{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Notes on Week 2 2018-02-02"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "to make a new cell press 'b'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "3+5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "to make a new markdown cell press 'b' and then 'm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "to execute a cell press 'control + enter'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "pressing 'shift + enter' will run a cell and then make a new one"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "if you are inside of a cell and want to make it a markdown, you can press 'control + m' and then 'm'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "to delete a cell press 'd''d'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "6==7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "can't assign to literal (<ipython-input-3-5becc1e26db9>, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-3-5becc1e26db9>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    6=7\u001b[0m\n\u001b[0m       ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m can't assign to literal\n"
     ]
    }
   ],
   "source": [
    "6=7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To include an <b>image</b> you can use normal md language <br>![](https://jupyter.brynmawr.edu/images/jupyter-sq-text.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To make a variable simply type it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x=50*2/3+1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "to retrive it you can simply type it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "34.333333333333336"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In python variables have types, to evaulate the type we can do:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "float"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(5/4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Suppose there is a piegeon, suppose there is.'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"Suppose there is a piegeon, suppose there is.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "roastbeef= 'Suppose there is a piegeon, suppose there is. \\\"someone\\\"'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "two_lines='line one\\nline two'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'line one\\nline two'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "two_lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "line one\n",
      "line two\n"
     ]
    }
   ],
   "source": [
    "print(two_lines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x=5\n",
    "y=4\n",
    "z=x+y\n",
    "z"
   ]
  }
 ],
 "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": "3.6.0"
  }
 },
 "nbformat": 4,
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}