diff --git a/Clase 3.ipynb b/Clase 3.ipynb
index a792215..aa1a6b2 100644
--- a/Clase 3.ipynb	
+++ b/Clase 3.ipynb	
@@ -58,11 +58,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Overwriting cuadratica.py\n"
+     ]
+    }
+   ],
    "source": [
     "%%writefile cuadratica.py     \n",
     "\n",
@@ -77,6 +85,26 @@
     "       "
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%%writefile?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -86,7 +114,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
@@ -104,13 +132,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
-    "cuadratica.raices?"
+    "cuadratica.raices??"
    ]
   },
   {
@@ -146,7 +174,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.0, 0.0)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cuad.raices(2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
@@ -166,7 +216,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {
     "collapsed": false
    },
@@ -178,13 +228,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "raices?"
+    "raices is cuadratica.raices"
    ]
   },
   {
@@ -204,20 +265,202 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Ejercicios\n",
+    "#### Ejercicios\n",
     "\n",
     "1. Cree un módulo `circunferencia.py` que defina una constante `PI` y una función `area(r)` que calcula el área para una circunferencia de radio `r`. \n",
     "\n",
-    "2. Desde una celda de la sesión intereactiva, importe todo el módulo como un alias `circle` y verifique `circle.PI` y `circle.area()`. Luego importe utilizando la forma `from circunferencia import ...` que importe también la función y la constante\n",
+    "2. Desde una celda de la sesión interactiva, importe todo el módulo como un alias `circle` y verifique `circle.PI` y `circle.area()`. Luego importe utilizando la forma `from circunferencia import ...` que importe también la función y la constante\n",
     "\n",
     "3. verifique que circle.area y area son el mismo objeto"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Writing circunferencia.py\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%writefile circunferencia.py\n",
+    "\n",
+    "__all__ = ['area', 'PI']\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n",
+    "from funciones_especiales import blah\n",
+    "from math import pi\n",
+    "PI = pi\n",
+    "\n",
+    "def area(r):\n",
+    "    return PI*r**2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "\n",
+    "class A:\n",
+    "    PI = 32\n",
+    "    \n",
+    "    def __init__(self, pi=3.14):\n",
+    "        self.pi = pi\n",
+    "        \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "mi_a = A()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "32"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "A.PI"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.141592653589793"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import circunferencia as circle\n",
+    "\n",
+    "circle.PI"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "314.1592653589793"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "circle.area(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.141592653589793"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "circle.pi"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "706.8583470577034"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from circunferencia import area\n",
+    "\n",
+    "area(15)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### Paquetes: módulos de módulos\n",
+    "### Paquetes: módulos de módulos\n",
     "\n",
     "Cuando tenemos muchos módulos que están relacionados es bueno armar un **paquete**. Un paquete de modulos es un simple directorio con un módulo especial llamado `__init__.py` (que puede estar vacio) y tantos modulos y subpaquetes como queramos. \n",
     "\n",
@@ -235,34 +478,79 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "mkdir: no se puede crear el directorio «paquete»: El archivo ya existe\r\n"
+     ]
+    }
+   ],
    "source": [
     "%mkdir paquete             # creamos un directorio  \"paquete\""
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 40,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Overwriting paquete/__init__.py\n"
+     ]
+    }
+   ],
    "source": [
-    "%%writefile paquete/__init__.py          # el archivo __init__.py  vacio\n",
+    "%%writefile paquete/__init__.py     \n",
+    "\n",
     " "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 41,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\r\n",
+      " "
+     ]
+    }
+   ],
+   "source": [
+    "!cat paquete/__init__.py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Overwriting paquete/modulo.py\n"
