Ejercicios MatPlotlib

parent e589fbdb
...@@ -752,31 +752,9 @@ ...@@ -752,31 +752,9 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 7,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [],
{
"name": "stdout",
"output_type": "stream",
"text": [
"distribución español= [('a', 855), ('b', 90), ('c', 283), ('d', 373), ('e', 846), ('f', 72), ('g', 59), ('h', 44), ('i', 416), ('j', 22), ('l', 414), ('m', 159), ('n', 498), ('o', 521), ('p', 167), ('q', 42), ('r', 461), ('s', 421), ('t', 273), ('u', 221), ('v', 59), ('x', 9), ('y', 57)]\n",
"\n",
"distribución frances= [('a', 455), ('b', 76), ('c', 162), ('d', 289), ('e', 927), ('f', 71), ('g', 52), ('h', 52), ('i', 391), ('j', 21), ('l', 360), ('m', 147), ('n', 445), ('o', 314), ('p', 177), ('q', 64), ('r', 443), ('s', 388), ('t', 400), ('u', 317), ('v', 67), ('x', 23), ('y', 6)]\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
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},
"output_type": "display_data"
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],
"source": [ "source": [
"texto_esp ='''La batalla de Normandía, llamada en clave Operación Overlord, fue la operación militar efectuada por los Aliados durante la Segunda Guerra Mundial que culminó con la liberación de los territorios de la Europa occidental ocupados por la Alemania nazi. La operación dio comienzo el 6 de junio de 1944, más conocido como el Día D, con el desembarco de Normandía; el conjunto de las operaciones navales recibió el nombre clave de Operación Neptuno. Un asalto aerotransportado llevado a cabo por mil doscientas aeronaves precedió al desembarco anfibio, que involucró a cinco mil barcos. El 6 de junio, ciento sesenta mil soldados cruzaron el canal de la Mancha de Inglaterra a Francia y hacia finales de agosto las tropas aliadas en suelo francés eran más de tres millones.\n", "texto_esp ='''La batalla de Normandía, llamada en clave Operación Overlord, fue la operación militar efectuada por los Aliados durante la Segunda Guerra Mundial que culminó con la liberación de los territorios de la Europa occidental ocupados por la Alemania nazi. La operación dio comienzo el 6 de junio de 1944, más conocido como el Día D, con el desembarco de Normandía; el conjunto de las operaciones navales recibió el nombre clave de Operación Neptuno. Un asalto aerotransportado llevado a cabo por mil doscientas aeronaves precedió al desembarco anfibio, que involucró a cinco mil barcos. El 6 de junio, ciento sesenta mil soldados cruzaron el canal de la Mancha de Inglaterra a Francia y hacia finales de agosto las tropas aliadas en suelo francés eran más de tres millones.\n",
"La decisión de emprender una invasión a través del canal de la Mancha en 1944 se tomó en la Conferencia Trident de Washington D. C., en mayo de 1943. El general estadounidense Dwight D. Eisenhower fue nombrado comandante del Cuartel General Supremo de la Fuerza Expedicionaria Aliada (SHAEF) y el general británico Bernard Montgomery comandante del XXIer Grupo de Ejércitos, que aglutinaba todas las fuerzas terrestres que tomarían parte en la invasión. El lugar elegido fue la costa de la región francesa de Normandía, donde se seleccionaron cinco playas a las que se dieron nombres en clave: Utah y Omaha, que serían atacadas por los estadounidenses, Sword y Gold, objetivo de los británicos, y la playa Juno, lugar de desembarco de los canadienses. Los puertos franceses estaban fuertemente defendidos, lo que motivó la creación de dos muelles artificiales, denominados Mulberry, y para superar las dificultades que se esperaban en las playas se emplearon carros de combate especialmente modificados. En los meses previos a la operación, los Aliados llevaron a cabo una elaborada maniobra de distracción militar, la Operación Bodyguard, usando desinformación tanto electrónica como visual. Con ello consiguieron evitar que los alemanes supieran la fecha y localización de los desembarcos. Adolf Hitler había encargado al reputado mariscal de campo Erwin Rommel la supervisión y mejora de una cadena de fortificaciones costeras conocida como el Muro Atlántico, en previsión del ataque enemigo.\n", "La decisión de emprender una invasión a través del canal de la Mancha en 1944 se tomó en la Conferencia Trident de Washington D. C., en mayo de 1943. El general estadounidense Dwight D. Eisenhower fue nombrado comandante del Cuartel General Supremo de la Fuerza Expedicionaria Aliada (SHAEF) y el general británico Bernard Montgomery comandante del XXIer Grupo de Ejércitos, que aglutinaba todas las fuerzas terrestres que tomarían parte en la invasión. El lugar elegido fue la costa de la región francesa de Normandía, donde se seleccionaron cinco playas a las que se dieron nombres en clave: Utah y Omaha, que serían atacadas por los estadounidenses, Sword y Gold, objetivo de los británicos, y la playa Juno, lugar de desembarco de los canadienses. Los puertos franceses estaban fuertemente defendidos, lo que motivó la creación de dos muelles artificiales, denominados Mulberry, y para superar las dificultades que se esperaban en las playas se emplearon carros de combate especialmente modificados. En los meses previos a la operación, los Aliados llevaron a cabo una elaborada maniobra de distracción militar, la Operación Bodyguard, usando desinformación tanto electrónica como visual. Con ello consiguieron evitar que los alemanes supieran la fecha y localización de los desembarcos. Adolf Hitler había encargado al reputado mariscal de campo Erwin Rommel la supervisión y mejora de una cadena de fortificaciones costeras conocida como el Muro Atlántico, en previsión del ataque enemigo.\n",
...@@ -867,8 +845,37 @@ ...@@ -867,8 +845,37 @@
" for dist_f in dist_letras_fran:\n", " for dist_f in dist_letras_fran:\n",
" if let == dist_f[0] and dist_f[0] == dist_e[0]:\n", " if let == dist_f[0] and dist_f[0] == dist_e[0]:\n",
" ndist_esp.append(dist_e)\n", " ndist_esp.append(dist_e)\n",
" ndist_fr.append(dist_f)\n", " ndist_fr.append(dist_f)\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"distribución español= [('a', 855), ('b', 90), ('c', 283), ('d', 373), ('e', 846), ('f', 72), ('g', 59), ('h', 44), ('i', 416), ('j', 22), ('l', 414), ('m', 159), ('n', 498), ('o', 521), ('p', 167), ('q', 42), ('r', 461), ('s', 421), ('t', 273), ('u', 221), ('v', 59), ('x', 9), ('y', 57)]\n",
"\n", "\n",
"distribución frances= [('a', 455), ('b', 76), ('c', 162), ('d', 289), ('e', 927), ('f', 71), ('g', 52), ('h', 52), ('i', 391), ('j', 21), ('l', 360), ('m', 147), ('n', 445), ('o', 314), ('p', 177), ('q', 64), ('r', 443), ('s', 388), ('t', 400), ('u', 317), ('v', 67), ('x', 23), ('y', 6)]\n"
]
},
{
"data": {
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2222XpUuXpqrmu5wFqbWWG264IatXr87uu+/+gPZh+CgAALAg3Xbbbdlxxx0FwnWoquy4444PqjdVKAQAABYsgXB2D/YaCYUAAAALwBlnnJHvfve7Ez+uewoBAIBNw0mLNvL+1sy6yimnnJJTTz01++23Xz7wgQ9s3OOPec973pNbbrklu+2225wdY22EQgAAgLV45zvfmXPOOSdLliy5p+3OO+/Mlltu3Cj14he/eKPub0MYPgoAADCDl73sZbn66qtz6KGHZtGiRTnmmGNywAEH5JhjjsmqVavylKc8Jfvtt1/222+//Ou//muS5Nxzz82BBx6Y5z73uXnsYx+bF7zgBWmtJUkuvPDCPPnJT86+++6bFStW5JZbbsldd92VV7/61dl///2zzz775K//+q+TJNddd12e+tSnZtmyZdlrr73yhS98Yc7OU08hAADADN71rnflM5/5TP7lX/4lf/mXf5lPfvKT+eIXv5htt902t956a84+++xss802ufLKK3P00UfnoosuSpJ85StfyWWXXZZHPvKROeCAA/KlL30pK1asyPOf//ycddZZ2X///XPzzTdn2223zXve854sWrQoF154YW6//fYccMABOeigg/LRj340Bx98cF7/+tfnrrvuyq233jpn5ykUAgAArIdnPetZ2XbbbZMkd9xxR0488cSsXLkyW2yxRb71rW/ds96KFSvuGW66bNmyrFq1KosWLcouu+yS/fffP0my/fbbJ0k++9nP5mtf+1o+/OEPJ0nWrFmTK6+8Mvvvv39e9KIX5Y477sgRRxyRZcuWzdl5CYUAAADr4WEPe9g9z9/2trdl5513zle/+tXcfffd2Wabbe5ZtvXWW9/zfIsttsidd9651n221vKOd7wjBx988P2WnXfeefnUpz6V4447Lq961avywhe+cCOdyX25pxAAAGADrVmzJrvsskse8pCH5H3ve1/uuuuuda7/mMc8Jtddd10uvPDCJMktt9ySO++8MwcffHBOPfXU3HHHHUmSb33rW/nRj36Ua665JjvvvHNe8pKX5Pjjj88ll1wyZ+eipxAAANg0rMdXSEzKy1/+8hx55JF573vfm0MOOeQ+vYgzeehDH5qzzjorr3jFK/LjH/842267bc4555wcf/zxWbVqVfbbb7+01rJ48eJ8/OMfz7nnnps3v/nN2WqrrfLwhz88733ve+fsXGpqJpzNzfLly9vUjZ4AAMCm5/LLL8/jHve4+S5jkzDTtaqqi1try2fb1vBRAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DHfUwgAAGwSlr7uUxt1f6veeNhG3d+G+uhHP5o3velNeeQjH5ljjjkmz372s9e5/tKlS3PRRRdlp5122qh1CIUw305aNMFjLZwvfAUA6N1znvOcPOc5z5nvMgwfBQAAWJv3v//9WbFiRZYtW5aXvvSlueuuu3Lcccdlr732yt577523ve1tSZIDDzwwr3zlK7Ns2bLstddeueCCC5IkF1xwQZ70pCfl8Y9/fJ785CfniiuuSJKcfvrpec5znpNDDjkke+yxR17zmtfcc8wzzzwze++9d/baa6+89rWvnfNz1FMIAAAwg8svvzxnnXVWvvSlL2WrrbbKy1/+8px88sm59tprc+mllyZJbrrppnvWv/XWW7Ny5cqcd955edGLXpRLL700j33sY/OFL3whW265Zc4555z87u/+bj7ykY8kSVauXJmvfOUr2XrrrfOYxzwmr3jFK7LFFlvkta99bS6++OLssMMOOeigg/Lxj388RxxxxJydp1AIAAAwg8997nO5+OKLs//++ydJfvzjH+eQQw7J1VdfnVe84hU57LDDctBBB92z/tFHH50keepTn5qbb745N910U2655ZYce+yxufLKK1NVueOOO+5Z/+lPf3oWLRrdSrTnnnvmmmuuyQ033JADDzwwixcvTpK84AUvyHnnnTenoXDOho9W1WlV9YOqunSs7ayqWjk8VlXVyqF9aVX9eGzZu8a2eUJVfb2qrqqqU6qq5qpmAACAKa21HHvssVm5cmVWrlyZK664Im9/+9vz1a9+NQceeGDe9a535fjjj79n/elRpary+7//+3na056WSy+9NJ/85Cdz22233bN86623vuf5FltskTvvvHPuT2oGc3lP4elJDhlvaK09v7W2rLW2LMlHknx0bPG3p5a11l421n5qkpck2WN43GefAAAAc+HpT396PvzhD+cHP/hBkuTGG2/MNddck7vvvjtHHnlkTj755FxyySX3rH/WWWclSb74xS9m0aJFWbRoUdasWZNdd901yeg+wtmsWLEin//85/PDH/4wd911V84888z8wi/8wsY/uTFzNny0tXZeVS2dadnQ2/e8JL+4rn1U1S5Jtm+tnT+8fm+SI5L800YtFgAAWPAm/RUSe+65Z04++eQcdNBBufvuu7PVVlvlrW99a5797Gfn7rvvTpL86Z/+6T3rb7PNNnn84x+fO+64I6eddlqS5DWveU2OPfbYnHzyyTnssNnr32WXXfLGN74xT3va09Jay2GHHZbDDz98bk5wUK21udv5KBT+Y2ttr2ntT03y1tba8rH1LkvyrSQ3J/m91toXqmp5kje21n5pWO8pSV7bWnvmWo53QpITkmS33XZ7wjXXXDMHZwUbma+kAACY0eWXX57HPe5x813GejnwwAPzlre8JcuXL5+X4890rarq4qnMtS7z9ZUURyc5c+z1dUl2a609PsmrkpxRVdtv6E5ba+9urS1vrS2fujETAACAtZv47KNVtWWS5yR5wlRba+32JLcPzy+uqm8n+dkk1yZZMrb5kqENAABgwTj33HPnu4QHbD56Cn8pyTdba6unGqpqcVVtMTz/6YwmlLm6tXZdkpur6onDfYgvTPIP81AzAAAwD+bydrfNxYO9RnP5lRRnJvlyksdU1eqqevGw6Kjcd+hokjw1ydeGr6j4cJKXtdZuHJa9PMn/TnJVkm/HJDMAANCFbbbZJjfccINguA6ttdxwww3ZZpttHvA+5nL20aPX0n7cDG0fyegrKmZa/6Ike820DAAA2HwtWbIkq1evzvXXXz/fpSxo22yzTZYsWTL7imsx8XsKAQAA1sdWW22V3Xfffb7L2OzN1+yjAAAALABCIQAAQMeEQgAAgI4JhQAAAB0TCgEAADomFAIAAHRMKAQAAOiYUAgAANAxoRAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6JhQCAAB0TCgEAADomFAIAADQMaEQAACgY0IhAABAx4RCAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGNCIQAAQMeEQgAAgI4JhQAAAB0TCgEAADomFAIAAHRMKAQAAOiYUAgAANAxoRAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6JhQCAAB0TCgEAADomFAIAADQMaEQAACgY0IhAABAx4RCAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGNCIQAAQMeEQgAAgI4JhQAAAB0TCgEAADomFAIAAHRMKAQAAOiYUAgAANAxoRAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6JhQCAAB0TCgEAADo2JyFwqo6rap+UFWXjrWdVFXXVtXK4fGMsWW/U1VXVdUVVXXwWPshQ9tVVfW6uaoXAACgR3PZU3h6kkNmaH9ba23Z8Ph0klTVnkmOSvJzwzbvrKotqmqLJH+V5NAkeyY5elgXAACAjWDLudpxa+28qlq6nqsfnuSDrbXbk3ynqq5KsmJYdlVr7eokqaoPDut+YyOXCwAA0KX5uKfwxKr62jC8dIehbdck3xtbZ/XQtrb2GVXVCVV1UVVddP3112/sugEAADY7kw6FpyZ5dJJlSa5L8ucbc+ettXe31pa31pYvXrx4Y+4aAABgszRnw0dn0lr7/tTzqvqbJP84vLw2yaPGVl0ytGUd7QAAADxIE+0prKpdxl4+O8nUzKSfSHJUVW1dVbsn2SPJBUkuTLJHVe1eVQ/NaDKaT0yyZgAAgM3ZnPUUVtWZSQ5MslNVrU7yh0kOrKplSVqSVUlemiSttcuq6kMZTSBzZ5LfaK3dNeznxCT/nGSLJKe11i6bq5oBAAB6M5ezjx49Q/N71rH+G5K8YYb2Tyf59EYsDQAAgMF8zD4KAADAAiEUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGNCIQAAQMeEQgAAgI4JhQAAAB0TCgEAADomFAIAAHRMKAQAAOiYUAgAANAxoRAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6JhQCAAB0TCgEAADomFAIAADQMaEQAACgY0IhAABAx4RCAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGNCIQAAQMeEQgAAgI4JhQAAAB0TCgEAADomFAIAAHRMKAQAAOiYUAgAANAxoRAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6JhQCAAB0TCgEAADomFAIAADQMaEQAACgY0IhAABAx4RCAACAjgmFAAAAHRMKAQAAOrblfBfQnZMWTeg4ayZzHAAAYJOmpxAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6JhQCAAB0TCgEAADomFAIAADQMaEQAACgY0IhAABAx4RCAACAjgmFAAAAHRMKAQAAOiYUAgAAdGzOQmFVnVZVP6iqS8fa3lxV36yqr1XVx6rqEUP70qr6cVWtHB7vGtvmCVX19aq6qqpOqaqaq5oBAAB6M5c9hacnOWRa29lJ9mqt7ZPkW0l+Z2zZt1try4bHy8baT03ykiR7DI/p+wQAAOABmrNQ2Fo7L8mN09o+21q7c3h5fpIl69pHVe2SZPvW2vmttZbkvUmOmIt6AQAAejSf9xS+KMk/jb3evaq+UlWfr6qnDG27Jlk9ts7qoW1GVXVCVV1UVRddf/31G79iAACAzcy8hMKqen2SO5N8YGi6LslurbXHJ3lVkjOqavsN3W9r7d2tteWtteWLFy/eeAUDAABsprac9AGr6rgkz0zy9GFIaFprtye5fXh+cVV9O8nPJrk29x1iumRoAwAAYCOYaE9hVR2S5DVJntVau3WsfXFVbTE8/+mMJpS5urV2XZKbq+qJw6yjL0zyD5OsGQAAYHM2Zz2FVXVmkgOT7FRVq5P8YUazjW6d5OzhmyXOH2YafWqSP66qO5LcneRlrbWpSWpentFMpttmdA/i+H2IAAAAPAhzFgpba0fP0Pyetaz7kSQfWcuyi5LstRFLAwAAYDCfs48CAAAwz4RCAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGNCIQAAQMeEQgAAgI4JhQAAAB0TCgEAADomFAIAAHRMKAQAAOiYUAgAANAxoRAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6JhQCAAB0TCgEAADomFAIAADQMaEQAACgY0IhAABAx4RCAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGNCIQAAQMeEQgAAgI4JhQAAAB0TCgEAADomFAIAAHRMKAQAAOiYUAgAANAxoRAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6JhQCAAB0TCgEAADomFAIAADQMaEQAACgY0IhAABAx4RCAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGNCIQAAQMeEQgAAgI494FBYVftvzEIAAACYvC03ZOWq2jPJ0cPjpiTL56IoAAAAJmPWUFhVS3NvELwjyU8lWd5aWzWXhQEAADD31jl8tKq+nORTGYXHI1trT0hyi0AIAACweZjtnsLvJ9kuyc5JFg9tbU4rAgAAYGLWGQpba0ck2TvJxUlOqqrvJNmhqlZMojgAAADm1qyzj7bW1rTW/ra1dlCSJyb5gyRvq6rvzbZtVZ1WVT+oqkvH2n6iqs6uqiuH/+4wtFdVnVJVV1XV16pqv7Ftjh3Wv7Kqjn1AZwp++9h4AAAZ8ElEQVQAAMD9bNBXUrTWvt9ae0dr7YAk/2M9Njk9ySHT2l6X5HOttT2SfG54nSSHJtljeJyQ5NRkFCKT/GGSn0+yIskfTgVJAAAAHpx1zj5aVZ/Muu8hfNa6tm+tnTfMXjru8CQHDs//Lsm5SV47tL+3tdaSnF9Vj6iqXYZ1z26t3TjUdHZGQfPMdR0bAACA2c32lRRvmYNj7txau254/h8ZTWKTJLsmGR+SunpoW1v7/VTVCRn1Mma33XbbiCUDAABsnmYLhd9Isri19o3xxuFL7K9/sAdvrbWq2mizmbbW3p3k3UmyfPlys6QCAADMYrZ7Ct+RZKcZ2ndM8vYHeMzvD8NCM/z3B0P7tUkeNbbekqFtbe0AAAA8SLOFwp9prZ03vbG19oUk+zzAY34iydQMoscm+Yex9hcOs5A+McmaYZjpPyc5qKp2GCaYOWhoAwAA4EGabfjodutYttVsO6+qMzOaKGanqlqd0Syib0zyoap6cZJrkjxvWP3TSZ6R5Koktyb59SRprd1YVf9fkguH9f54atIZAAAAHpzZQuFVVfWM1tqnxxur6tAkV8+289ba0WtZ9PQZ1m1JfmMt+zktyWmzHQ8AAIANM1so/M0kn6qq5yW5eGhbnuRJSZ45l4UBAAAw99Z5T2Fr7cokeyf5fJKlw+PzSfZprX1rrosDAABgbs3WU5jW2u1J/nYCtQAAADBh6wyFVfWdJGv7vr/WWnv0xi8JAACASZmtp3D5tNcPyWi20N9O8pU5qQgAAICJWWcobK3dkCRV9ZAkxyR5dZKVSQ5rrX1j7ssDAABgLs02fHSrJC9K8ltJvpjkiNbaVZMoDAAAgLk32/DR7yS5M8lfJPlukn2qap+pha21j85hbQAAAMyx2ULhORlNNLPv8BjXkgiFAAAAm7DZ7ik8bkJ1AAAAMA9mu6fwL1prvzk8f2Vr7e1jy04XGgFgQk5aNMFjrZncsQCYdw+ZZflTx54fO23ZPgEAAGCTNlsorLU8BwAAYDMw20QzD6mqHTIKj1PPp8LhFnNaGQAAAHNutlC4KMnFuTcIXjK2rM1JRQAAAEzMbLOPLp1QHQAAAMyD2WYf3W9aU0vyw9ba9+auJAAAACZltuGjfz5D209U1UOTHN1aWzkHNQEAADAhsw0ffdpM7VW1PMkpue9XVgAAALCJme0rKWbUWrsoycM3ci0AAABM2AMKhVW1c8w+CgAAsMmbbaKZd+T+4e8nkjw5ySvnqigAAAAmY7aJZi6a9roluSHJq1prP5ibkgAAWC8nLZrQcdZM5jjAvJgtFH46yeLW2jfGG6tqz6pqrbXr5640AAAA5tps9xS+I8lOM7TvmOTtG78cAAAAJmm2UPgzrbXzpje21r6QZJ+5KQkAAIBJmS0UbreOZVttzEIAAACYvNlC4VVV9YzpjVV1aJKr56YkAAAAJmW2iWZ+K8k/VtXzklw8tC1P8qQkz5zLwgAAAJh76+wpbK19K8neST6fZOnw+HySfYZlAAAAbMJm+/L6x7bWvpnkb6tq69ba7WPLnthaO3/OKwQAAGDOzHZP4Rljz788bdk7N3ItAAAATNhsobDW8nym1wAAAGxiZguFbS3PZ3oNAADAJma22UeXVNUpGfUKTj3P8HrXOa0MAACAOTdbKHz12POLpi2b/hoAAIBNzDpDYWvt79a2rKp22/jlbP6W3nbG7CttBKsmchQAAGBTN9s9hamqJ1XVc6vqJ4fX+1TVGUm+NOfVAQAAMKfWGQqr6s1JTktyZJJPVdXJST6b5N+S7DH35QEAADCXZrun8LAkj2+t3VZVOyT5XpK9Wmur5rwy6MSkhhQnhhUDAHB/sw0fva21dluStNb+M8mVAiEAAMDmY7aewp+uqk+Mvd59/HVr7VlzUxYAAACTMFsoPHza6z+fq0IAgAXupEUTPNaayR0LoHOzhcLvtNa+O5FKAAAAmLjZ7in8+NSTqvrIHNcCAADAhM0WCmvs+U/PZSEAAABM3myhsK3lOQAAAJuB2e4p3Leqbs6ox3Db4XmG1621tv2cVgcAAMCcWmcobK1tMalCAAAAmLzZho8CAACwGZtt+CgA82FS3wfnu+CAB8v3V8ImT08hAABAx4RCAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGNCIQAAQMe2nO8CAGCtTlo0wWOtmdyxAGAB0VMIAADQMaEQAACgY0IhAABAxyYeCqvqMVW1cuxxc1X9ZlWdVFXXjrU/Y2yb36mqq6rqiqo6eNI1AwAAbK4mPtFMa+2KJMuSpKq2SHJtko8l+fUkb2utvWV8/araM8lRSX4uySOTnFNVP9tau2uihQMAAGyG5nv46NOTfLu1ds061jk8yQdba7e31r6T5KokKyZSHQAAwGZuvkPhUUnOHHt9YlV9rapOq6odhrZdk3xvbJ3VQ9v9VNUJVXVRVV10/fXXz03FAAAAm5F5C4VV9dAkz0ry90PTqUkendHQ0uuS/PmG7rO19u7W2vLW2vLFixdvtFoBAAA2V/PZU3hokktaa99Pktba91trd7XW7k7yN7l3iOi1SR41tt2SoQ0AAIAHaT5D4dEZGzpaVbuMLXt2kkuH559IclRVbV1VuyfZI8kFE6sSAABgMzbx2UeTpKoeluSXk7x0rPlNVbUsSUuyampZa+2yqvpQkm8kuTPJb5h5FAAAYOOYl1DYWvtRkh2ntR2zjvXfkOQNc10XAABAb+Z79lEAAADmkVAIAADQMaEQAACgY0IhAABAx4RCAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGNCIQAAQMeEQgAAgI4JhQAAAB0TCgEAADomFAIAAHRsy/kuAAAAHpSTFk3wWGsmdyyYED2FAAAAHRMKAQAAOmb4KH2b1HATQ00AAFig9BQCAAB0TCgEAADomFAIAADQMaEQAACgY0IhAABAx4RCAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGNCIQAAQMeEQgAAgI4JhQAAAB0TCgEAADomFAIAAHRMKAQAAOiYUAgAANAxoRAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6JhQCAAB0TCgEAADomFAIAADQMaEQAACgY0IhAABAx4RCAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGNbzncBAACwWThp0YSOs2Yyx6EbegoBAAA6JhQCAAB0TCgEAADomFAIAADQMRPNAADrZeltZ0zsWKsmdiQA9BQCAAB0TCgEAADo2LyFwqpaVVVfr6qVVXXR0PYTVXV2VV05/HeHob2q6pSquqqqvlZV+81X3QAAAJuT+e4pfFprbVlrbfnw+nVJPtda2yPJ54bXSXJokj2GxwlJTp14pQAAAJuh+Q6F0x2e5O+G53+X5Iix9ve2kfOTPKKqdpmPAgEAADYn8zn7aEvy2apqSf66tfbuJDu31q4blv9Hkp2H57sm+d7YtquHtuvG2lJVJ2TUk5jddtttDksHgMky8ycAc2U+Q+H/aK1dW1U/meTsqvrm+MLWWhsC43obguW7k2T58uUbtC0AAECP5m34aGvt2uG/P0jysSQrknx/aljo8N8fDKtfm+RRY5svGdoAAAB4EOYlFFbVw6pqu6nnSQ5KcmmSTyQ5dljt2CT/MDz/RJIXDrOQPjHJmrFhpgAAADxA8zV8dOckH6uqqRrOaK19pqouTPKhqnpxkmuSPG9Y/9NJnpHkqiS3Jvn1yZcMAACw+ZmXUNhauzrJvjO035Dk6TO0tyS/MYHSAAAAurLQvpICAACACRIKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0LH5+koKAAAepKW3nTGR46yayFGA+aKnEAAAoGNCIQAAQMeEQgAAgI4JhQAAAB0z0Qzz46RFEzzWmskdCwAANjF6CgEAADomFAIAAHRMKAQAAOiYUAgAANAxoRAAAKBjQiEAAEDHfCUFAAAP2NLbzpjYsVZN7EjQF6EQYAGa1IesVRM5CgCwkAmFACxYeiAAYO65pxAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6JhQCAAB0TCgEAADomFAIAADQMaEQAACgY0IhAABAx4RCAACAjm053wXAfFp62xkTOc6qiRwFAAA2nJ5CAACAjgmFAAAAHRMKAQAAOiYUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGO+pxAA2LSctGiCx1ozuWMBzBM9hQAAAB0TCgEAADomFAIAAHRMKAQAAOiYUAgAANAxoRAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6tuV8FwAAC95JiyZ0nDWTOQ4AjNFTCAAA0DGhEAAAoGNCIQAAQMeEQgAAgI4JhQAAAB0TCgEAADrmKymYF0tvO2Nix1o1sSMBAMCmR08hAABAx4RCAACAjhk+CgDAJs1tKfDg6CkEAADomFAIAADQMaEQAACgYxMPhVX1qKr6l6r6RlVdVlWvHNpPqqprq2rl8HjG2Da/U1VXVdUVVXXwpGsGAADYXM3HRDN3Jvl/W2uXVNV2SS6uqrOHZW9rrb1lfOWq2jPJUUl+Lskjk5xTVT/bWrtrolUDAABshibeU9hau661dsnw/JYklyfZdR2bHJ7kg62121tr30lyVZIVc18pAADA5m9e7ymsqqVJHp/k34amE6vqa1V1WlXtMLTtmuR7Y5utzlpCZFWdUFUXVdVF119//RxVDQAAsPmYt1BYVQ9P8pEkv9lauznJqUkenWRZkuuS/PmG7rO19u7W2vLW2vLFixdv1HoBAAA2R/MSCqtqq4wC4Qdaax9Nktba91trd7XW7k7yN7l3iOi1SR41tvmSoQ0AAIAHaT5mH60k70lyeWvtrWPtu4yt9uwklw7PP5HkqKrauqp2T7JHkgsmVS8AAMDmbD5mHz0gyTFJvl5VK4e2301ydFUtS9KSrEry0iRprV1WVR9K8o2MZi79DTOPAgAAbBwTD4WttS8mqRkWfXod27whyRvmrCgAAIBOzevsowAAAMwvoRAAAKBj83FPIQAAbHaW3nbGRI6zaiJHoSd6CgEAADomFAIAAHRMKAQAAOiYUAgAANAxoRAAAKBjQiEAAEDHhEIAAICOCYUAAAAdEwoBAAA6JhQCAAB0TCgEAADomFAIAADQMaEQAACgY0IhAABAx4RCAACAjm053wUwD05aNMFjrZncsQDowtLbzpjYsVZN7EgA80dPIQAAQMf0FALALCbVM7VqIkcBgPvSUwgAANAxoRAAAKBjQiEAAEDHhEIAAICOmWgG8DUlAAAd01MIAADQMaEQAACgY0IhAABAx4RCAACAjploBgAANhcmj+MB0FMIAADQMaEQAACgY0IhAABAx9xTCCwc7oMAAJg4PYUAAAAd01MIALChjGwANiN6CgEAADomFAIAAHTM8FGAcYaEAQCd0VMIAADQMT2FHVp62xkTO9aqiR0JAAB4IPQUAgAAdEwoBAAA6JhQCAAA0DGhEAAAoGMmmgFMPgQA0DE9hQAAAB3TUwgAAGx+Tlo0wWOtmdyx5oCeQgAAgI7pKQQWDPc2AsCD4/+l93It1p+eQgAAgI4JhQAAAB0TCgEAADrmnkKAMe4/GGPWNgDoglAIALCB/AEJ2JwYPgoAANAxPYUAAMDG4/aDTY6eQgAAgI4JhQAAAB0zfBSAGZlIAwD6oKcQAACgY0IhAABAx4RCAACAjm0y9xRW1SFJ3p5kiyT/u7X2xnkuCQAAmMY96ZueTaKnsKq2SPJXSQ5NsmeSo6tqz/mtCgAAYNO3SYTCJCuSXNVau7q19n+TfDDJ4fNcEwAAwCavWmvzXcOsquq5SQ5prR0/vD4myc+31k6ctt4JSU4YXj4myRUTLXTu7JTkh2pIsjDqUMO9FkIdC6GGZGHUoYZ7LYQ61HCvhVDHQqghWRh1qOFeC6EONdxrIdSxEGrYmH6qtbZ4tpU2mXsK10dr7d1J3j3fdWxsVXVRa2157zUslDrUsLDqWAg1LJQ61LCw6lDDwqpjIdSwUOpQw8KqQw0Lq46FUMN82FSGj16b5FFjr5cMbQAAADwIm0oovDDJHlW1e1U9NMlRST4xzzUBAABs8jaJ4aOttTur6sQk/5zRV1Kc1lq7bJ7LmqSFMCR2IdSQLIw61HCvhVDHQqghWRh1qOFeC6EONdxrIdSxEGpIFkYdarjXQqhDDfdaCHUshBombpOYaAYAAIC5sakMHwUAAGAOCIUAAAAdEwpZp6paWlWXzncdC01VnVRVvz3fdfz/7d197FZlHcfx92fWEsSFsVmzLRnF1KBBEpkpDUmaNd16QBBrrIflTDZKR+tJN8d0Q6nxV6XlmBlozArLmg8bajyYk4QfAvJghc6wh0WJ/qQHgk9/nOuHNz6kND