From a424471c2e2165c2077e4bffa726969c4641b8d7 Mon Sep 17 00:00:00 2001
From: Laura <laura.marcela.becerra@gmail.com>
Date: Mon, 6 Nov 2023 11:05:06 -0500
Subject: [PATCH] hide cells

---
 .../Pandas-checkpoint.ipynb                   | 50 +++++++++++++------
 .../apiMakeSens-checkpoint.ipynb              | 18 ++++---
 Book/Jupyter_Notebooks/Pandas.ipynb           | 10 +++-
 Book/Jupyter_Notebooks/apiMakeSens.ipynb      | 18 ++++---
 4 files changed, 69 insertions(+), 27 deletions(-)

diff --git a/Book/Jupyter_Notebooks/.ipynb_checkpoints/Pandas-checkpoint.ipynb b/Book/Jupyter_Notebooks/.ipynb_checkpoints/Pandas-checkpoint.ipynb
index d63a668..a90ec6a 100644
--- a/Book/Jupyter_Notebooks/.ipynb_checkpoints/Pandas-checkpoint.ipynb
+++ b/Book/Jupyter_Notebooks/.ipynb_checkpoints/Pandas-checkpoint.ipynb
@@ -47,6 +47,42 @@
     "*  Visualización de datos utilizando herramientas integradas o integrando con otras bibliotecas como Matplotlib y Seaborn.\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "hide-input"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<iframe width=\"560\" height=\"315\" src=\"https:&#x2F;&#x2F;www.canva.com&#x2F;design&#x2F;DAFtE_0BP_c&#x2F;view?embed\" title=\"Pandas Review\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen></iframe>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from IPython.display import HTML\n",
+    "import warnings\n",
+    "\n",
+    "warnings.filterwarnings('ignore')\n",
+    "\n",
+    "HTML('<iframe width=\"560\" height=\"315\" src=\"https:&#x2F;&#x2F;www.canva.com&#x2F;design&#x2F;DAFtE_0BP_c&#x2F;view?embed\" title=\"Pandas Review\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen></iframe>')"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -1688,20 +1724,6 @@
    "outputs": [],
    "source": []
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/Book/Jupyter_Notebooks/.ipynb_checkpoints/apiMakeSens-checkpoint.ipynb b/Book/Jupyter_Notebooks/.ipynb_checkpoints/apiMakeSens-checkpoint.ipynb
index b67a3a5..139839c 100644
--- a/Book/Jupyter_Notebooks/.ipynb_checkpoints/apiMakeSens-checkpoint.ipynb
+++ b/Book/Jupyter_Notebooks/.ipynb_checkpoints/apiMakeSens-checkpoint.ipynb
@@ -503,10 +503,8 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 52,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
     "Resumiendo:"
    ]
@@ -514,12 +512,20 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {},
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "hide-input"
+    ]
+   },
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<iframe width=\"560\" height=\"315\" src=\"https:&#x2F;&#x2F;www.canva.com&#x2F;design&#x2F;DAFwVICi7qs&#x2F;view?embed\" title=\"Pandas Review\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen></iframe>"
+       "<iframe width=\"660\" height=\"415\" src=\"https:&#x2F;&#x2F;www.canva.com&#x2F;design&#x2F;DAFwVICi7qs&#x2F;view?embed\" title=\"Pandas Review\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen></iframe>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -536,7 +542,7 @@
     "\n",
     "warnings.filterwarnings('ignore')\n",
     "\n",
-    "HTML('<iframe width=\"560\" height=\"315\" src=\"https:&#x2F;&#x2F;www.canva.com&#x2F;design&#x2F;DAFwVICi7qs&#x2F;view?embed\" title=\"Pandas Review\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen></iframe>')"
+    "HTML('<iframe width=\"660\" height=\"415\" src=\"https:&#x2F;&#x2F;www.canva.com&#x2F;design&#x2F;DAFwVICi7qs&#x2F;view?embed\" title=\"Pandas Review\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen></iframe>')"
    ]
   },
   {
diff --git a/Book/Jupyter_Notebooks/Pandas.ipynb b/Book/Jupyter_Notebooks/Pandas.ipynb
index 8f057e6..a90ec6a 100644
--- a/Book/Jupyter_Notebooks/Pandas.ipynb
+++ b/Book/Jupyter_Notebooks/Pandas.ipynb
@@ -50,7 +50,15 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {},
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "hide-input"
+    ]
+   },
    "outputs": [
     {
      "data": {
diff --git a/Book/Jupyter_Notebooks/apiMakeSens.ipynb b/Book/Jupyter_Notebooks/apiMakeSens.ipynb
index b67a3a5..139839c 100644
--- a/Book/Jupyter_Notebooks/apiMakeSens.ipynb
+++ b/Book/Jupyter_Notebooks/apiMakeSens.ipynb
@@ -503,10 +503,8 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 52,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
     "Resumiendo:"
    ]
@@ -514,12 +512,20 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {},
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": [
+     "hide-input"
+    ]
+   },
    "outputs": [
     {
      "data": {
       "text/html": [
-       "<iframe width=\"560\" height=\"315\" src=\"https:&#x2F;&#x2F;www.canva.com&#x2F;design&#x2F;DAFwVICi7qs&#x2F;view?embed\" title=\"Pandas Review\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen></iframe>"
+       "<iframe width=\"660\" height=\"415\" src=\"https:&#x2F;&#x2F;www.canva.com&#x2F;design&#x2F;DAFwVICi7qs&#x2F;view?embed\" title=\"Pandas Review\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen></iframe>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -536,7 +542,7 @@
     "\n",
     "warnings.filterwarnings('ignore')\n",
     "\n",
-    "HTML('<iframe width=\"560\" height=\"315\" src=\"https:&#x2F;&#x2F;www.canva.com&#x2F;design&#x2F;DAFwVICi7qs&#x2F;view?embed\" title=\"Pandas Review\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen></iframe>')"
+    "HTML('<iframe width=\"660\" height=\"415\" src=\"https:&#x2F;&#x2F;www.canva.com&#x2F;design&#x2F;DAFwVICi7qs&#x2F;view?embed\" title=\"Pandas Review\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen></iframe>')"
    ]
   },
   {
-- 
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