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tap1012
tap1012
Commit 00646378 authored by Aldo Eduardo Niebla Cruz's avatar Aldo Eduardo Niebla Cruz
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Ejercicios

parent c54ef283
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Showing with 37 additions and 29 deletions
06-MatPlotLib&Statistics.ipynb
View file @ 00646378
......@@ -36,7 +36,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
......@@ -59,13 +59,13 @@
},
{
"cell_type": "code",
"execution_count": 95,
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 1080x720 with 0 Axes>"
"<Figure size 432x288 with 0 Axes>"
]
},
"metadata": {},
......@@ -73,9 +73,9 @@
},
{
"data": {
"image/png": 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\n",
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAD8CAYAAAB0IB+mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAADl5JREFUeJzt3GGo3Xd9x/H3x2adzFUd9gqSRFtZOs3cwO7SOYTZoRtpB8kDhyRQto5i0FkZKIMOh5P6yMkcCNlcxqQqaI0+GBeMFOZaCsVob2mtJqVyjW5NlTVq5xPRWvbdg3O6HW+T3v96/+ecJN/3CwLnf84v5/s7uZ/7yTn3f85NVSFJuvS9YNkbkCQthoUvSU1Y+JLUhIUvSU1Y+JLUhIUvSU1sWfhJPp7kiSTfOM/tSfLRJBtJHk5y7fjblMZnttXNkGf4dwD7nuP2G4A90z+HgX/Y/rakhbgDs61Gtiz8qroX+OFzLDkAfLImTgAvTfKKsTYozYvZVjc7RriPncBjM8dnptd9b/PCJIeZPFPiRS960W+95jWvGWG89GwPPPDA96tqZZt3Y7Z1wdlOtsco/MGq6ihwFGB1dbXW19cXOV6NJPn3Rc4z21qU7WR7jHfpPA7snjneNb1OutiZbV1Sxij8NeCPp+9oeAPwo6p61kte6SJktnVJ2fJHOkk+A1wPXJnkDPDXwC8AVNXHgOPAjcAG8GPgT+e1WWlMZlvdbFn4VXVoi9sLeNdoO5IWxGyrGz9pK0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNWPiS1ISFL0lNDCr8JPuSPJpkI8lt57j9lUnuTvJgkoeT3Dj+VqXxmW11smXhJ7kMOALcAOwFDiXZu2nZXwHHqur1wEHg78feqDQ2s61uhjzDvw7YqKrTVfUUcCdwYNOaAl48vfwS4LvjbVGaG7OtVoYU/k7gsZnjM9PrZn0AuCnJGeA48O5z3VGSw0nWk6yfPXv2eWxXGpXZVitjnbQ9BNxRVbuAG4FPJXnWfVfV0apararVlZWVkUZLc2W2dckYUviPA7tnjndNr5t1C3AMoKq+DLwQuHKMDUpzZLbVypDCvx/Yk+TqJJczOXG1tmnNfwBvBkjyWibfFL6u1YXObKuVLQu/qp4GbgXuAh5h8o6Fk0luT7J/uuy9wNuTfA34DHBzVdW8Ni2NwWyrmx1DFlXVcSYnrGave//M5VPAG8fdmjR/Zlud+ElbSWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJix8SWrCwpekJgYVfpJ9SR5NspHktvOseVuSU0lOJvn0uNuUxmeu1c2OrRYkuQw4Avw+cAa4P8laVZ2aWbMH+EvgjVX1ZJKXz2vD0hjMtToa8gz/OmCjqk5X1VPAncCBTWveDhypqicBquqJcbcpjc5cq50hhb8TeGzm+Mz0ulnXANckuS/JiST7znVHSQ4nWU+yfvbs2ee3Y2kco+UazLYuDmOdtN0B7AGuBw4B/5TkpZsXVdXRqlqtqtWVlZWRRktzMyjXYLZ1cRhS+I8Du2eOd02vm3UGWKuqn1XVt4FvMvlGkS5U5lrtDCn8+4E9Sa5OcjlwEFjbtOZfmDwLIsmVTF4Knx5xn9LYzLXa2bLwq+pp4FbgLuAR4FhVnUxye5L902V3AT9Icgq4G/iLqvrBvDYtbZe5VkepqqUMXl1drfX19aXM1qUvyQNVtbqM2WZb87SdbPtJW0lqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqwsKXpCYsfElqYlDhJ9mX5NEkG0lue451b01SSVbH26I0P2ZbnWxZ+EkuA44ANwB7gUNJ9p5j3RXAnwNfGXuT0jyYbXUz5Bn+dcBGVZ2uqqeAO4ED51j3QeBDwE9G3J80T2ZbrQwp/J3AYzPHZ6bX/a8k1wK7q+oLz3VHSQ4nWU+yfvbs2f/3ZqWRmW21su2TtkleAHwEeO9Wa6vqaFWtVtXqysrKdkdLc2W2dakZUviPA7tnjndNr3vGFcDrgHuSfAd4A7DmyS1dBMy2WhlS+PcDe5JcneRy4CCw9syNVfWjqrqyqq6qqquAE8D+qlqfy46l8ZhttbJl4VfV08CtwF3AI8CxqjqZ5PYk++e9QWlezLa62TFkUVUdB45vuu7951l7/fa3JS2G2VYnftJWkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpCQtfkpqw8CWpiUGFn2RfkkeTbCS57Ry3vyfJqSQPJ/lSkleNv1VpXOZa3WxZ+EkuA44ANwB7gUNJ9m5a9iCwWlW/CXwe+JuxNyqNyVyroyHP8K8DNqrqdFU9BdwJHJhdUFV3V9WPp4cngF3jblManblWO0MKfyfw2Mzxmel153ML8MVz3ZDkcJL1JOtnz54dvktpfKPlGsy2Lg6jnrRNchOwCnz4XLdX1dGqWq2q1ZWVlTFHS3OzVa7BbOvisGPAmseB3TPHu6bX/ZwkbwHeB7ypqn46zvakuTHXamfIM/z7gT1Jrk5yOXAQWJtdkOT1wD8C+6vqifG3KY3OXKudLQu/qp4GbgXuAh4BjlXVySS3J9k/XfZh4JeBzyV5KMnaee5OuiCYa3U05Ec6VNVx4Pim694/c/ktI+9LmjtzrW78pK0kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNWHhS1ITFr4kNTGo8JPsS/Joko0kt53j9l9M8tnp7V9JctXYG5XmwWyrky0LP8llwBHgBmAvcCjJ3k3LbgGerKpfBf4O+NDYG5XGZrbVzZBn+NcBG1V1uqqeAu4EDmxacwD4xPTy54E3J8l425TmwmyrlR0D1uwEHps5PgP89vnWVNXTSX4EvAz4/uyiJIeBw9PDnyb5xvPZ9AiuZNPenHvJzf61AWsutWx3/Dp3mwvDsn1OQwp/NFV1FDgKkGS9qlYXOf8Zy5rdbe4yZydZX+S8CyHbXb/OneY+M/v5/t0hP9J5HNg9c7xret051yTZAbwE+MHz3ZS0IGZbrQwp/PuBPUmuTnI5cBBY27RmDfiT6eU/Av6tqmq8bUpzYbbVypY/0pn+3PJW4C7gMuDjVXUyye3AelWtAf8MfCrJBvBDJt84Wzm6jX1v17Jmd5u7zNlbzr0Es+3X+dKfu63Z8cmKJPXgJ20lqQkLX5KamHvhL+uj6wPmvifJqSQPJ/lSkleNMXfI7Jl1b01SSUZ5e9eQuUneNn3cJ5N8eoy5Q2YneWWSu5M8OP03v3GEmR9P8sT53vOeiY9O9/Rwkmu3O3Pmvpf2KxmWle1l5Xro7Hlkexm5nt7vfLJdVXP7w+RE2LeAVwOXA18D9m5a82fAx6aXDwKfXdDc3wN+aXr5nWPMHTp7uu4K4F7gBLC6oMe8B3gQ+JXp8csX+HU+Crxzenkv8J0R5v4ucC3wjfPcfiPwRSDAG4CvXMy5Xma2l5XrZWZ7WbmeZ7bn/Qx/WR9d33JuVd1dVT+eHp5g8h7sMQx5zAAfZPJ7WX6ywLlvB45U1ZMAVfXEAmcX8OLp5ZcA393u0Kq6l8k7Z87nAPDJmjgBvDTJK7Y7l+X+SoZlZXtZuR46ex7ZXkquYX7Znnfhn+uj6zvPt6aqngae+ej6vOfOuoXJ/5Zj2HL29OXX7qr6wkgzB80FrgGuSXJfkhNJ9i1w9geAm5KcAY4D7x5p9nb3Na/7nUeuh86eNVa2l5XrQbOZT7Yv1FzD88z2Qn+1woUoyU3AKvCmBc17AfAR4OZFzNtkB5OXvtczedZ3b5LfqKr/WsDsQ8AdVfW3SX6HyXvbX1dV/72A2S0tMttLzjUsL9sXVa7n/Qx/WR9dHzKXJG8B3gfsr6qfbnPm0NlXAK8D7knyHSY/f1sb4QTXkMd8Blirqp9V1beBbzL5JtmuIbNvAY4BVNWXgRcy+QVU8zQoB3O633n9SoZlZXtZuR4yG+aT7Qs110P39mxjnGB4jhMPO4DTwNX830mPX9+05l38/MmtYwua+3omJ2T2LPoxb1p/D+OctB3ymPcBn5hevpLJS8KXLWj2F4Gbp5dfy+RnnRlh9lWc/8TWH/LzJ7a+ejHnepnZXlaul5ntZeZ6XtkeJQxbbPpGJv/bfgt43/S625k884DJ/4ifAzaArwKvXtDcfwX+E3ho+mdtUY9509oxvzG2esxh8rL7FPB14OACv857gfum3zQPAX8wwszPAN8DfsbkGd4twDuAd8w83iPTPX19rH/nZeZ6mdleVq6Xme1l5Hqe2fZXK0hSE37SVpKasPAlqQkLX5KasPAlqQkLX5KasPAlqQkLX5Ka+B85Vopyh8eoGAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 1080x720 with 2 Axes>"
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
......@@ -358,16 +358,20 @@
},
{
"cell_type": "code",
"execution_count": 48,
"execution_count": 3,
"metadata": {},
"outputs": [
{
"ename": "SyntaxError",
"evalue": "invalid syntax (<ipython-input-48-4c9e5b44a732>, line 13)",
"output_type": "error",
"traceback": [
"\u001b[0;36m File \u001b[0;32m\"<ipython-input-48-4c9e5b44a732>\"\u001b[0;36m, line \u001b[0;32m13\u001b[0m\n\u001b[0;31m plt.text(60, .025, r'$\\mu='mu,'\\ \\sigma=15$')\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
"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": [
......@@ -383,7 +387,7 @@
"plt.ylabel('Probability')\n",
"plt.title('Histogram of IQ')\n",
"# se puede usar latex\n",
"plt.text(60, .025, r'$\\mu='mu,'\\ \\sigma=15$')\n",
"plt.text(60, .025, r'$\\mu=100\\ \\sigma=15$')\n",
"plt.axis([40, 160, 0, 0.03])\n",
"\n",
"plt.show()"
......@@ -748,7 +752,7 @@
},
{
"cell_type": "code",
"execution_count": 79,
"execution_count": 4,
"metadata": {},
"outputs": [
{
......@@ -758,7 +762,6 @@
"longitud texto español: 8305 \tlongitud texto francés: 8343\n",
"\n",
"distribución español = [('a', 880), ('b', 98), ('c', 311), ('d', 387), ('e', 882), ('f', 84), ('g', 67), ('h', 49), ('i', 424), ('j', 23), ('k', 2), ('l', 428), ('m', 176), ('n', 506), ('o', 533), ('p', 174), ('q', 43), ('r', 463), ('s', 442), ('t', 276), ('u', 225), ('v', 61), ('w', 12), ('x', 11), ('y', 57), ('z', 33)]\n",
"\n",
"distribución frances = [('a', 522), ('b', 93), ('c', 203), ('d', 331), ('e', 1035), ('f', 85), ('g', 62), ('h', 61), ('i', 430), ('j', 26), ('k', 4), ('l', 411), ('m', 180), ('n', 513), ('o', 358), ('p', 200), ('q', 70), ('r', 491), ('s', 454), ('t', 440), ('u', 344), ('v', 76), ('w', 7), ('x', 26), ('y', 9), ('z', 5)]\n"
]
}
......@@ -864,7 +867,7 @@
" \n",
"print('longitud texto español:', len(docs[0]), '\\tlongitud texto francés:', len(docs[1]))\n",
"print('\\ndistribución español =', ndist_esp)\n",
"print('\\ndistribución frances =', ndist_fr)"
"print('distribución frances =', ndist_fr)"
]
},
{
......@@ -912,14 +915,14 @@
},
{
"cell_type": "code",
"execution_count": 94,
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
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IIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjub1LgCgl9tvvz0rVqzoXcY6t9122+UBD7h3119uvvnmrFy58n6uaP208cYbZ5tttuldBjCBBHJgYu255575wQ9+kHnz5u63wp///OfZc88989GPfjRbbbXVjLdrreVVr3pV3ve+9+VBD3rQOqxw/XHLLbfkuuuuy0477dS7FGDCzN3/hQDW4o477siyZcsyf/783qWsM3feeWeOO+647L333jn77LOzyy67zGi7JUuW5LzzzssNN9yQhzzkIeu4yvXDwoUL87Of/ax3GcAEMoccYA6bN29e3vWud+XlL3959tlnn5x//vlr3eYtb3lLPvaxj+Xcc8+dmDAO0JNADjAB/uzP/iwf/vCHc+ihh+b973//tP1OPPHEvPe97815552XbbfddhYrBJhcAjnAhDjggANy4YUX5q1vfWuOPfbY37hZ8+STT87f/M3f5HOf+1x22GGHTlUCTB6BHGCCLFy4MJdeemmuuuqqPOMZz8iPf/zjJMnpp5+eN7zhDTn33HOzYMGCvkUCTBiBHGDCbL311vnMZz6T+fPnZ++998673/3uvOIVr8hnP/vZLFy4sHd5ABNHIAeYQBtvvHHe/e5356UvfWne+MY35tOf/nR222233mUBTCSBfIJUVe8SgPVIVeWYY47J9176szzucY/rXQ6wHpAV+hDIAQCgo/UmkFfV46vqjKo6uaoO710PAADMhvXmL3W21r6U5Nm96wAAgNm01ivkVbWyqq4YW14ztD+9qv6tqq6sqq9W1VFD+9Kq+vbQ9+qqOmTK/q6oqtOntJ0ybLPJ8H6bqrphbP3vVdW/VNU1VXVtVb2hhklOVXVEVZ14n0cCAAA6mMkV8jtaa48Zb6iqjZO8N8njW2vfGoL0grEu72itva2qdk1yYVVt21q7a3i/UZInVdWDWms/GdtmZZIjk5w05VibJvlUkpe21v65qjZL8o9Jjk7yf+/RpwUAgPXMvZ1DvkVGYf4HSdJa+3lr7ZqpnVprX0tyZ5JthqbDkpya5J+TLJ7S/fgkx1bV1B8SnpvkotbaPw/7/GmSY5K85