3XYffntZ3tPgd+v+vDzbnPdX/PdZ1zapI0T9JWSctqZ6mla58PSffXzgD1c0garNl+RHSfpJGSLqmdI6IrUhRGxP/rEmC67U/WDhIN2++vnQG6kyMi/jc1+vW74EiafiwiSFHYeZJuk/SQpC2SLqoU43WSlpVRoR9LGt52AElzJD0saaOkH7bdfsnwDUk7JK0BTqqRoeT4lKQHJQ1Iul7SURUyXAeMAe6QdGnb7ffkuELSdklrJN1SafT2KEnfL5/RuyUNq5AB6M4IWVdytK2MHG+TdGM5ViyTdLaktZIelfTelrNsrb1vSrpM0uayfKnt9kuGof+X2v3YwT6k4vFq6P3YLukmYDOHPge6jfaPkfTL0p9vljSrzfZ7LATeXvrSRTUCPH+2iaT5kq5sOcNCSXN71lufCSVpcvmOd3TZP7ZIGt9mhpJjQe9xStLVkr7Ydo5aUhR232dtTwLeA8yTNKpChpOA79g+BXials+sSRoHXA5Msz0BaP0DKmkSzfMxJwIfASa3naHkOAWYBZxheyKwH2h9pM72xcCTwFm2F7fdPjSdCPAJYALwYZrPSA1jgW/bHgc8VTJF/3oH8C3g5LJcCJwJzAe+3nKWqvtmOW5+BjgNeB/weUnvbjNDj9r9WCf6kB5jad6PcbYfb7ntc4AnbU+wPR64s+X2h3wV+J3tiba/XClDFywHZvaszyzbWmN7Hc3zx68CrgWW2q5xacYSYA5AGUG/AFhaIUcVKQq7b56kjcADNGfzxlbI8ITtteX1UpovOG2aBtxq+68Atv/WcvsAU4AVtvfafprm4FXDB4FJwDpJA2V9TKUstZ0B/Mz2P20/A9xeKcdO2wPl9UPA6Eo5oht22t5k+wCwBVjp5tlPm2h/36i9b55Jc9x81vYg8FOaY2kNtfuxrvQhQx63/UCltjcB0yVdI2mK7T2VcgRgewNwvKQTJE0A/m77iQpRFgDTaU7wXluhfWw/BuwuJ68+BGywvbtGlhqOiIfX9ytJU4GzgdNt75V0H3B0hSjPf5hlHm5Zj4Af2P5a7SBx0L96Xu8Hqk0fjU7o3R8O9KwfoP0+N/vmc9KPHerZWg3b3iHpVJoR06skrbS9oFaeyv7DoQM0Nb7jAdwKzADeQsujhD1GASOA19O8D7X20RuAT9O8F0sqZagiI4Xd9kaaMzZ7JZ1MM/2mhrdJOr28vhBY03L79wDnD02dlfSmltsHWAV8VNIwSccC51XIALASmCHpeGjeC0knVspS21rgvHINwgjg3NqBIuIQq2mOm8MlHQN8rGyroXY/1pU+pDpJJwB7bS8FFgGnVoryDHBspbaH/JlmlG6UpDdQrx9bTjNVcgZNgVjD9cAVwDLgmkoZAFbQTHGeDNxVMUfrMlLYbXcCF0vaCmynmUJaw3ZgrqQlwCPAd9ts3PYWSVcDv5K0H9hAcxanzQzrJS0HNgJ/Ada12X5PjkckXQ7cXea77wPmAm1fE1Kd7XWSfg48TNOxbgIyDakb+n0UJjh43LwReLBsuqFMVauhdj/WiT6kI94FLJJ0gKYP+0KNELZ3l5tAbQbuqHFdoe19khbQfEZ2AdvazlBybCknK3bZ/mPb7UuaA+yzfbOam+fdL2ma7XvazmL735LuBZ6yvb/t9mtSc6lDRMSRR9II24PlToKrgItsr6+dq5+VEf31tvt1BDs6RtJo4BflpiadUO4wOWj7m7WzRMRzygn39cD5th+tnadNmT4aEUey75Ub7qwHfpKCsK4yLezXQL7oRkTEEUXSO4Hf0twgrK8KQshIYURERERERF/LSGFEREREREQfS1EYERERERHRx1IURkRERERE9LEUhRERES9B0uCLbLtS0i5JAz3LrJ7Xg5K2l9c3SZoqaU9Z3ybpBTfikXSbpFqPHYqIiD6X5xRGREQcvsUv8jiB5QCS7gPm2/5NWZ8KrLZ9rqRhwAZJK2yvLX8+EpgEDEoaY/v3bf0jIiIiICOFERERrbH9D2AAeGvP5o8DtwM/Ai6okSsiIvpbisKIiIjDd2nPdNF7X+kPSToOGAus6tk8G7ilLLNf3ZgREREvL0VhRETE4Vtse2JZznoFf3+KpI3ALuAu238CkPRmmiJxje0dwD5J41+72BERES+UojAiIuK1t9r2BGAc8DlJE8v2mcBxwE5JjwGjyWhhRES0LEVhRERES2zvBBYCXymbZgPn2B5tezTNDWdyXWFERLQqRWFERMRLGy7pDz3LZWV77zWFA5JGH8bvvA74QPmZE4GDj6IoReMeSae9OvEjIiJenmzXzhARERERERGVZKQwIiIiIiKij6UojIiIiIiI6GMpCiMiIiIiIvpYisKIiIiIiIg+lqIwIiIiIiKij6UojIiIiIiI6GMpCiMiIiIiIvrYfwHHl5JKPNZpgwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 1080x720 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"print('distribución español=', ndist_esp)\n", "print('distribución español=', ndist_esp)\n",
"print()\n", "print()\n",
"print('distribución frances=', ndist_fr)\n", "print('distribución frances=', ndist_fr)\n",
......
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