diff --git a/module2/exo2/exercice_fr.ipynb b/module2/exo2/exercice_fr.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..665cf4bcb4bb1c9b2f487df815043be9aa72a472 100644
--- a/module2/exo2/exercice_fr.ipynb
+++ b/module2/exo2/exercice_fr.ipynb
@@ -1,5 +1,76 @@
{
- "cells": [],
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Savoir faire un calcul simple soi-même"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data = (\n",
+ "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",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(2.8, 23.4)"
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# pour inspection visuel\n",
+ "sorted_data = sorted(data)\n",
+ "sorted_data[0], sorted_data[-1]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "La moyenne du jeu de donnée est de 14.113000000000001\n",
+ "L'écart-type du jeu de donnée est de 4.334094455301447\n",
+ "Le jeu de donnée s'étend de min = 2.8 à max = 23.4\n",
+ "La médiane du jeu de donnée est de 14.5\n"
+ ]
+ }
+ ],
+ "source": [
+ "import numpy as np\n",
+ "\n",
+ "moy = np.mean(data)\n",
+ "print(f\"La moyenne du jeu de donnée est de {moy}\")\n",
+ "ecart_type = np.std(data, ddof=1)\n",
+ "print(f\"L'écart-type du jeu de donnée est de {ecart_type}\")\n",
+ "min = np.amin(data)\n",
+ "max = np.amax(data)\n",
+ "print(f\"Le jeu de donnée s'étend de min = {min} à max = {max}\")\n",
+ "mediane = np.median(data)\n",
+ "print(f\"La médiane du jeu de donnée est de {mediane}\")"
+ ]
+ }
+ ],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
@@ -16,10 +87,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.3"
+ "version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
-
diff --git a/module2/exo3/exercice.ipynb b/module2/exo3/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..f6d5640ee705fa3a77a27be651cef01bb692da52 100644
--- a/module2/exo3/exercice.ipynb
+++ b/module2/exo3/exercice.ipynb
@@ -1,5 +1,24 @@
{
- "cells": [],
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Réaliser un affichage graphique"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data = (\n",
+ "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",
+ ")"
+ ]
+ }
+ ],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
@@ -16,10 +35,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.6.3"
+ "version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
-
diff --git a/module3/exo3/co2_file.csv b/module3/exo3/co2_file.csv
new file mode 100644
index 0000000000000000000000000000000000000000..da5e1a61cebc8b4d9a3b167bb15a7360ed40a3e6
--- /dev/null
+++ b/module3/exo3/co2_file.csv
@@ -0,0 +1,3311 @@
+date,value
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diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb
index 7dbd2ac4ae32e1d00af40040155a604bf2566f7c..4493a6e65d6cd223f07237490be71edf72e22a5e 100644
--- a/module3/exo3/exercice.ipynb
+++ b/module3/exo3/exercice.ipynb
@@ -2,15 +2,21 @@
"cells": [
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "hideCode": false,
+ "hidePrompt": false
+ },
"source": [
"# Sujet 1 : Concentration de CO2 dans l'atmosphère depuis 1958"
]
},
{
"cell_type": "code",
- "execution_count": 2,
- "metadata": {},
+ "execution_count": 7,
+ "metadata": {
+ "hideCode": false,
+ "hidePrompt": false
+ },
"outputs": [],
"source": [
"%matplotlib inline\n",
@@ -18,6 +24,8 @@
"import pandas as pd\n",
"import isoweek\n",
"\n",
+ "from os.path import exists\n",
+ "\n",
"# set diagram sizes\n",
"# print(plt.rcParams['figure.dpi']) # default = 72\n",
"# print(plt.rcParams['figure.figsize']) # default = 6.0, 4.0\n",
@@ -27,15 +35,21 @@
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "hideCode": false,