+     ]
+    }
+   ],
    "source": [
     "%%writefile paquete/modulo.py\n",
     "\n",
@@ -293,7 +581,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 44,
    "metadata": {
     "collapsed": false
    },
@@ -307,6 +595,13 @@
     "# ![](files/M.bmp)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![](files/M.bmp)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -354,22 +649,61 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 46,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Component,Mol fraction\r\n",
+      "n2,0.46\r\n",
+      "co2,3.36\r\n",
+      "c1,62.36\r\n",
+      "c2,8.9\r\n",
+      "c3,5.31\r\n",
+      "c4,3.01\r\n",
+      "c5,1.5\r\n",
+      "c6,1.05\r\n",
+      "c7,2.0\r\n",
+      "c7+,12.049\r\n"
+     ]
+    }
+   ],
    "source": [
     "%cat data/near_critical_oil.csv"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 47,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[['Component', 'Mol fraction'],\n",
+       " ['n2', '0.46'],\n",
+       " ['co2', '3.36'],\n",
+       " ['c1', '62.36'],\n",
+       " ['c2', '8.9'],\n",
+       " ['c3', '5.31'],\n",
+       " ['c4', '3.01'],\n",
+       " ['c5', '1.5'],\n",
+       " ['c6', '1.05'],\n",
+       " ['c7', '2.0'],\n",
+       " ['c7+', '12.049']]"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "import csv\n",
     "\n",
@@ -380,6 +714,17 @@
     "critical_oil"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "csv?"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -389,7 +734,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 50,
    "metadata": {
     "collapsed": true
    },
@@ -404,11 +749,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 51,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Nombre,Peso\r",
+      "\r\n",
+      "Juan,92\r",
+      "\r\n",
+      "\"La \"\"Mole\"\" Moli\",121\r",
+      "\r\n",
+      "Martín,5 kilos de más\r",
+      "\r\n"
+     ]
+    }
+   ],
    "source": [
     "%cat pesos.csv"
    ]
@@ -449,100 +809,299 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Números aleatorios\n",
-    "\n",
-    "Todas las funciones relacionadas a la aleatoriedad están en el módulo `random`. \n",
-    "\n",
-    "Ver [documentación](https://docs.python.org/3/library/random.html)"
+    "### Números aleatorios\n",
+    "\n",
+    "Todas las funciones relacionadas a la aleatoriedad están en el módulo `random`. \n",
+    "\n",
+    "Ver [documentación](https://docs.python.org/3/library/random.html)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.5155237329761995"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import random\n",
+    "\n",
+    "# la función más básica\n",
+    "random.random()                      # float aleatorio, 0.0 <= x < 1.0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "90"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "random.randrange(100, 10, -5)           # análogo a range() devuelve un numero aleatorio de la serie"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "10"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "random.choice([0.3, 10, 'A'])     # elige un elemento al azar de una secuencia no vacía"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 60,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[0.3, 10]"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "import random\n",
-    "\n",
-    "# la función más básica\n",
-    "random.random()                      # float aleatorio, 0.0 <= x < 1.0"
+    "l = [0.3, 10, 'A']\n",
+    "random.sample(l, k=2)      # elige k elementos de la poblacion dada "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 62,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[7, 4, 2, 3, 6, 8, 1, 9, 0, 5]"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "l = list(range(10))\n",
+    "random.shuffle(l)       # \"desordena\" una lista (inline)\n",
+    "l.pop"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
-    "random.randrange(10)           # análogo a range() devuelve un numero aleatorio de la serie"
+    "También tiene muchas funciones de probabilidad"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 64,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['BPF',\n",
+       " 'LOG4',\n",
+       " 'NV_MAGICCONST',\n",
+       " 'RECIP_BPF',\n",
+       " 'Random',\n",
+       " 'SG_MAGICCONST',\n",
+       " 'SystemRandom',\n",
+       " 'TWOPI',\n",
+       " '_BuiltinMethodType',\n",
+       " '_MethodType',\n",
+       " '_Sequence',\n",
+       " '_Set',\n",
+       " '__all__',\n",
+       " '__builtins__',\n",
+       " '__cached__',\n",
+       " '__doc__',\n",
+       " '__file__',\n",
+       " '__loader__',\n",
