working-with-cells.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Working with Cells\n",
    "\n",
    "Cell can be run by seletecting the cell by selecting it the click the \"run cell\" button above. \n",
    "But, it's easier to run it by pressing **Shift + Enter**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Select the cell, then press Shift + Enter\n",
    "6+3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now try assigning a value to a variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pi_school = 'exponential growth'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pi_school[:11]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Code completion\n",
    "\n",
    "This helps you to complete the name of variables, function names and so on. Code completion also comes in handy if you're using a module but don't quite remember which function you're looking for or what the available functions are.\n",
    "\n",
    "> **Exercise:** Place the cursor at the end of `pi_` in the next cell and press **tab**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "pi_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run this cell\n",
    "mindful = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Complete the name here again, choose one from the menu\n",
    "mind"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check completion with random package"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run this\n",
    "import random"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **Exercise:** In the cell below, place the cursor after `random.` then press **tab** to bring up the code completion menu for the module. Choose `random.randint` from the list, you can move through the menu with the up and down arrow keys."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "random."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above you should have seen all the functions available from the random module. Maybe you're looking to draw random numbers from a [Gaussian distribution](https://en.wikipedia.org/wiki/Normal_distribution), also known as the normal distribution or the \"bell curve\". \n",
    "\n",
    "## Tooltips\n",
    "\n",
    "You see there is the function `random.gauss` but how do you use it? You could check out the [documentation](https://docs.python.org/3/library/random.html), or just look up the documentation in the notebook itself.\n",
    "\n",
    "> **Exercise:** In the cell below, place the cursor after `random.gauss` the press **shift + tab** to bring up the tooltip."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "random.gauss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You should have seen some simple documentation like this:\n",
    "\n",
    "    Signature: random.gauss(mu, sigma)\n",
    "    Docstring:\n",
    "    Gaussian distribution.\n",
    "    \n",
    "The function takes two arguments, `mu` and `sigma`. These are the standard symbols for the mean and the standard deviation, respectively, of the Gaussian distribution. Maybe you're not familiar with this though, and you need to know what the parameters actually mean. This will happen often, you'll find some function, but you need more information. You can show more information by pressing **shift + tab** twice.\n",
    "\n",
    "> **Exercise:** In the cell below, show the full help documentation by pressing **shift + tab** twice."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "random.gauss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You should see more help text like this:\n",
    "\n",
    "    mu is the mean, and sigma is the standard deviation.  This is\n",
    "    slightly faster than the normalvariate() function."
   ]
  }
 ],
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