l7W3s3SpUuzdOnSe73t+L/TrQcAmC3rQ/6YSQ3rQ51r1Fpb45LRlesrxpZDh/b3J7k5yWlJDk/ygKF9aZJXDa9/P8l3ktTw/pokOyV5apKzx45xSpJnJjk5yQszCvA3DOvenuTlq6nr1iQPTnJEkhNn8DlekmRZkmU77bRTm21LlixpSe5elixZcq+3nbr9+Po17XfqPiwWy2iZeEse3LuC9cIjH/nI7ueixbI+LDM10/yxLs2khp51JlnW1pJRW2t3B+VpVdWK1trm06zbPcmBSZ6f5MrW2hFVtTTJi5PckuT2JK9rrV1YVYuSvLO19sSq2ijJjUn+a2vth1V1SpJzklyZ5JNJ9kvypdbagqp6e5IbW2vvnHLsW5PMT/InSRa11o5Z4wcZs2jRorZs2bKZdr/frHq259rGfLptW2t3/zvd+pnsAxiZP39+Pv/5z2f+/Pm9S+lr6ZbJ0tt6V9HdwoULc8455/hrpUy0e5oV1odssT5noKq6rLW2aG397tNTVlprVyW5qqpOTXJ9Rlerk2EO+ZTuhyX53bGbNR+c5H8ked/Y/q6tqivy609b+WqSJ4/vqKoenmRFa+3HG9ID7JcsWXKft51uH/dl3wAA98b6kD9mUsP6UOea3Ksr5FW1eUZXpc8f3h+Y5PjW2m7DFfIV44G8qh6Q0RXx32+tfWdoe0qSN7TW9l91hby19vGq+r0kn06S4Qr5pkm+kuQlrbXzhvcfS/LZ1toJVXVENpAr5L2tDz/FwvrEFfKBK+RJXCGHRFa4v830CvlMburcdMpjD/86SSV59fAYwiuSvDG/ujq+Ok9K8u1VYXzw+SSPrqqHjXdsrX0lyeVj7+/I6AbQ11fVNUmuSvLlJOOPOjyiqr41tuw4g88FAADdrXXKSmtto2lWHTxN/6WrabsgyV5T2lYmeejw9ogp6/5kyvurMppXvrrjnZLRTaEAALDBubePPQRgDrjmmtETa1esWNG5EoDJJZADTKjzzjsvT37y6J75xYsX54477uhcEcBkEsgniJs0gFVOOumk/Omf/mnOOOOMrHzDD/PQhz40z3zmM/OLX/yid2lAR7JCHwI5wAS5884787KXvSwnnHBCLrroouy7777ZaKONcsopp+SBD3xgnvvc5+bOO+/sXSbARBHIASbEj370ozztaU/Ltddemy9+8Yt5xCMecfe6jTfeOKeffnpWrFiRI488MnfddVfHSgEmi0AOMAGWL1+evffeO7vuumvOOeecbLnllr/RZ5NNNsknPvGJ3HjjjTn66KP96hpglgjkAHPc+eefn3322SeveMUrcvzxx2fevOmfeLvZZpvlnHPOyRVXXJFXvvKVQjnALFjrc8gB5qpvfvObOfbYY+f0X+r86U9/mrPOOiunnXZa9t9//xlts8UWW+Qzn/lM9t9//zz72c/OjjtOxt9au/nmm3uXAEwogRyYWHvttVf22GOPPPjBD+5dyjp18cUX/9p88ZnYeuutc+655+YjH/lIVq5cuY4qW7+8+c1vzs4779y7DGAC1ST+OnLRokVt2bJlvcsAAGAOq6rLWmuL1tbPHHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOhIIAcAgI4EcgAA6EggBwCAjgRyAADoSCAHAICOBHIAAOioWmu9a5h1VXV7kmt617GB2CbJ93sXsQExXjNnrGbOWM2csZo5YzVzxmrmjNWvm99a++21dZo3G5Wsh65prS3qXcSGoKqWGauZM14zZ6xmzljNnLGaOWM1c8Zq5ozVvWPKCgAAdCSQAwBAR5MayN/bu4ANiLG6Z4zXzBmrmTNWM2esZs5YzZyxmjljdS9M5E2dAACwvpjUK+QAALBeEMgBAKCjiQjkVfWyqvp6VX2lqt461v7aqlpeVddU1R+OtR80tC2vqtf0qbqfqnplVbWq2mZ4X1X1rmE8/r2qHjvW9wVVde2wvKBf1bOrqv5mOKf+varOrKqtxtY5r9bAOPy6qvqdqvrXqvrq8D3q5UP7Q6rq3OFr69yq2npon/brcVJU1UZV9W9Vdc7wfuequnQYk49W1QOH9k2G98uH9Qt61j3bqmqrqvr48L3qa1W1t/NqelV17PA1eHVVnVZVv