+       " '__name__',\n",
+       " '__package__',\n",
+       " '__spec__',\n",
+       " '_acos',\n",
+       " '_ceil',\n",
+       " '_cos',\n",
+       " '_e',\n",
+       " '_exp',\n",
+       " '_inst',\n",
+       " '_log',\n",
+       " '_pi',\n",
+       " '_random',\n",
+       " '_sha512',\n",
+       " '_sin',\n",
+       " '_sqrt',\n",
+       " '_test',\n",
+       " '_test_generator',\n",
+       " '_urandom',\n",
+       " '_warn',\n",
+       " 'betavariate',\n",
+       " 'choice',\n",
+       " 'expovariate',\n",
+       " 'gammavariate',\n",
+       " 'gauss',\n",
+       " 'getrandbits',\n",
+       " 'getstate',\n",
+       " 'lognormvariate',\n",
+       " 'normalvariate',\n",
+       " 'paretovariate',\n",
+       " 'randint',\n",
+       " 'random',\n",
+       " 'randrange',\n",
+       " 'sample',\n",
+       " 'seed',\n",
+       " 'setstate',\n",
+       " 'shuffle',\n",
+       " 'triangular',\n",
+       " 'uniform',\n",
+       " 'vonmisesvariate',\n",
+       " 'weibullvariate']"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "random.choice([0.3, 10, 'A'])     # elige un elemento al azar de una secuencia no vacía"
+    "dir(random)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 63,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['betavariate',\n",
+       " 'expovariate',\n",
+       " 'gammavariate',\n",
+       " 'lognormvariate',\n",
+       " 'normalvariate',\n",
+       " 'paretovariate',\n",
+       " 'vonmisesvariate',\n",
+       " 'weibullvariate']"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "random.sample(l, k=3)      # elige k elementos de la poblacion dada "
+    "[method for method in dir(random) if method.endswith('variate')]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 67,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
-    "l = list(range(10))\n",
-    "random.shuffle(l)       # \"desordena\" una lista (inline)\n",
-    "l "
+    "random.normalvariate??"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "También tiene muchas funciones de probabilidad"
+    "#### Ejercicio\n",
+    "\n",
+    "1. Crear un generador de 1000 números aleatorios pertecientes a una curva de probabilidad normal con media 1 y variancia 0.25. \n",
+    "\n",
+    "2. Verificar que la media y la variancia son cercanas a las esperadas (Tip: investigar las funciones del módulo `statistics`)\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 81,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
-    "[method for method in dir(random) if method.endswith('variate')]"
+    "normal = [random.normalvariate(1, 0.25) for n in range(1000)]\n",
+    "\n",
+    "import statistics as stats"
    ]
   },
   {
-   "cell_type": "markdown",
-   "metadata": {},
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.25535015504245945"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "#### Ejercicio\n",
-    "\n",
-    "1. Crear un generador de 1000 números aleatorios pertecientes a una curva de probabilidad normal con media 1 y variancia 0.25. \n",
-    "\n",
-    "2. Verificar que la media y la variancia son cercanas a las esperadas (Tip: investigar las funciones del módulo `statistics`)\n"
+    "stats.stdev(normal)"
    ]
   },
   {
@@ -556,11 +1115,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 84,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "b'\\x80\\x03]q\\x00(X\\x05\\x00\\x00\\x00puedeq\\x01X\\x03\\x00\\x00\\x00serq\\x02}q\\x03(X\\t\\x00\\x00\\x00cualquierq\\x04KdX\\x04\\x00\\x00\\x00casiq\\x05]q\\x06X\\x04\\x00\\x00\\x00cosaq\\x07X\\x01\\x00\\x00\\x00!q\\x08\\x85q\\tue.'"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "información = ['puede', 'ser', {'casi': [], 'cualquier': 100, 'cosa': ('!',)}]\n",
     "\n",
@@ -571,11 +1141,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 85,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['puede', 'ser', {'casi': [], 'cosa': ('!',), 'cualquier': 100}]"
+      ]
+     },
+     "execution_count": 85,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# en sentido contrario\n",
     "pickle.loads(_)"
@@ -583,7 +1164,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 86,
    "metadata": {
     "collapsed": false
    },
@@ -596,11 +1177,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 87,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['puede', 'ser', {'casi': [], 'cosa': ('!',), 'cualquier': 100}]"
+      ]
+     },
+     "execution_count": 87,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "pickle.load(open('datos.pkl', 'rb'))"
    ]
@@ -614,17 +1206,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 91,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "b'\\x80\\x03c__main__\\nA\\nq\\x00)\\x81q\\x01}q\\x02X\\x05\\x00\\x00\\x00valorq\\x03X\\x08\\x00\\x00\\x00un valorq\\x04sb.'"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "class A:\n",
     "    \"una clase que no hace absolutamente nada\"\n",
-    "    pass\n",
+    "    \n",
+    "    def __init__(self, valor):\n",
+    "        self.valor = valor\n",
+    "    \n",
     "\n",
-    "a = A()\n",
+    "a = A('un valor')\n",
     "\n",
     "a_serializado = pickle.dumps(a)\n",
     "a_serializado"
@@ -632,26 +1238,59 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 89,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "bytes"
+      ]
+     },
+     "execution_count": 89,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "type(a_serializado)    # la serializados es como datos binarios \"crudos\""
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 92,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
     "b= pickle.loads(_)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 95,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 95,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "a is b"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -679,11 +1318,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 96,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "AttributeError",
+     "evalue": "Can't get attribute 'A' on <module '__main__'>",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-96-3801b5552b00>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mdel\u001b[0m \u001b[0mA\u001b[0m    \u001b[1;31m# borramos la clase A del espacio de nombres global\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mpickle\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloads\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma_serializado\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;31mAttributeError\u001b[0m: Can't get attribute 'A' on <module '__main__'>"
+     ]
+    }
+   ],
    "source": [
     "del A    # borramos la clase A del espacio de nombres global\n",
     "pickle.loads(a_serializado)"
@@ -698,11 +1349,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 97,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'[\"puede\", \"ser\", {\"cualquier\": 100, \"casi\": [], \"cosa\": [\"!\"]}]'"
+      ]
+     },
+     "execution_count": 97,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "import json\n",
     "\n",
@@ -720,7 +1382,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 98,
    "metadata": {
     "collapsed": true
    },
@@ -739,14 +1401,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 100,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "IPython.utils.text.SList"
+      ]
+     },
+     "execution_count": 100,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "mole = !cat pesos.csv | grep \"Mole\"    \n",
-    "mole"
+    "type(mole)"
    ]
   },
   {
@@ -760,11 +1433,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 101,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 101,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "import subprocess\n",
     "\n",
@@ -773,11 +1457,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 102,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "b'hola python, soy echo\\n'"
+      ]
+     },
+     "execution_count": 102,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "subprocess.check_output(['echo', 'hola python, soy echo'])    # se ejecuta en el \"kernel\" (ver consola)"
    ]
@@ -799,7 +1494,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 104,
    "metadata": {
     "collapsed": true
    },
@@ -812,28 +1507,74 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "OrderedDict es... un diccionario que sí queda ordenado"
+    "OrderedDict es... un diccionario que sí queda ordenado"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 110,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Dictionary that remembers insertion order'"
+      ]
+     },
+     "execution_count": 110,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "OrderedDict.__doc__    # para http://twitter.com/Obvio"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 114,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'a': 12, 'b': 10}"
+      ]
+     },
+     "execution_count": 114,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "OrderedDict.__doc__    # para http://twitter.com/Obvio"
+    "d = dict()\n",
+    "d['a'] = 12\n",
+    "d['b'] = 10\n",
+    "d"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 115,
    "metadata": {
     "collapsed": false,
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "('item_1', 1)\n",
+      "('item_2', '1 millon')\n",
+      "('item_3', None)\n"
