exercice 3 : graphiques

parent 2cdfc01c
{
"cells": [],
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# exercice 3\n",
"## Reproduction de la 1re figure (séquence plot) "
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7fae253b1f28>]"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
},
{
"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": [
"import matplotlib.pyplot as plt\n",
"data = [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2, 16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0, 13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6, 19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3, 16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0\n",
"]\n",
"plt.xlim(0,100)\n",
"plt.ylim(0,25)\n",
"plt.grid()\n",
"plt.plot(data, color='blue')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Reproduction de la 2e figure (histogramme) "
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(array([ 4., 3., 5., 9., 16., 20., 22., 9., 8., 4.]),\n",
" array([ 2.8 , 4.86, 6.92, 8.98, 11.04, 13.1 , 15.16, 17.22, 19.28,\n",
" 21.34, 23.4 ]),\n",
" <a list of 10 Patch objects>)"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD8CAYAAACMwORRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAADj1JREFUeJzt3W+IHPd9x/HPx5Ebg88Qm1x8V5/NtcU+agR1c8ItuIQ9goPrJ7ahCdUDI5OU84MYHGJBjZ9EEAymXN0+KaU2NlHBcTmwXJsQ2hqjixoIJVqjSnKPs0Mqu2eLE8IK9j2J/+ibBzvqXqSTdnd2dnbvu+8XLLszO7O/7/7ut5+bm52Zc0QIAJDLVcMuAABQPcIdABIi3AEgIcIdABIi3AEgIcIdABLqGO62b7Z92Paq7TdtP1rMP2D7PdvHitu9gy8XANANdzrO3fa0pOmIeMP2dZKaku6X9A1JmxGxNPgyAQC92NVpgYg4Lel08fgj26uSbhp0YQCA8jpuuf/WwvaspCOSdkv6rqSHJH0o6aikxyLi3DbrLEpalKRrrrlm/pZbbum35hTOnz+vq67iKw+JvtiKvmijL9reeuutsxEx2cs6XYe77QlJP5H0ZEQcsn2jpLOSQtL31dp1880rvcbc3Fysra31Ul9aKysrajQawy5jJNAXbfRFG33RZrsZEXt6WaerX4u2r5b0kqQXIuKQJEXERkR8FhHnJT0r6c5eCwYADEY3R8tY0nOSViPi6S3zp7cs9oCkk9WXBwAoo+MXqpLukvSgpBO2jxXznpC01/Ydau2WOSXp4YFUCADoWTdHy/xUkrd56sfVlwMAqAJfRQNAQoQ7ACREuANAQoQ7ACREuANAQoQ7ACREuANAQoQ7ACREuANAQoQ7ACREuANAQoQ7ACREuANAQoQ7ACREuANAQoQ7ACREuANAQoQ7ACREuANAQoQ7ACREuAMjaGpqVrZru01NzQ77LaNiu4ZdAIBLbWy8IylqbM+1tYV6sOUOAAkR7gCQEOEOAAkR7gCQEOEOAAkR7gCQEOEOAAkR7gCQEOEOAAkR7gCQEOEOAAkR7gCQEOEOAAl1DHfbN9s+bHvV9pu2Hy3m32D7NdtvF/fXD75cAEA3utly/1TSYxHxh5L+VNK3bd8u6XFJr0fErZJeL6YBACOgY7hHxOmIeKN4/JGkVUk3SbpP0sFisYOS7h9UkQCA3jii+38IYHtW0hFJuyW9GxFf2PLcuYi4ZNeM7UVJi5I0OTk5v7y83GfJOWxubmpiYmLYZYyEndAXx4+f0CeffDzwdmZmZrS+vl5MzQ+8vbam5ufrbK+znTAu6rKwsNCMiD29rNN1uNuekPQTSU9GxCHbv+om3Leam5uLtbW1XupLa2VlRY1GY9hljISd0Be2Vcd/RlpaWtH+/Q1J9bTXZvWyoVeHnTAu6mK753Dv6mgZ21dLeknSCxFxqJi9YXu6eH5a0pleGgYADE43R8tY0nOSViPi6S1PvSppX/F4n6RXqi8PAFBGN/8g+y5JD0o6YftYMe8JSU9JWrb9LUnvSvr6YEoEAPSqY7hHxE/V2gG4na9WWw4AoAqcoQoACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACRHuAJAQ4Q4ACe0adgFAWVNTs9rYeGfYZQAjiXDHjtUK9qipNdfUDlANdssAQEKEOwAkRLgDQEIdw93287bP2D65Zd4B2+/ZPlbc7h1smQCAXnSz5f4DSfdsM//vIuKO4vbjassCAPSjY7hHxBFJH9RQCwCgIo7ofCiZ7VlJP4qI3cX0AUkPSfpQ0lFJj0XEucusuyhpUZImJyfnl5eXKyh759vc3NTExMSwyxgJZfui2WxKmq++oO1bq6WtmZlNra9P1NZeW1Pz83W21xmfkbaFhYVmROzpZZ2y4X6jpLNqHWT8fUnTEfHNTq8zNzcXa2trvdSX1srKihqNxrDLGAll+8K26j3OffBtLS2taP/+Rm3ttVndZEGd+Iy02e453EsdLRMRGxHxWUScl/SspDvLvA4AYDBKhbvt6S2TD0g6ebllAQD163j5AdsvSmpI+qLtdUnfk9SwfYdafzeekvTwAGsEAPSoY7hHxN5tZj83gFoAABXhDFUASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASKhjuNt+3vYZ2ye3zLvB9mu23y7urx9smQCAXnSz5f4DSfdcNO9xSa9HxK2SXi+mAQAjomO4R8QRSR9cNPs+SQeLxwcl3V9xXQCAPjgiOi9kz0r6UUTsLqZ/FRFf2PL8uYjYdteM7UVJi5I0OTk5v7y8XEHZO9/m5qYmJiaGXcZIKNsXzWZT0nz1BW3fWi1tzcxsan19orb22pqan6+zvc74jLQtLCw0I2JPL+sMPNy3mpubi7W1tV7qS2tlZUWNRmPYZYyEsn1hW1Ln8VuNetpaWlrR/v2N2tprs7rJgjrxGWmz3XO4lz1aZsP2dNHotKQzJV8HADAAZcP9VUn7isf7JL1STTkAgCp0cyjki5J+JmnO9rrtb0l6StLdtt+WdHcxDQAYEbs6LRARey/z1FcrrgUAUBHOUAWAhAh3AEiIcAeAhAh3VGZqala2e741m81S66FKny/1Myhzm5qaHfabHQsdv1AFurWx8Y7KnXizUnI9Ar46v1ZdJ01tbPBzqwNb7gCQEOEOAAkR7gCQEOEOAAkR7gCQEOEOAAkR7gBq1t0x9WXPf+C4+haOcwdQs26PqV/pcrkrG9fj6tlyB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECHcASIhwB4CEdvWzsu1Tkj6S9JmkTyNiTxVFAQD601e4FxYi4mwFrwMAqAi7ZQAgIUdE+ZXt/5V0TlJI+qeIeGabZRYlLUrS5OTk/PLycun2Mtnc3NTExMTA2zl+/IQ++eTjgbfTNt/zGjMzm1pfL9MXzVLtlVNPW+2+qPO9qeb2umur/Li4tL35+Tr7snoLCwvNnnd7R0Tpm6TfLe6/JOm/JX3lSsvfdtttgZbDhw/X0o6kkKKmW7m2lpYO19reKLfV7os639to9mX5cXFpezudpKMRveVzX7tlIuL94v6MpJcl3dnP6wEAqlE63G1fa/u6C48lfU3SyaoKAwCU18/RMjdKetn2hdf5YUT8WyVVAQD6UjrcI+KXkv6owloAABXhUEgASIhwB4CECHcASGjsw31qala2a7tNTc0O+y0DY+bzY/n5ruLaMjvaxsY7kqLG9lxbWwAk6deq6zM+Sp/vsd9yB4CMCHcASIhwB4CECHcASIhwB4CECHcASIhwB4CECPfatU6oaDabtZxUAWA8jf1JTPW7cELFiuo5sYKAB8YRW+4AkBDhDgAJEe4AkBDhDgAJEe4AkBDhDgAJEe4AkBDhDgAJEe4AkBDhDgAJEe4AkBDhDgAJEe4AkBDhDgAJEe4AkBDhDgAJEe4AkBDhDgAJEe4AkBDhDgAJEe4AkFBf4W77Httrtn9h+/GqigIA9Kd0uNv+nKR/kPTnkm6XtNf27VUVBgAor58t9zsl/SIifhkRH0v6F0n3VVMWAKAfjohyK9p/IemeiPirYvpBSX8SEY9ctNyipMVicrekk+XLTeWLks4Ou4gRQV+00Rdt9EXbXERc18sKu/pozNvMu+Q3RUQ8I+kZSbJ9NCL29NFmGvRFG33RRl+00Rdtto/2uk4/u2XWJd28ZXpG0vt9vB4AoCL9hPvPJd1q+/ds/46kv5T0ajVlAQD6UXq3TER8avsRSf8u6XOSno+INzus9kzZ9hKiL9roizb6oo2+aOu5L0p/oQoAGF2coQoACRHuAJBQLeHOZQp+m+1Ttk/YPlbmEKedzPbzts/YPrll3g22X7P9dnF//TBrrMtl+uKA7feKsXHM9r3DrLEOtm+2fdj2qu03bT9azB+7cXGFvuh5XAx8n3txmYK3JN2t1uGTP5e0NyL+Z6ANjzDbpyTtiYixO0HD9lckbUr654jYXcz7G0kfRMRTxS//6yPir4dZZx0u0xcHJG1GxNIwa6uT7WlJ0xHxhu3rJDUl3S/pIY3ZuLhCX3xDPY6LOrbcuUwB/l9EHJH0wUWz75N0sHh8UK3BnN5l+mLsRMTpiHijePyRpFVJN2kMx8UV+qJndYT7TZL+b8v0ukoWm0hI+g/bzeLyDOPuxog4LbUGt6QvDbmeYXvE9vFit036XRFb2Z6V9MeS/ktjPi4u6gupx3FRR7h3dZmCMXNXRHxZrStqfrv48xyQpH+U9AeS7pB0WtLfDrec+tiekPSSpO9ExIfDrmeYtumLnsdFHeHOZQouEhHvF/dnJL2s1q6rcbZR7Gu8sM/xzJDrGZqI2IiIzyLivKRnNSZjw/bVaoXZCxFxqJg9luNiu74oMy7qCHcuU7CF7WuLL0pk+1pJXxNXynxV0r7i8T5JrwyxlqG6EGaFBzQGY8O2JT0naTUint7y1NiNi8v1RZlxUcsZqsVhO3+v9mUKnhx4oyPK9u+rtbUutS7/8MNx6g/bL0pqqHU51w1J35P0r5KWJd0i6V1JX4+I9F80XqYvGmr96R2STkl6+MJ+56xs/5mk/5R0QtL5YvYTau1rHqtxcYW+2KsexwWXHwCAhDhDFQASItwBICHCHQASItwBICHCHQASItwBICHCHQAS+g3z0hMYu39EPAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.axis([0, 25, 0, 25])\n",
"plt.grid()\n",
"plt.hist(data, color='blue', edgecolor='black')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
......@@ -16,10 +107,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment