Commit 859b113a authored by templier_w56's avatar templier_w56

mod2ex3

parent 8e7c00c8
{
"jupyter.jupyterServerType": "remote"
"jupyter.jupyterServerType": "local",
"python.pythonPath": "/usr/bin/python3"
}
\ No newline at end of file
{
"cells": [
{
"source": [],
"source": [
"# Hello"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"hello world\n"
]
}
],
"source": [
"print(\"hello world\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
......@@ -22,7 +48,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
"version": "3.8.5-final"
}
},
"nbformat": 4,
......
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{
"cells": [],
"cells": [
{
"source": [
"# MOOC RR\n",
"\n",
"## Module 2: exo 3\n",
"\n",
"Premièrement, nous importons les _librairies_ nécessaires:"
],
"cell_type": "markdown",
"metadata": {}
},
{
"source": [
"from statistics import mean, median, stdev"
],
"cell_type": "code",
"metadata": {},
"execution_count": 1,
"outputs": []
},
{
"source": [
"Ensuite, nous stockons les données dans une variable `data`:"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"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]"
]
},
{
"source": [
"Ceci étant fait, passons aux questions.\n",
"\n",
"### Calcul de la moyenne:"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"moyenne = 14.113\n"
]
}
],
"source": [
"moyenne = mean(data)\n",
"print(f\"moyenne = {moyenne}\")"
]
},
{
"source": [
"### Calcul du minimum et maximum:"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"maximum = 23.4\nminimum = 2.8\n"
]
}
],
"source": [
"maximum = max(data)\n",
"print(f\"maximum = {maximum}\")\n",
"\n",
"minimum = min(data)\n",
"print(f\"minimum = {minimum}\")"
]
},
{
"source": [
"### Calcul de la médiane et de l'écart-type:"
],
"cell_type": "markdown",
"metadata": {}
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"médiane = 14.5\nécart-type = 4.334094455301447\n"
]
}
],
"source": [
"med = median(data)\n",
"print(f\"médiane = {med}\")\n",
"\n",
"ec = stdev(data)\n",
"print(f\"écart-type = {ec}\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
......@@ -16,10 +136,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
"version": "3.8.5-final"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
}
\ No newline at end of file
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