+     ]
+    }
+   ],
    "source": [
     "d = OrderedDict()\n",
     "d['item_1'] = 1\n",
@@ -852,11 +1593,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 105,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Counter({'a': 5, 'b': 2, 'c': 1, 'd': 1, 'r': 2})"
+      ]
+     },
+     "execution_count": 105,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "contador = Counter('abracadabra')\n",
     "contador"
@@ -864,13 +1616,46 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 108,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[('a', 5), ('b', 2)]"
+      ]
+     },
+     "execution_count": 108,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "contador.most_common(2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Counter({1: 3, 2: 2, 'hola': 1})"
+      ]
+     },
+     "execution_count": 109,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "contador.most_common(3)"
+    "Counter([1, 2, 'hola', 1, 1, 2])"
    ]
   },
   {
@@ -882,11 +1667,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 118,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Raices(x1=-0.6180339887498949, x2=1.618033988749895)"
+      ]
+     },
+     "execution_count": 118,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "\n",
     "Raices = namedtuple('Raices', ['x1', 'x2'])\n",
@@ -915,13 +1711,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 120,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.618033988749895"
+      ]
+     },
+     "execution_count": 120,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "soluciones[0], soluciones[1]"
+    "soluciones[1]"
    ]
   },
   {
@@ -933,22 +1740,44 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 121,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-0.6180339887498949"
+      ]
+     },
+     "execution_count": 121,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "soluciones.x1"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 122,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.618033988749895"
+      ]
+     },
+     "execution_count": 122,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "soluciones.x2"
    ]
@@ -962,11 +1791,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 123,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "AttributeError",
+     "evalue": "can't set attribute",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-123-464369c72c17>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msoluciones\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mx1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m10\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;31mAttributeError\u001b[0m: can't set attribute"
+     ]
+    }
+   ],
    "source": [
     "soluciones.x1 = 10"
    ]
@@ -986,7 +1827,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 125,
    "metadata": {
     "collapsed": true
    },
@@ -997,7 +1838,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 126,
    "metadata": {
     "collapsed": false
    },
@@ -1010,11 +1851,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 127,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Hola curso!\n",
+      "\n",
+      "\n",
+      "Los quiero mucho :D\n"
+     ]
+    }
+   ],
    "source": [
     "print(contenido)"
    ]
@@ -1030,7 +1882,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 134,
    "metadata": {
     "collapsed": false
    },
@@ -1039,6 +1891,97 @@
     "simbolos = set(\"#$%&\\'()*+,-./:;<=>?@[\\]^_`{|}~\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 135,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "url = 'http://www.lavoz.com.ar'\n",
+    "with urlopen(url) as response:\n",
+    "    contenido = response.read().decode('utf8')     # el decode es para \"decodificar\" bytes crudos como texto unicode"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 139,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'#', 'a'}"
+      ]
+     },
+     "execution_count": 139,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "set('#hola') & set('#dfdfdfa')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 141,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[('comun', 44),\n",
+       " ('clearfix\"', 40),\n",
+       " ('sinimagen', 23),\n",
+       " ('destacada', 19),\n",
+       " ('página', 14),\n",
+       " ('formato', 14),\n",
+       " ('segmentación', 14),\n",
+       " ('clearfix', 14),\n",
+       " ('sobre', 10),\n",
+       " ('galeria', 10)]"
+      ]
+     },
+     "execution_count": 141,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "palabras = [palabra.lower() for palabra in contenido.split() if len(palabra) > 4 and not set(palabra) & simbolos]\n",
+    "\n",
+    "Counter(palabras).most_common(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 142,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "ename": "ImportError",
+     "evalue": "No module named 'pyquery'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mImportError\u001b[0m                               Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-142-ec75c589f7ac>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mpyquery\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mPyQuery\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;31mImportError\u001b[0m: No module named 'pyquery'"
+     ]
+    }
+   ],
+   "source": [
+    "from pyquery import PyQuery"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -1053,7 +1996,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 145,
    "metadata": {
     "collapsed": false
    },
@@ -1069,14 +2012,14 @@
    "source": [
     "%%writefile ejemplo_script.py\n",
     "\n",
-    "saludo = \"Hola Mundo\"\n",
+    "saludo = \"Hola Terremoto!\"\n",
     "\n",
     "print(saludo)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 146,
    "metadata": {
     "collapsed": false
    },
@@ -1085,7 +2028,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Hola Mundo\r\n"
+      "Hola Terremoto!\r\n"
      ]
     }
    ],
@@ -1102,7 +2045,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 147,
    "metadata": {
     "collapsed": false
    },
@@ -1111,14 +2054,31 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Hola Mundo\n",
-      "Hola Mundo\n"
+      "Hola Terremoto!\n"
      ]
     }
    ],
    "source": [
-    "from ejemplo_script import saludo\n",
-    "print(saludo)"
+    "from ejemplo_script import saludoº"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 148,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Hola Terremoto!\n"
+     ]
+    }
+   ],
+   "source": [
+    "sak"
    ]
   },
   {
@@ -1132,7 +2092,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 149,
    "metadata": {
     "collapsed": false
    },
@@ -1141,7 +2101,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Writing ejemplo_script2.py\n"
+      "Overwriting ejemplo_script2.py\n"
      ]
     }
    ],
@@ -1158,25 +2118,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 150,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "'Hola'"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Hola Mundo\r\n"
+     ]
     }
    ],
    "source": [
-    "from ejemplo_script2 import saludo\n",
-    "saludo[:4]"
+    "!python ejemplo_script2.py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 151,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from ejemplo_script2 import saludo"
    ]
   },
   {
@@ -1212,7 +2179,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 166,
    "metadata": {
     "collapsed": false
    },
@@ -1221,7 +2188,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Writing ejemplo_argv.py\n"
+      "Overwriting ejemplo_argv.py\n"
      ]
     }
    ],
@@ -1230,12 +2197,14 @@
     "\n",
     "if __name__ == '__main__':\n",
     "    import sys\n",
-    "    print(sys.argv)"
+    "    print(sys.argv)\n",
+    "    print(sys.argv[2] * int(sys.argv[1]))\n",
+    "    "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 170,
    "metadata": {
     "collapsed": false
    },
@@ -1244,12 +2213,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "['ejemplo_argv.py', 'parametro', '10', '--allthenight', '--shampein']\r\n"
+      "['ejemplo_argv.py', '80', '_']\r\n",
+      "________________________________________________________________________________\r\n"
      ]
     }
    ],
    "source": [
-    "!python ejemplo_argv.py --allthenight --shampein"
+    "!python ejemplo_argv.py 80 _"
    ]
   },
   {
@@ -1270,7 +2240,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 171,
    "metadata": {
     "collapsed": false
    },
@@ -1303,7 +2273,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 176,
    "metadata": {
     "collapsed": false
    },
@@ -1312,18 +2282,17 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "usage: prog.py [-h] [--sum] N [N ...]\r\n",
-      "prog.py: error: the following arguments are required: N\r\n"
+      "72\r\n"
      ]
     }
    ],
    "source": [
-    "!python3 prog.py"
+    "!python3 prog.py --sum 10 4 56 2 "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 177,
    "metadata": {
     "collapsed": false
    },
@@ -1351,7 +2320,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 178,
    "metadata": {
     "collapsed": false
    },
@@ -1366,7 +2335,7 @@
     }
    ],
    "source": [
-    "!python3 prog.py  10 2 --sum 45 "
+    "!python3 prog.py  10 2 --sum"
    ]
   },
   {