Added in video exercises

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guipsamora · Aug 5, 2020 · 7243941 · 7243941
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diff --git a/01_Getting_&_Knowing_Your_Data/World Food Facts/Exercises_with_solutions.ipynb b/01_Getting_&_Knowing_Your_Data/World Food Facts/Exercises_with_solutions.ipynb
@@ -4,7 +4,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Ex1 - Getting and knowing your Data"
+    "# Ex1 - Getting and knowing your Data\n",
+    "Check out [World Food Facts Exercises Video Tutorial](https://youtu.be/_jCSK4cMcVw) to watch a data scientist go through the exercises"
    ]
   },
   {
@@ -43,9 +44,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stderr",
@@ -70,9 +69,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -303,9 +300,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -325,9 +320,7 @@
   {
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    "execution_count": 6,
-   "metadata": {
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-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -354,9 +347,7 @@
   {
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    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -391,9 +382,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
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+   "metadata": {},
    "outputs": [
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@@ -429,9 +418,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
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-   },
+   "metadata": {},
    "outputs": [
     {
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@@ -458,9 +445,7 @@
   {
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    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
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+   "metadata": {},
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@@ -487,9 +472,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
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@@ -516,9 +499,7 @@
   {
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    "execution_count": 13,
-   "metadata": {
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+   "metadata": {},
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      "data": {
@@ -539,21 +520,34 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [conda root]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-root-py"
+   "name": "python3"
   },
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    "codemirror_mode": {
     "name": "ipython",
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+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.12"
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
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diff --git a/02_Filtering_&_Sorting/Chipotle/Exercises_with_solutions.ipynb b/02_Filtering_&_Sorting/Chipotle/Exercises_with_solutions.ipynb
@@ -4,7 +4,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Ex1 - Filtering and Sorting Data"
+    "# Ex1 - Filtering and Sorting Data\n",
+    "\n",
+    "Check out [Chipotle Exercises Video Tutorial](https://youtu.be/ZZPiWZpdekA) to watch a data scientist go through the exercises"
    ]
   },
   {
@@ -2212,7 +2214,20 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.3"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
   }
  },
  "nbformat": 4,

diff --git a/02_Filtering_&_Sorting/Euro12/Exercises_with_Solutions.ipynb b/02_Filtering_&_Sorting/Euro12/Exercises_with_Solutions.ipynb
@@ -4,7 +4,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Ex2 - Filtering and Sorting Data"
+    "# Ex2 - Filtering and Sorting Data\n",
+    "Check out [Euro 12 Exercises Video Tutorial](https://youtu.be/iqk5d48Qisg) to watch a data scientist go through the exercises"
    ]
   },
   {
@@ -19,9 +20,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import pandas as pd"
@@ -44,9 +43,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -583,9 +580,7 @@
   {
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    "execution_count": 37,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
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      "data": {
@@ -628,9 +623,7 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -657,9 +650,7 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -722,9 +713,7 @@
   {
    "cell_type": "code",
    "execution_count": 82,
-   "metadata": {
-    "collapsed": false
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+   "metadata": {},
    "outputs": [
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      "data": {
@@ -883,7 +872,6 @@
    "cell_type": "code",
    "execution_count": 56,
    "metadata": {
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     "scrolled": true
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@@ -1040,9 +1028,7 @@
   {
    "cell_type": "code",
    "execution_count": 55,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1069,9 +1055,7 @@
   {
    "cell_type": "code",
    "execution_count": 57,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1201,9 +1185,7 @@
   {
    "cell_type": "code",
    "execution_count": 66,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1333,9 +1315,7 @@
   {
    "cell_type": "code",
    "execution_count": 84,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -1579,9 +1559,7 @@
   {
    "cell_type": "code",
    "execution_count": 86,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
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@@ -2119,9 +2097,7 @@
   {
    "cell_type": "code",
    "execution_count": 89,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2177,23 +2153,36 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "python2"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.12"
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }