f2+ncojK5srX+KLly5+BWUH3xHmxTXy0zM7WxlGp3LB3fHTdd3RrPSZqxHPCU9TgRd6rzPNxx5+G0vxK+NvDqPtT1RfwBuB0eb8WAH5rZlwrKLI1nn7rR3Dt3deCFFVVmddt3KL74flI69Gbg/1kbS7xODMORZ0HGnTQ6/hw+EjyY4sWZpvxQ0l42FhP4rbjtc5nTRuWwsN1g7mb+rlZhnRYBi2YJzzGz11SpQ9KeZvbTtLu25SxOJH3IzL5bu+Gd+SUeM+afkk4xszdRzcHmd+m1jjVJdu5LcX+CLCnGrpQ7svy2hi47z724Dvc39F+HuzTu7LGmmb1H0rqS1jezswqK3Z4EV+Z+vyc+62zHFfj3WQWP8pnxGB53pax9lX05ckzPhHc69yFVC2FQG6uf1g/z1HIP4A+12/CZRU9VeBqLEy/8983+m1PwWWFlAd5z99AqG56E4Ke4BcQ7cTPBftW1Nh4p7QV4AKNLqRZ055P4QuHtqdyVFLgVd9nG6/CnfLa/OyXu/rha6IVVr9/ufbv9HnyXue3eVyh3XHrdr0GdFwKL5/YXBy4sKfMYrjr5FzWS16Y/14StT/3i57iu/qa0vxQtyZ/blFkJXxu5Lm2HURKioov2XYaPbm/ArYwOBA4qKTMHWCO3v2av+2CX3+kAfHD3h7T/LDqEL5gM2zCCWWUJCA7FR8JPActnViJW09mjDDO7PY26f4lbHrzKPKFyWblD5S7WjzIWFrZjHsMueTPwC7lN99Z4coZXFRdha+Cd8tR0/6ZYb64O79vtd4t1eF/G5smS5l2SfkJLu0r6xbPwaX92zrLpWOdGpmBndbE6+Qq7d9hYx8zeklQdmNm/pPaOD/JwDO/DLY1uBD5h5eqWThmDqtrE1/HlyPg8cFlaPAaffe9bUs8geQPVM2p1TVIhrcv4GUxHR6hWhmGFsgXeaT4JfCIdyzql0aP4AxrLo5mxMu5We7UkOgi6cSSBfZ6kVfAFkL7Q8CHz2jpVdHjfbr9bmsZP+T4ea3xtfJSWF1Rl/eJgxtJ0gYcDPrCsoU3+PKmOdjr6ds4rmZ30qvgi+gVpf1t8IblMgD8paamsvmRN1claaBZuFXMp3jdegK8rdaTpQyxHHV+OrM6z0+LsVvhv/DEz+1uX7eglA1Gdpmu/G7dUeg7utLYVPtOv7Ck61Kz0/UQNE7aqi7grDdrY+pBZFV+Y/HdqY7vs48ubO7qs3O6a7UaqGss+LsYyj5P21zazvnXSukg60sze36DcMxmz1b3aStJ0dfrzdBDE+XJ5q4FpuCXQfDP7dEGZs4D3mNm9aX914HtmVjhCTzPAL+A65nNxXf87zeyiNufeaCmJc1r4vMYqxobRWOKOcVi51+wWuHPWivh/ZXngEDO7uqTcs5kY4rXyqLMp6b7/wwpCFUv6JP5Q3x7X778LON7Kk7I0ac+N+ID2KjPbRB4a5CAze0vlayysArwVteTR7NQ5NcC4K00eMpLOMrMdk+okWwjJFWkbDKzRw2yQdHogZZSp1uoKhV78eXLXutjMXl7w+U1mtmFufwoeurat00tL2WcwNlq9qtNoVTUDqLWUzTtxTcPTov3ezAq9ZiXtamYnlx1r+fwbeIiBmxkz3zQzm2CF1Wvkpq3r4MlJOiY3Tg/OBUHO+qU6lXStmW2RLN5eZGb/ljTPzDapeo1hemIOBNXPo9k47kpdWgVn60OmQ5kd0+taTeuZpMxhbDbSeqMLVSidhALuJNGJJ8zsCUlIWjL9vuuXNbLlQTMFtxV+Zkmxi5L54QmpXW/FF1471bEmHrHwEXNnqMdx2/P1JH3X2geqylRXMF59VSXE6wtb6t8MeG/JdwLPuNQqrNsdy7ML9RN29AQze2VaQ9ig0zmS1gIuzYS2PNXeDCuJXtqQe+Qp6X6Jq2ofwsMgVGahF+CM5dGs6tLdTdyVRjR4yGTluloAmUzUeSC1YRfqC4Wmf57sQSPcxOzPeFjajpjZh9KC5n+lQ0eZ2WkFRU7CF9MekWdRPxmfzm+M55R8d5s6uvFWbr3WdUk90hZ1l1XrdtxKqO8CPK0Z3JNGttsAGwE/sWKv1JPx9YqMp9KxjvejKWb2hvT2wLS2sgIesbIyQxfgVVUbXVDXpbubuCtNqfuQ6ckCyGQijfo6YsXBhGoLhQ5/ntL1jaYPmmRxUjXK3FI25mC1J/AjM/tWUr3Ma1J/ERqLUwI+q9gMz93Zib/iNvg7Md7e/jHcsqyIOgk7uuUUYKak5+E+Jmfg6QRfV1BmsfwMx8yeVIOE2VWQdJyZvT3Vc3F2DHh71WsMTYA3HXU24GFVzKMJvR3J1KBJ3JD9GNPhbpvpcPvf1L5R5EFqFD+YGguFpDvPHF1KvSvV3jTwEdxz74GCMt/AF6lFuVojr0J6Ba6WwDwPZVkTm5C3RpmPB7Y6pcO5WJusWhqL3f5QSV1npG0QPG0eAOwNwGFmdoSkshg0D0rayczOAJC0M56Muh+Mk3Xy8NWbdzi3LcMcgdcedTZkZ1wV8jHGXLo7xgsZEtlD5lIqPGQSlXW4mmjtMo4qJpX9xrqL3VxZKMgj+y1uYzFjrgQexgMrzcJVFUXsg8evyXTY2+ABrtZLaybHtSlzCJ5koWo0ywsknYR7Sa5EMj9MVhSVEjXUwZpFMARXPVWN3Z7V1U0I4Lr8R25DvxdjJp0dE6sk3of/B7+LP0jvxv0yekbqg1k6v2y2D/7bHlXrYjY8j6fZ6fV6PEYJuOlTP+tcBaonYB3gvWiSrPk03HzrQHx2cTrw6w7nrpm2Q9L2wrQdjDsoDf0e5Nq6NG46d1TaXxfYsYfXvw5YJrc/N71OxSMglpU/E08Oku2vhqtGViZ5TLYpU8uTL/2hs5APz84d3xR4dR/u+YZ4dMQ70zYH2LBCuezevZvkgUlJYmh8tnN769anvrQB7pW6e9pfC9i/YtllgeX60a5cHV/v9hrDTKnW12h1GqA9dy9Ilgfrmtlv5TEwpprZYxXLvpykw7WCVFqSLreWaIrtjg0TST/HBcg7zDMoLYXbZ29SUKZOftVWc7t3mtmP0/sJ0eHalF9gb532hatPNlSHCH6SDsctVX7JeBVP5cwr/UQNIhim827Eze1mpfLXqiTgm9wsMmMaHrdmZSsIMNUNqf+sYWa/LzlvTzP7act6wAKsP7FupuDBxNYys6/IE2Ksbp0Tp09gSq8bVYO8auNsPJzqjj28/ncZC5V6AfBuM3sm7rpbNk0eKJLeg8eN/kE69Gz8z97p/CmSbsr2zexiMzujSHgnlpEHqs+uU5TlfFisY2aHkNLMmXuklil+j8WD7s/HvRx/wlgwp1aWlWcyIl3/xwDy8LxlruMAl0o6S9Je8nCqZ+AJNZbBVTHtWB7X078Kn8q/nt729W5ZJhPeAOaOQlX6RRa7/U9WMXa7mf09t/3FzA6jTwvv8oBw80iL05I2kaeaa0f2fZfrsPWD7+HquLel/f9Lx6rTzylCyfRhnzbHDu7h9efl3t/S8tncYX3vTm3FdbBzc8duLCnzM3JBgSrWszmusrojbfPwyIFDvwe5Nl6BB226Lu2vQ4lqDZjTes9wW9525/43nul96dyxZfCHQOmUFn+YvAlPxn0YHsdm0qnlat7z0/AUfjPS9gXgl32qa7PcNhPXOV/fp7qyZN9zc8cK/1cDvu9ZH8+3r9a9GOYi5pslPWFmPwOQ9D16a6Y3cHvuLvi3ubkSsMAVuqyNqwM3S7qG8XkMO3q0mdkc3EyycpbzIXAAPmJ6rqSfkdzHS8rUicnxReBrwF2SMgenNXAzs7I8pJiZyb11H7ExddeyuAldW+SBpvZhYm7Gd5XVNyDehVswZSqdSyjJkgWgZgnD89ZGmR39ro1aXc58M3ukxXKn8H+VZhGH4wYWhi9yf8zMbu9D+2olTm/HMHXgS+HTzx/hwXf+Yb1NqvsULtiEj+gezz7C4wKXrUYPDEmH4NPvdwAfBj4A/M7MOuaETHrvCViyJ+1QpnYWn2Ggiu7jufPbxeT4piUv2g5llsIj9wH80SpEqEzl3oNHz1vZzNZJ+vfvm9l2BWVOBm7Fp8pfxq2hbjGz/TqcPxCrIU2MYPgjK4lg2FL+YlLCcBtLejIubEDF63zUXJXSUyQdA5wP7I/3+4/gFkjvKyhzFa7GOCEdeiseRrofOTH3wD2IN8PXEd4MfMEKQhFMuMagBbjGuyIvh+t6Lwe+BL0PJzsKpIWwd5OLvwAcbT3+cdQwi8+g0ZCCHVVBHrdiSzxgVia0xi1stikz19xU9gbzHI2L4zE22up+NRa75oPpNdPn74HnaO3JAzctGOcjGN5RZxClsVgec3P3Yp7ViOWRytxlZm0DanVDmh19nrHQzOfgGeafKChzdauwlnSVmW3V6/alaz+fscTp51vNxOnDUKHkXZGz1x3SVhjzYmFE4wMb/bDC+fvgo79vpv178BGngE+b2ZEFxStn8RkWahbXZJA0UXdlo9qH5UmH78NnQW2xFLtG0kttvIXQ/pIup3d+DBvYWATDYyjP2N5KNwnD8/TFO8nMHscFeMeZbBsulLQ/nnDY8L74q2zg2csBZrrmA4yN9pG0eJ1Z0DBSqnUT82Khw9y77nqlXJIVirwPz9mX8aCZPSdNh8/FdZKduELSCy2ll5uk7MKQgh1V5GJJmRPG9ri6qyw931FyT8Uv4GrDZamgbydZDZnZZdAXq6EFgsLcY7Fu+Q/ijifPl/QXUsLwBu3oV4yhJvk3s2iUrcG83kXvB5jXAc/Fk60LVwHeK3fke09asypkmK70u+J2y49J+gKuB/qKmZW5ui6M1FmQnGLjEwOfnM59Iul1i6iTxWdY9DXYkbqLuQKuT90H1xm/F3eeKpw5mdnR6e0l1BMA+wA/krRC2n8YFyS9onEEQ/yE24FXJhPKKbixwFtok8tVxdl/yvptU1axmvk3BzzAPBs4zczOAZD0KnxwdhIetKxU7z7MRcxMH7g1bpd9KPC5fiwWTHbqLEhK+qOZPa/N8Sn4YlxR2NU12x23SRBuVmMZ5p+NR92rHNckLQJ/FRcgZ6fyH7WxRM75czN752m4Gdv1uBDZCNdrb91apkLb++oMNdmshlJ7Poj/VqcDv037n8TN4HYeYvMWIGkO8IZsZpv6/2nWJk56Wgi/21IiEEnvwBc+7wQO7MfanKTZZjaz3bGqawnDNCPMFtF2AI40s9MlHTjE9gyNvKBWSt9WsIB5rqSvmtkXWo5/GVehFNWT6VZL444PgSzD/BzqBzt6lZl9Wh606B7cLO1CxrJ9L8BSzBVJJwL7ZuqkpJvuGOS/hJ4vwMFEqyGN5Y0dttXQcfi0/0o84fencT+GXcxs3hDb1Uqd/Js/AF4JIOlluBf3h4FNcDXRm/vQvn9I+gyubwefvTyUTAsrmRMOU4D/RVJ2076ROuswPUMHjgrc/SV1cvf/FHC0pD/io0fwEeds2sSJbqlvUBEga2MtQY6SpcaGwF+sQ5S/HJlJ6OvwrEn/qKDPfX5+LcDMbpLH3m5Cv6axpzNmNTSZ1gTWzi1+Ho1H61vDKoZ+GBRWL//m1Nwo+y14LJ5TgFOS5VE/eBvu9/DLtH9ZOjYV2K3KBYYpwHfD9T2HmtnD8khrnxpie4bBdxlL33YBLenbaBOf2sz+CewudzjIBO/vzOxPFeobVATI2kj6PnCEmd2cdL5X4rO0lSV90sxOKCh+pqRbcRXKB+QOER1NxRK3JOHzU1wA74k/zDq1r1P+yto6XEkzgXvN7C8lp05Wq6H84udTkv482YQ3LBhJA2R6/g3kCc3bWTRNlbSYmc3HzfryI/W+yMn0MPmwpGVtYgTIP7Yr08rQc2K2TucrWmIsFOT1XJJuMbMX5D5bYFvbw/oy/dr1wKbJAuYaM9uyl/U0bNvNlnIwSvoosI2Z7SJPVvybonuRZm9LA48mgbIMsKyZ3V9QZhrwfnxaDb7AeGQnG2FJxxa138xKPRdz15qF69z/YAU5OCUdhT/UJpXVkMac5GC8o1ylxc9BISlvHTQNt9+fY23s7yV9Hp/B/Q1XiW1mZiZPBjGrH2scyaroaLyvriFpY+C9ZvaBqteYTAkd1sC91YY+nR8gg3b3f1g1klsMmHwgru0Zs665r4I65Mr8wpSZ/VPSpbhlU1uSoP5O2kqpI6ArXGsvAHn87SImpdWQNUh6UmCFkl2z50LfzF6f35dH+zukw7lfkycEWR04N7cGNQXXhfeD7wCvJq35mNn1uVlDJRaFhA6TmUGnb8tHgJxsyS0elrQjHsfkpaQ8k3JHmbYqijQ6fzZ+7zZlzCFkeXxE3hFJL8Vjqbd6fPbckSzVNS89WPbEHyyHV7D+eW2v2zIszGw5AElfxh2ZjsN/rz3oX7S/Vu7B11XaYm1CL5jZH/rZIDO7u2WA8lSnc9sxTAHeJI3YQkXDkczKRZ8XmTsl/Tn4yH+QmVGq8F48+P4zcRPA+9Lx7fAUX+14NR7o6jlAPl7zY/jaQhHH4A+ycWEF+sSR+MN6Y9xi4xg85G1b89GMSW411JRXt5gKHynpajqMjLshZ5oKPpLehLGF/8nA3UmNYvK8mx+hYB2mHcMU4JN5Oj+ZyYciaGVkQxGkkc6EBbvk5HBOhzKzgFmS3pQsBurwiJnVygDeBfOTPnVnfOR9jDyWeCGT2WqoC56SB3HKXNV3p38P0Nm59/NxC6XL+1RXZTTmLv8+PPLhs/HZwbmMxb+pdq0hOvIsg1sKZNOoFYCf2XgvwyDoiMayqHyCNvpVK8iiIulg3FzrVMY7DLX1xCywQsnKdcyuk+yQz8a9KP8Lz/g+zwoCYKVy1+PJDsapGc2sky3zpEfSDFxovRT/zS7HZ1x3DLFZAyUNVk/HLc0uLPD5KGVoI/DcdB4m33R+JJDHdliX8VY8HYM+JR3zr82sVszhSUwWF2TZBmWzaXzeE87onB0mWxBbFXgJKdEwsC1wEWOxtNvxFty+911pUXYN4JsV2rjQqRmToB6Ip6ZqpNobMC/AHYO+CPxE0i+A461GKrWMYYSTLYqJMGlMkCY7kt4N7Ifrf+fhC8JXtjORypX5KZ7C6RTgWKsZujIASWfhgYbuTfurA98zs8IRuhrkPFWf88YOg2Sj/x4mxqTveXILSZfhjjLfwR/Ae+My74Be19UUSc/CPYffig8OTrSCPAATyg/bDjxohjzo/xZ4woNNkvPPQUV2xanc8rjecW/8QXosrhscqiOGOiSTzShRhxxLexVKoVCQtAMTs+QUWuWoJWGBxocD7lSmdhKIVG4Z3GpoCguJmlGeQPlSJsakr7uGUaWuOWa2uXLx2iVdamb/1eu6uiGtBb4R+Die1Hi1qmWHuYi5gNRRdwHeZmY7DLk5o8IT5hEIkbSkmd0qaf2yQmb2qKRTcNO8jwJvAD4l6X/M7Ig+t7mIzJRsffzBlMVDeT3lscDPyr2fhn+nvxYVkHt+Lo2rQI7Gp7RVprAXSToH118aPnK6sLgIHyQlgQAws9tUEhUvnTeZrYaasrSZfWZAddVJtTdQkiPZ6/HB1EvxNZLPUhLPaAI2vISeS+BC+yTc1fVY4PXDas+obXgi2hVxW+ZL8EWRX5eU2SmVuwEPW7BqOr40cOewv1Nqy7nAcrn95fCww3WuMQW4oOScG1pel8UdOKpc/42MOQG9ocL5V6fXuel1sazeRW3Do0a+bkB1bZF+1+ck+XIqsNUkuAfH4+qwX+ADh2lNrzUMHfj2+FPn1fjI5ee4u/CMgTZkIUIejnYFXNA9WXDeLOAYa7PQKWk7Mzu/j82shDymycaWEjokN/nrzez5Na6xPvAraxN2N3fO1Wb2InkOxDcCfwduMrN1u/sGbeuqnfN0YSWtgS2DW/78hwGtfaUF/4dt0AKvfVv2Ak61HqgthxH97xxgHWBrM9vTzM6kZibmwJG0taS9zcPRXonbk3Y6dyrw7HbCG2AyCO/EccA1kg6UdACudvhJUQFJj0l6NNvwDDll0/SzJK2IW4NcB9xBLrVVQV1vlHSbpEdSfY/lPGg7sT9uOrggCQSenaesrglJj9sdGyXMbDkzm2JmS5nZ8mm/p8Jb0pfSmhCSlpTHgP8TcL+kV/ayriaY2axeCG8YjhXKprje8M149pUTgS+ZWdtkA0F7knCbiacfWy+tZp9sBUF3JJ0BvN0mSWKATkjaHI8DAnCJFWRpkvshP9e6CIKWRvnTqtwXeRjf11tNCx55tqQ1zOz3NcpcZy3JB9SHIGeDpq75a4Pr3wxsaGYmaV98xv9KYD08MNXQg7f1imHkxJwLzAU+I48RsTuwhKTf4Nkyjhp0m0aUNwCb4qNHzOyvKg+O9ARwozxXYD51W8dsN0NiHp4cdzEAFeQLTX/S04DNm1aW1DVV423f30B474SP9JcA1pLHHf+ytU+Zh6TdcbvxtdJDN2M5XNUzsnQyf6Wz/X0TnsypSl6Nm+Y9hYcQnhSGG71i4F9GYzF3MXdrvVzSR/AIdG/Fs18E5TyZhFeWEbxKsttf0TmuyKRA0odx2937cTMz4dYeRRH4rpK0hZldO4Amzpb0czwIf96Ds8iR5wDcCuWidO685JHYiSvwB9gquCt9xmP4AvQosx9j5q/bZuavPa7j3/IMS/fjVkb5TEuFQc4Ggbrw6m1lGE+jqyTdg5vNnG1md5h7BnaMeRG05SR5RqMVk53xu4Cy5LqjYIq2H64WqjPS3BZ4n6Q78JlFP8OuLo/Hvn5V7phR7Ik538weUcWs7+ZBrO7Ena4WNhqZv9ZkP9zCYzrwHTP7M4Ck1+Gz/2HTjVfvOIahQpmZvNJeCxwm6dl4KqHfABdn1gdBZ5Le9+fA83ETzPXxdYTzOpx/kpntlpx/2jm8TKas9HfjacRKyalWug67Kveo/EdZ/7NmccFvkvQ2POvLunjUuSsqtCnvtbwEnjrun/222Ogz96TF418C50l6iBKb/bqY2dX4f6P1+K/xBeShkvUhuVfvBtbi1VvnWkP3xJTnPvwvPBLdNsCDFs48pWReZhXPXd3M7tUkzkqfIekY/IH0K8arKCZ4YuYX+SSdYmZv6qLe3+LWUaeYWcfkxskBYx8menB29PqUu85/nrFR+znAV61D9p+C6+wCbGlmZaFyR4Kq5q8LK2rg1dvK0BX65mEVL0gbaUQelFNZ75s94SeToC7grrQtkbYi8jqJrgIUmdkr08xmg5JTj8MzR70aT4axB8W5NKcCZ5jZK3Eh3k0bfylp/26uMZlI5q+LMk28escxzHCyA8uIsjAi6Xf4SPUOKup9JW0FHIFHQ1sCD6c6slPylhH4BJO7DmUaJ8RI5eeah3a9wcw2SjPIc6w4iFgj882Wxa4puNnoy81sYdSNL5Kk3ziLzXKJmZ1Wp/wwR+CDzIiyMNJE7/td/Cl/Mi4M3gF09FYcBvJodZ9mooqinYAsSknXybuv24QYWUb2h5Olw314ZL0imppv5nM6zscf1gMJxbowImkmcK+Z/WXYbclIFieVFy1bGaYAH2RGlIUOM7tT0tZ4iNJjk+ArjYttZn+UNDXZxR4rjw43mfgZvkC7I56xZC/ci3EC1iAlnZmt1VXr4KjkiPIFPODWsnhc5yLamW+WTn0bLphOapK567/M7GlJ6+GLjb9JqtR+82FgI0l/sJKonYMgjb6/gVujiAZhBYapQqmVESUYT0NPzEtwj7Sj8ZHjvcA7zWzjQbS5ChoLAXpDpg6SdLGZFeaPbFhXXz0Cc/XsZ2aHlx3LffalgsuZmX2lpw0cIJLm4CqDlYCr8LRnj5vZHgNsw3I25PDJqR2NvHrzDHMEXjcjSjCeJp6Yb8d1qR/C1VfPBRpbbvSJbCR2rzxe919xr72eMiCPwIy98DRied7Z5ljGP9scWwa3fnkGMLICHB80Pi5pHzyI3SGS+mKbndbZ5pnZPyXtCWyG5ySdLIv5tb16WxlmSrVth1X3QkJtT8ykdpme3vfa+61XfFXSCsAn8AXX5fGHTa/pu0dgU5d4M1vgfZkeyvvhCThOZLxn5igiSS/GrXf2Scf6JYeOxNdJNsbXVY7BA6P1fDbXkCZeveMYqhmhGmRECRZQ2RMzmccdgI+8BUyRNB8fAU2q+21mWXKGR3DPtH4xCI/Axi7xyVrm47igmwVsZmYP9bh9w+CjeOKC08zsZklrU9N0rgbz0yBnZ3zkfYw8lOtkoYlX7ziGqQNvmxHFzPYpLBgsQB5b/VW4UD6nwBPzY8DrgH1zbsVr4yOUs83sOwNq8qRBHgBrb1ygvAJ4CFjczF5XUm5X/J49JukL+LT8q71cu5H0TTxG+VF4vs3/69W1JwuSlrHxic37UcfFeMiOd+F69wdxlcoL+1nvIBmmAM/saLPXZfEg568qLbwII+l5wGrmgcDyx18G/MXM/tSmzFxgezP7W8vx6XgWmpEOT9otdTwCc/11azzZ8KHA58zsRQVlalkbSHoan1LPZ7y1ysgn/k7qk2OAZc1sjaTeeK+ZfaAPdT0TV2Fda2aXSloD2MbMCuPLD4omXr2tDCOhQ8a/0uvjyYLiP0C3Jl6LAofhU/BWHk+ftWPxVuENYGYP4vE1FklUIyFGjsxnYQfgSDM7nXKP0UOAncxsBauQxMDGEh4sl85fvkq5EeEw3Iv17wBmdj3wsn5UZGb34enLVpL0enzdaFII78RxwDPx+3ExvqBeyzpmmDrw1owohqtSgmJmmNkE/amZzVbnEKVFo8pJFYNCnlzhTbhzTN5Dt6e6+rwZJp4vcXHgp3iC2SL+ktYeXgl8I7W3bCDUtbXBwoSZ3a3xkRn74siXLI2+hIfpEHCEpC+b2Y/6UV8Dnmdmu0ra2cxmSTqemhFZh2mFkplCnSKPylUpI0owNtVqw1Idjmcei62o5HrD4HR8AXMO1ZMsNKGJGSbAbnjgtUPN7GF5BLlPlZTp2tpgIeJuSS8BTNISeGTGfj3cPgVsaik0saRn4AvLk0WAN/HqHccwEjq8wswuUJug5pIW1U5dh2slvcfMxlmcJLvaOe0KNPFYHCLPMbPXDKCeJgkxSDbMD+Ap327D9dS3lRTr2tpgIeJ9uP37s4F7gHOBD/aprnsYr5J4DA9XPFlo4tU7jmHkxDzIzA6QdGybj62OAn9RRNJqwGm46iMT2DNxPewbkt5vZJF0FG7eeGOf6/kk7oW5Pb4Y+S7geDM7oqRcbQ/YYDhI+gnwQnxWZ3gcmWuAP0D7EMWjxtDjgQfNkLQtkMUNvtnMLig6f7KjsWQTi+GC9XZc3dDT7DqS3gyclWzAK5lhtpSfR1K9ZNY7ebf/lnNPMrPd0vtvmNlncp+duyhaXEn6nzaHHwFmpwXhXtZ1QNHnk9iZrTLDGIF/vOjzheGpGNRHHZJNZPTK/TnZf78Utw8+ATejrLyIJukaM9tSKXxtUr1c2UGAz80J+XHhbrUQZJdvQpphPR+PiAm+YH0zHtbhdjP76JCaNpIMYxEzWyhaH3dlzlyMXw/0PJBQMBpkAlrSOsA9ZvZvSdvgyYx7ZvplZm+QtDy+iPkR4BhJpwMnWLVAVnVykRaNjhbVqe/zgFdYSmwu6UhcD7490FO1maQLaZ9CcKGJtzRMR55zgTdZigqWLABOHtACVjBJSSqKmfhq/Dn4A379Mg/JLup7Bu4F/AFgZTN7boUyVT1gbwV2x80Mf4o7lWSOPD81sxf05EuMEJJ+j6eFeyTtrwBcbWbP7/WsRFI+5eA0fLQ/38w+3as6uqEXXr3DtANfg/E2yE9S04QmWCh52szmJyulw8zsCPUvWt1KuMv6W4CVgVOqlDOz8yRdTfr/SFrZ2mfyuRfIVIL35d5n+4sihwDzJF2EP8heBvx3UkX9tpcVmVmrVdblyb1+svBFMzs5efW+GvfqPZKxSK2lDFOAHwdck3SShk9pJ5OXVDAc/iOP4vcOxjLS9MxbNM30dsFHxpvhI/yvAhdahemopPfiuTD/BTxNWmSlTSYfi4ibEzAPKPVrYEv83n3OzLKs9GX29LXQ+PR5U4DNcc/HycIEr15JB9a5wFCtUNIUZ+u0e4mZ9WWkFYwOkjbAbYWvNLMTJK0FvMXMDu7R9f+Gq2ZOxKevtTLBSLoNeHG70ARBNTS4RBp/Zix93nzgz8CXzeyyXtfVhOTA+Bfcq3dzfFBwjdVIsDJsAT4VWI3xLtN3Da1BwUKPpKXN7PEuyp8NvLGbayzKqEMijYVpYbEqkpbGvXpvNLPbklfvC83s3KrXGJoKRdKH8RjV9+NTiWwq2hN732C0yGymc/bg4+iVHXgPBO9ngSuSDjzvFl+WoDhw+p5II0PS4sD7GQuWdRHwg7qzrn7R0Kt3HMO0Qvkj8KIsTkGwaCPpWSkeSVt78F7ZgXeLpGuAy3CTt6ez42Y2q8Y1Vgf+YWb9jPUyKZF0rZltkayNXpTMReeZ2SZ9qOtofP0k+23eDjxlZu/udV1N6IVX7zAXMe/GPbCCAOAsxsyo3j7sxhQw38wKndEqcBywjqRTzOyTvWjUCHGPPArpL4HzJD2E5z3tB1u06JMvkHR9n+pqQtOAagsYpgC/HbhI0q8YPxUNT8xFkyXk6a5e0i7QWb+DnEn6b3xAcXTJrPBCSfsCZzK+37YzI2yLmb1SkoANmrZ3VDGzN6S3ByZHmxVwr9h+8JSkdSwlOZFnoepL6NqGNAqolmeYAvyutC1BeUD8YOHnfXj+xxUZMx/MGETkvmuAdYDv4CaMnXhbev1s7lhbM8KMTt6lZnZzNw0eRfL3Al/3moGnVuxHXPpP4Q/c21Nda+Jp9CYLdbx62xLBrIJJhaR9zOyYYbejlwzau3QyMwRP2yXxsB0Cbp1s6w5NAqqNKz+EYFZnUhAHwsx2GmBzgkmIPOD/DMabl/bUyStNpw8HXowvRl4JfMzMbi8p13Z0XtS+XOCrTwFPZN6li2gwq77fC0lbAHdbCq2cfrM3AXcCB9ZRd012hqFCOXQIdQYjgqTjcFXGPMb0lUbvvXSPB76HLyQBvBWPTljmxrxF7v00YDt8EaqofZl36V70wbt0xBjEvchS3mXJvg8GPgxsAhyFx74ZGpIeo/0gtnbS6lChBJMKSbcAG1Rxa++ynqutJZO8pKvMbKua11kBOK5o5thv79JRYhD3QtL1mfWJpO8BD5rZgWm/LyaLwyIEeDCpkHQy8BEzu7dP18/iY3waeBh3qTc8oNWSNparter1FgduWBQjC05WJN0EbJKCot0K7Ju56ku6ycw2LL7C4JC0Ge7IY8BldcOJDNMKJQjasQrwu+QwkzfT69XayBzG4mMAvDf3mQGFArxlDWcKbgp4Uodz23qVLqisR96lo0QuPsk4zKyjFU8DTgAuTnFv/gVcmup+HpPI90TSl4BdGbOw+rGkk83sq5WvESPwYDIh6eXtjpvZpAgD2tK++cCdZnZPh3MHkmVolJDHX8+Yhguwlc3sSz2uZytgdTzj0j/TsfWAZevE2+4nSV24qZk9kfaXwlP1VZ7NDdOVfj3cTnNNxlsbLHJBbYLBkwKp7cBEa5dwJBswki4zs63Lz1y4kPQbYHczezjtr4gn+tix6jWGqUI5Gfg+brg+mbyjgiGQ/YnbrNDXXpmvyJnAE7TENCmjgwXBI8Bs4BPtzBDTaPAI4AW409pU4J99+E6TnqTzzZiC24TXch8fdSQdgfehfwM3Szov7W+Px9mpzDAF+HwzO3KI9QeTiz0AzGxQf+bnNNRBfxuP3XE8/nB5K54k4PfAj4Bt2pT5bjrvZFxgvQPPDbko8q3c+/nAHcBuw2nK0JidXucAp+WOX1T3QsNUoRwIPIB/gUYxJYKFB+WytqcgT2/qc33fAM6vE3s5letofpg3X2v5fLaZzZR0Q/bQkHSFmb2kqy8RLPIMcwS+V3rNp1EqjCkRLNQo934QfeAq4DRJU4D/UF1V87Sk3YBfpP28U0in0dDjkpbAc0EegufKrB24aGFB0g7A/2N8Rp4vD69Fw0HSusDXcUum/L2o3P+HJsDNbK1h1R1MSqzD+37xLdyN/saaTkN74C74/4u38ypgz2RB8KEOZd6O63s/BHwMeC7u2r3IIen7ePCqbYGj8QfgNUNt1PA4Fk9q8x38fuzN+IFMKcNOqbYhE58+kdh4EUTSU8A/8Q68FJBlzunLIqakc4DXmlnlBcwu61sKWMPMfj+I+iYrmRop97oscKqZvWrYbRs0kuaY2eaSbjSzF6Zjl5rZf1W9xjBTqh2AL/hsAPwaeC2+AhsCfBHEzKYOuMp78Xj0v6FGPPpk/noksJqZbShpI2CnIucLSa/HYwAtAawlaRM8ue6iGLjtX+n18ZSB5u/AojobfyKp8G6T9CE8wfGqdS4wpS/Nqsab8UBA95nZ3sDGwJJDbE+waPFn4HxcqC6X28r4IR4L/D8AZnYDbmFSxIHAlrjrPmY2D7c/XxQ5K9k7fxMPAnYH7jm5KPJRXJ30ETwr/Z4Ux6KfwDAXMf9lZk9Lmi9pedwiJRYwg4FgZk0T6S5tZtd4Qp0FzC8pM9/MHmkps0iSizVziqSzgGlmNmnc2wfMDDO7Fvg/UqIJSbsCV1e9wDBH4LPTk/iHuD3kdSy6ixnBgJE0XdI3Jf1a0gXZVqHo31JWmSwN1ptxdUwRN0l6GzBV0rrJkeOK7r7BaCFpC0nPzO2/A48h85VcgLFFjc9WPNaRSRELRdIMYPk0HQ2CviPpXODnwCfx8KZ74WFHP1NSbm08pvRLgIdwVcweRXFNJC0NfJ5c5hXgK1kMjEUBSdcBrzSzf6QY3ScyFqP7BWY21Bjdg0TSa4HX4Q5MP899tDweSnnLytcaoiPPG4ALsulTGo1vY2a/HEqDgkWKnAVA3rnmYjNrG0yrTfllgClm9pikj5rZYf1s76izKMXoLkPSxviD68tAPojXY8CFZvZQ5WsNUYBP+NG0iKaZCgZPznvyHOB/cPf4X5jZOg2udZeZrdHm+BlF5RYlK5RRitE9KFIs+cXowrx0mIuY7fTvEZ88GBRflWfT+QQeaGp53CqgCZ1WJ18M3I1bWVxdcN6iwEjE6B4wr6FL89JhjsB/hJtVfQ9fEPowsJKZvXMoDQoWeZqqQgpG4FPxCHO7AxsBvwJOMLObu23rKDIKMboHiaQ5wCuAizLNQ16lV+kaQxTgywBfxJOPCjgX+Gr2wwbBoOkkiNNnRYlolzKzwtmjpCVxQf5NfJR1RLftDUabLDBaXnVcV4APMxbKP4H9h1V/ELSho4qjaZjbJLh3wIX3DFzffmpRmWCRYZx5Ke7QU8u8dOAjcEmHmdlHNT634AIWpYWdYHJRNAJveL1ZwIbAb4ATzeymXl07GH16YV46DAG+uZnN0STPfRgsnHSrCqlZ19N4gC5a6uxXlqFgEWMoOvC0uDPLzPYceOVBEASTgA5aiCw93w+qjMSH4kpvZk8B01OQ+yAIgkWR2/E4KD9M26PA/cB6ab+UYdpd3wFcnpwdFlieRFbwIAgWETY1s5fl9s+UdImZvUxSJVPTYQrwv6ZtCotYVuogCAJcC7GGmd0FIGkNYJX02ZNVLjBMM8KDwO3Bw/Y7CIJFkE8Al0n6E76wvRbwgeQjM6vKBYbpyPNi4BjcC2