Jupyter Notebook INE's template.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"position: relative; text-align: right;\">\n",
    "<img src=\"https://user-images.githubusercontent.com/7065401/98614301-dcf01780-22d6-11eb-9c8f-65ebfceac6f6.png\" style=\"width: 130px; display: inline-block;\"></img>\n",
    "\n",
    "<img src=\"https://user-images.githubusercontent.com/7065401/98864025-08deda80-2448-11eb-9600-22aa17884cdf.png\" style=\"height: 100%; max-height: inherit; position: absolute; top: 20%; left: 0px;\"></img>\n",
    "<br>\n",
    "\n",
    "<h2 style=\"font-weight: bold;\">\n",
    "    Santiago Basulto\n",
    "</h2>\n",
    "\n",
    "<h3 style=\"color: #ef7d22; margin-top: 0.8em\">\n",
    "    Senior Python Data Scientist\n",
    "</h3>\n",
    "<hr>\n",
    "<br><br>\n",
    "\n",
    "<p style=\"font-size: 80%; text-align: right; margin: 10px 0px;\">\n",
    "    sbasulto@ine.com\n",
    "</p>\n",
    "<p style=\"font-size: 80%; text-align: right; margin: 10px 0px;\">\n",
    "    @santiagobasulto\n",
    "</p>\n",
    "<p style=\"font-size: 80%; text-align: right; margin: 10px 0px;\">\n",
    "    linkedin.com/in/santiagobasulto/\n",
    "</p>\n",
    "\n",
    "</div>\n",
    "\n",
    "<br><br><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<div style=\"position: relative;\">\n",
    "<img src=\"https://user-images.githubusercontent.com/7065401/98728503-5ab82f80-2378-11eb-9c79-adeb308fc647.png\"></img>\n",
    "\n",
    "<h1 style=\"color: white; position: absolute; top:30%; left:10%;\">\n",
    "    Course name\n",
    "</h1>\n",
    "\n",
    "<h3 style=\"color: #ef7d22; font-weight: normal; position: absolute; top:43%; left:10%;\">\n",
    "    Instructor name\n",
    "</h3>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h2 style=\"font-weight: bold;\">\n",
    "    Topic 1\n",
    "</h2>\n",
    "\n",
    "![orange-divider](https://user-images.githubusercontent.com/7065401/98619088-44ab6000-22e1-11eb-8f6d-5532e68ab274.png)\n",
    "\n",
    "- Item 1\n",
    "- Item 2\n",
    "- Item 3\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<div style=\"width: 100%; background-color: #222; text-align: center\">\n",
    "<br><br>\n",
    "\n",
    "<h1 style=\"color: white; font-weight: bold;\">\n",
    "    Content separator 1\n",
    "</h1>\n",
    "    \n",
    "<h3 style=\"color: #ef7d22; font-weight: normal;\">\n",
    "    Content separator 1\n",
    "</h3>\n",
    "\n",
    "<br><br> \n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h2 style=\"font-weight: bold;\">\n",
    "    Topic 2\n",
    "</h2>\n",
    "\n",
    "![orange-divider](https://user-images.githubusercontent.com/7065401/98619088-44ab6000-22e1-11eb-8f6d-5532e68ab274.png)\n",
    "\n",
    "Lorem ipsum dolor sit amet consectetur ad sapien eget aliquet platea lacinia, dignissim porta nunc nam malesuada tortor **habitant vestibulum consequat libero duis**. And _italic_ text is also available!\n",
    "\n",
    "\n",
    "> You can use blockquotes as shown here.\n",
    "\n",
    "\n",
    "**LaTeX** is also available, this formula $f(x) = x^2$ is an example.\n",
    "\n",
    "$$g(x) = \\frac{1}{x}$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<div style=\"width: 100%; background-color: #ef7d22; text-align: center\">\n",
    "<br><br>\n",
    "\n",
    "<h1 style=\"color: white; font-weight: bold;\">\n",
    "    Content separator 2\n",
    "</h1>\n",
    "    \n",
    "<h3 style=\"color: white; font-weight: normal;\">\n",
    "    Content separator 2\n",
    "</h3>\n",
    "<br><br> \n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h2 style=\"font-weight: bold;\">\n",
    "    Topic 3\n",
    "</h2>\n",
    "\n",
    "![orange-divider](https://user-images.githubusercontent.com/7065401/98619088-44ab6000-22e1-11eb-8f6d-5532e68ab274.png)\n",
    "\n",
    "Follow this quick [Markdown tutorial](https://www.markdownguide.org/basic-syntax) to learn how to use its syntax.\n",
    "\n",
    "- Item 1\n",
    "- Item 2\n",
    "- Item 3\n",
    "\n",
    "> Avoid content overflow!\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<div style=\"width: 100%; background-color: #ef7d22; text-align: center\">\n",
    "<br><br>\n",
    "\n",
    "<h1 style=\"color: white; font-weight: bold;\">\n",
    "    Content separator 2\n",
    "</h1>\n",
    "    \n",
    "<h3 style=\"color: white; font-weight: normal;\">\n",
    "    Content separator 2\n",
    "</h3>\n",
    "\n",
    "<br><br> \n",
    "</div>\n",
    "\n",
    "<hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h2 style=\"font-weight: bold;\">\n",
    "    Topic 4\n",
    "</h2>\n",
    "\n",
    "![orange-divider](https://user-images.githubusercontent.com/7065401/98619088-44ab6000-22e1-11eb-8f6d-5532e68ab274.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 + 2 + 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def sum(num1, num2):\n",
    "    return num1 + num2\n",
    "\n",
    "sum(4, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Or Markdown code:\n",
    "\n",
    "```python\n",
    "def my_test_function(x, y, z):\n",
    "    a = x + y\n",
    "    b = z\n",
    "    \n",
    "    return a * b\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   0  1   2\n",
       "0  1  2  10\n",
       "1  3  5   2\n",
       "2  7  4   4"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.DataFrame([[1,2,10], [3,5,2], [7,4,4]])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1243f76a0>]"
      ]
     },
     "execution_count": 5,
     "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": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.plot(df[0], df[1], color='green')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 3 artists>"
      ]
     },
     "execution_count": 6,
     "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": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.bar(df[0], df[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<h2 style=\"font-weight: bold;\">\n",
    "    Wrapping up\n",
    "</h2>\n",
    "\n",
    "![orange-divider](https://user-images.githubusercontent.com/7065401/98619088-44ab6000-22e1-11eb-8f6d-5532e68ab274.png)\n",
    "\n",
    "\n",
    "Blocks of code are either fenced by lines with three back-ticks \\`\\`\\`, or are indented with four spaces.\n",
    " \n",
    "```python\n",
    "s = \"Python syntax highlighting\"\n",
    "print s\n",
    "```\n",
    "\n",
    "Also, this is an example table:\n",
    "\n",
    "| Date    | Value |\n",
    "|---------|-------|\n",
    "| 2017-01 | 366   |\n",
    "| 2018-01 | 250   |\n",
    "| 2019-01 | 250   |\n",
    "\n",
    "\n",
    "> Finally, don't forget to keep that _separator_ at the end of your Notebook.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<div style=\"position: relative;\">\n",
    "<img src=\"https://user-images.githubusercontent.com/7065401/98729912-57be3e80-237a-11eb-80e4-233ac344b391.png\"></img>\n",
    "</div>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}