+XcGqmqk6vq5qq6eqztHp9Lk5oZZqS1NqeXJE9Jcl6STYb32w7/PjrJlUk2SbJzkm8k2WhYvpHk4UkeOPR5dO/PMYvj9TtJPpvkxiTbDG0HJ/lMkkqyV5JLh/aHJLlu+Hfr4fXWvT/DLI3TU5PMG16/JclbnFczGjfj8Jtj8rAkjx1eb5HkP4bz6K1JXjO0v2bsHFvt1+MkLUmOS/KRJOcM789I8pzh9XuSvHR4fXSS9wyvn5Pko71rn+Vx+vsk/3N4/cAkWzmvph2rHZJcn2TTsXPqCOfW3ePz5CSPTXL1WNs9OpcmOTPMZJmEK+QvTfLXrbWfJ0lr7eahfXGS01trP2+tXZ9keZLHD8vy1tp1rbVfJDl96Dsp3pHk1UnG7/ZdnOQf2sglSbaqqocl+cMk57bWfthauzXJuUkOmvWKO2it/XNr7c7h7SVJdhxeO6/WzDhM0Vq7qbV2+fD69iRfyygcLM4oUGX4978Pr6f7epwIVbVjkqclef/wvpLsn+TjQ5epY7VqDD+e5ICh/5xXVVtmFKI+kCSttV+01n4U59WazEuyaVXNS7JZkpvi3EqStNY+n+SHU5rv6bk0sZlhJiYhkC9M8qThV0oXVNWeQ/sOSf5zrN+3hrbp2ue8qlqc5NuttSunrDJWa3ZkRlcDEmO1NsZhDYZfe/+3JJcm2a61dtOw6rtJthteT/oYHp/RRYO7hvf/JcmPxn5AHh+Pu8dqWH/b0H8S7JzkliQfHKb3vL+qHhTn1Wq11r6d5G1JvplREL8tyWVxbq3JPT2XJvocW5t5vQu4P1TVeUkeuppVf5HRZ3xIRr822TPJGVX18Fksb72ylrF6XUZTMciax6q19smhz18kuTPJh2ezNuaeqto8yT8meUVr7cfjF9taa62qJv4ZtVX19CQ3t9Yuq6r9eteznpuX0RSDl7XWLq2qd2Y0reBuzqtfGeY/L87oB5kfJflYXL2dMefSfTcnAnlr7cDp1lXVS5N8orXWknypqu5Ksk2Sb2c0X3qVHYe2rKF9gzfdWFXV7hl9I7pyCAI7Jrm8qh6f6cfq20n2m9J+/v1edCdrOq+SpKqOSPL0JAcM51cyoefVPbCm8ZlYVbVxRmH8w621TwzN36uqh7XWbhp+3btqut0kj+ETkxxSVQcn+a0kD07yzox+JT5vuFI5Ph6rxupbwzSELZP8YPbL7uJbSb7VWrt0eP/xjAK582r1DkxyfWvtliSpqk9kdL45t6Z3T8+lOZ0Z7qtJmLJyVkY3dqaqFmZ0Y8v3k3wqyXOGO6V3TvLIJF9K8uUkjxzurH5gRjdrfKpL5bOotXZVa23b1tqC1tqCjL6ZP7a19t2MPv/zhzun90py2/Brqs8meWpVbT1cXXjq0DbnVdVBGf3a/JDW2k/HVjmv1sw4TDFh2lK0AAAEA0lEQVTMO/1Akq+11t4+tupTSVY9heAFST451r66r8c5r7X22tbajsP3qOck+ZfW2uFJ/jXJM4duU8dq1Rg+c+g/EVfxhu/d/1lVjxqaDkjy1TivpvPNJHtV1WbD1+Sq8XJuTe+enksTmxlmpMedpLO5ZBTAP5Tk6iSXJ9l/bN1fZPTEh2uS/NFY+8EZPengGxlNT+j+OTqM2w351VNWKsn/HcbjqiSLxvodmdGNi8uTvLB33bM4Psszmgt3xbC8x3k147EzDr8+HvtkdBP1v4+dTwdnNB/1c0muzehJUQ8Z+k/79ThJS0ZX2lY9ZeXhGf3guzyjqQarnqr1W8P75cP6h/eue5bH6DFJlg3n1lkZPdnCeTX9eL0xydeHvHBqRk/Lcm6NPu9pGc2t/2VGF+xedG/OpUnNDDNZahggAACgg0mYsgIAAOstgRwAADoSyAEAoCOBHAAAOhLIAQCgI4EcYANSVSur6oqxZUFV7VdVtw3vv15Vbxvrf0RV3TJlm0cP6xZW1T9V1bVVdXlVnVFV2w3bnDjluOdX1aLh9Q1VddXY/t41tJ9SVd+uqk2G99tU1Q1j+5juePtV1TlTjndWVV2yzgYSYD0yJ/5SJ8AEuaO19pjxhqpakOTC1trTq2rTJP9WVWe21i4auny0tXbMlG1+K8mnkxzXWjt7aNsvyW/PsI6ntNa+v5r2lRk9a/ike3u8qtoqyeOSrKiqh7fWrpthTQAbJFfIAeaQ1todGf1xoR3W0vW5Sb64KhwP257fWrv6PpZwfJJjhz8nfm+P9ydJzk5yekZ/kRNgThPIATYsm45NFTlz6srhT1I/Msnnx5oPnTJlZdMkuyW57D7U8a9j+zt2rP2bSb6Q5HlT+t+T4x2W0V8GPG14DTCnmbICsGH5jSkrgydV1ZUZhfHjW2vfHVu3uikrazrGdH/Cebx9uikrSfJXST6Z0RSVe6SqtsvoM3yhtdaq6pdVtdv9cOUeYL3lCjnA3HBha22PJL+X5EVVtbrQPu4rGc3TXp0fJNl6SttDkkwXwH9Na+3ajKbNPHuGxxv37OHY1w83hC6Iq+TAHCeQA8whrbXrk/x1kv+9lq4fSfKEqnraqoaqenJV7Zbky0meWFUPHdoXJdkkyX/eg1LenORVMzzeuMOSHNRaW9BaW5BRiDePHJjTBHKAuec9SZ48PH0l+c055E8Ybv58epKXDY8h/GqSo5Pc0lr7XpKXJ/mnqroioxs1D2ut3TV2jPE55P8wtYDW2leSXD72ftrjreoz1Ds/ySVj212f5Laq+v37OCYA661qbbqpggAAwLrmCjkAAHQkkAMAQEcCOQAAdCSQAwBARwI5AAB0JJADAEBHAjkAAHT0/wCfzXu4m8KT3gAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 936x576 with 1 Axes>"
"<Figure size 864x504 with 1 Axes>"
]
},
"metadata": {
......@@ -943,7 +946,7 @@
" data_esp = np.random.normal(mean_esp, std_esp, 1000)\n",
" data_fran = np.random.normal(mean_fran, std_fran, 1000)\n",
" treatments = [data_esp, data_fran]\n",
" plt.rcParams['figure.figsize']=[13, 8]\n",
" plt.rcParams['figure.figsize']=[12, 7]\n",
" pos = np.array(range(len(treatments))) + 1\n",
" bp = plt.boxplot(treatments, vert=False, sym='k+', positions=pos, notch=1, bootstrap=5000)\n",
" plt.xlabel('FRECUENCIA')\n",
......@@ -1217,7 +1220,7 @@
},
{
"cell_type": "code",
"execution_count": 95,
"execution_count": 7,
"metadata": {},
"outputs": [
{
......@@ -1232,13 +1235,6 @@
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n"
]
},
{
"data": {
"image/png": 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\n",
......@@ -1273,8 +1269,8 @@
"plt.xticks(roulette_bet)\n",
"for i,j in zip(roulette_bet, np.array(roulette_prob)*100):\n",
" plt.annotate(str(round(j,2))+'%', xy=(i,j+0.5) )\n",
"\n",
"plt.show()\n",
"print()\n",
"plt.subplot(1, 2, 1)\n",
"plt.plot(roulette_num, custom_rand_var.pmf(roulette_num), 'go', ms=7, mec='g')\n",
"plt.vlines(roulette_num, 0, custom_rand_var.pmf(roulette_num), colors='g', lw=4)\n",
......@@ -1390,6 +1386,18 @@
"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": "3.5.3"
}
},
"nbformat": 4,
......
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