uNFODlvWb2gaE0KAiCYMAkP4Hn4wL81roRKocZD/ww4NV4SiXM7HrgZUUFgiAIFhaSHfingA+lLE3PlbRjnWsMU4BjZne3HHpqKA0JgiAYPMfiuu4Xp/17gI65VdsxTAF+t6SXACZpCUmfBG4ZYnuCIAgGyTpmdghj+VX/Rc2IlcMU4O8DPgg8G3/ybJL2gyAIFgWelLQUY+n51gH+XecCkyKlWhAEwaKGpFfhsVA2wKOxvhR4p5ldVPkaQ7RCWQuPAT6DnDljBLMKgmBhRtJ3gePN7ApJzwC2wlUnV5nZ3+pca5iOPL/EzQjPBJ4eYjuCIAgGyW3AtyStjic1PiFZodRmmCPwq83sRUOpPAiCYMhIWhN4a9qm4WnnTjSzP1S+xhAF+NuAdXHdzwLF/aKYWikIgkUbSZsCPwI2MrOpVcsNU4XyQuDteE64TIViaT8IgmChJmWlfw0+At8OuBg4qNY1hjgCvxV/2lQK2hIEQbAwIClLdL0DcA1wIvDLJjGhhjkCvx5YEXhgiG0IgiAYNJ8Djgc+aWb/6OZCwxyBXwRsBFzLeB14mBEGQRBUYJgj8AOGWHcQBMHIM2k8MSW9FHibmYU7fRAEQQWGOQJH0ibA24DdgD8DpwyzPUEQBKPEwAW4pPVws5nd8VjgP8dnAtsOui1BEASjzMBVKJKeBi4F9jGzP6Zjt5vZ2gNtSBAEwYgzjHCybwLuAy6U9ENJ21EzBm4QBEEwXDPCZYBdcFXKK/AknqeZ2blDaVAQBMGIMSmsUCStDOwKvMXMwpU+CIKgApNCgAdBEAT1GWpS4yAIgqA5IcCDIAhGlBDgwaRG0lOS5uW2GV1eb4akm3L7W0q6SNJtkq6T9CtJL+y64UEwAIbqiRkEFfiXmW3SjwtLWg04CQ/hcEU6tjWwDnBjy7mLmdn8frQjCJoSI/Bg5JC0iaSrJN0g6TRJK5Uc31zS9ZKuBPKxdj4EzMqEN4CZXWZmv0zlfizp25IuBL5RcP2LJM1M71eRdEd6/05Jp0s6W9LvJUUAt6CnhAAPJjtL5dQnp6VjPwE+Y2Yb4SPlA0qOHwt8xMxe3HLt/weUpfBbD3ilmX2i4PpFbAnsAWwC7JoJ+iDoBSHAg8nOv8xsk7S9QdIKwIpmdnH6fBbwshrHj+tUkaSrJd0i6fDc4ZPN7KlO16/Q/vPM7O9m9i/gVGDrSt86CCoQAjxY2BGea7UdNwObZTtm9iLgi8AKuXOqpLmaz9h/aVrLZ611h+NF0DNCgAcjhZk9Ajwk6b/SobcDFxccfxh4JC1OgqszMr4HvFPSS3LHlq5Tb3p/B7B5ev/mlqLbS1pZ0lJ46IjLK33RIKhAWKEEo8hewPclLQ3cDuxdcnxv4EeSHgfOyS5iZvdJegu+QPlsPD/r34Av16z3UOAkSW8HLmgpcxmutnkecLyZzW74nYNgAuFKHwR9QtI7gZlm9qFhtyVYOAkVShAEwYgSI/AgCIIRJUbgQRAEI0oI8CAIghElBHgQBMGIEgI8CIJgRAkBHgRBMKKEAA+CIBhR/j/+RSIE8w31MQAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "grouped['Fat_g'].plot(kind='bar')"
+    "Si quiero imprimir un grafico que muestre la diferencias de promedio de grasa entre los diferentes grupos de comida, usando la agrupacion realizada anteriormente, puedo crear un nuevo grafico."
    ]
   },
   {
@@ -1955,7 +2082,7 @@
     "collapsed": true
    },
    "source": [
-    "Ordeno los valores en orden descendente y me quedo con los 5 primeros"
+    "Primero ordeno los valores en orden descendente y me quedo con los 5 primeros, y luego con la ultima linea de codigo graficamos, pero esta vez le indicamos que el tipo de grafico sera de torta."
    ]
   },
   {