+ "hidePrompt": false
+ },
"source": [
"Les données sont disponibles sur le site Web de l'[institut Scripps. ](https://scrippsco2.ucsd.edu/data/atmospheric_co2/primary_mlo_co2_record.html)"
]
},
{
"cell_type": "code",
- "execution_count": 9,
- "metadata": {},
+ "execution_count": 8,
+ "metadata": {
+ "hideCode": false,
+ "hidePrompt": false
+ },
"outputs": [
{
"data": {
@@ -101,21 +115,30 @@
"4 1958-04-26 316.48"
]
},
- "execution_count": 9,
+ "execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "# récolte le 12/02\n",
- "data_url = \"https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/weekly/weekly_in_situ_co2_mlo.csv\"\n",
- "data = pd.read_csv(data_url, encoding = 'utf-8', comment='\"', names=[\"date\", \"value\"])\n",
+ "filename = \"co2_file.csv\"\n",
+ "if not exists(filename):\n",
+ " # récolte le 12/02\n",
+ " data_url = \"https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/weekly/weekly_in_situ_co2_mlo.csv\"\n",
+ " data = pd.read_csv(data_url, encoding = 'utf-8', comment='\"', names=[\"date\", \"value\"])\n",
+ " data.to_csv(filename, index=False)\n",
+ "else:\n",
+ " data = pd.read_csv(filename, encoding = 'utf-8', comment='\"')\n",
+ "\n",
"data.head(5)"
]
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "hideCode": false,
+ "hidePrompt": false
+ },
"source": [
"## Contrôle Qualité\n",
"### Recherche des lignes sans donnée"
@@ -123,8 +146,11 @@
},
{
"cell_type": "code",
- "execution_count": 10,
- "metadata": {},
+ "execution_count": 9,
+ "metadata": {
+ "hideCode": false,
+ "hidePrompt": false
+ },
"outputs": [
{
"data": {
@@ -162,7 +188,7 @@
"Index: []"
]
},
- "execution_count": 10,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
@@ -173,7 +199,10 @@
},
{
"cell_type": "markdown",
- "metadata": {},
+ "metadata": {
+ "hideCode": false,
+ "hidePrompt": false
+ },
"source": [
"Il ne manque aucune donnée.\n",
"\n",
@@ -183,38 +212,265 @@
},
{
"cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
+ "execution_count": 10,
+ "metadata": {
+ "hideCode": false,
+ "hidePrompt": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " date | \n",
+ " value | \n",
+ "
\n",
+ " \n",
+ " timestamp | \n",
+ " | \n",
+ " | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 1958-03-29 | \n",
+ " 1958-03-29 | \n",
+ " 316.19 | \n",
+ "
\n",
+ " \n",
+ " 1958-04-05 | \n",
+ " 1958-04-05 | \n",
+ " 317.31 | \n",
+ "
\n",
+ " \n",
+ " 1958-04-12 | \n",
+ " 1958-04-12 | \n",
+ " 317.69 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
"
+ ],
+ "text/plain": [
+ " date value\n",
+ "timestamp \n",
+ "1958-03-29 1958-03-29 316.19\n",
+ "1958-04-05 1958-04-05 317.31\n",
+ "1958-04-12 1958-04-12 317.69"
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "data['timestamp'] = [ pd.to_datetime(d) for d in data['date'] ]\n",
+ "data['timestamp'] = pd.to_datetime(data['date'])\n",
"sorted_data = data.set_index('timestamp').sort_index()\n",
- "sorted_data.head(5)\n",
- "# for row1, row2 in zip(sorted_data[:-1], sorted_data[1:]):\n",
- "# delta = (row2['timestamp'] - row1['timestamp']).days\n",
- "# if delta != 7:\n",
- "# print(row1)"
+ "sorted_data.head(3)"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 11,
+ "metadata": {
+ "hideCode": false,
+ "hidePrompt": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[1958-05-03 00:00:00,1958-05-17 00:00:00] => 14 days 00:00:00\n",
+ "[1958-05-24 00:00:00,1958-07-05 00:00:00] => 42 days 00:00:00\n",
+ "[1958-08-16 00:00:00,1958-08-30 00:00:00] => 14 days 00:00:00\n",
+ "[1958-09-06 00:00:00,1958-11-08 00:00:00] => 63 days 00:00:00\n",
+ "[1959-01-31 00:00:00,1959-02-14 00:00:00] => 14 days 00:00:00\n",
+ "[1959-03-07 00:00:00,1959-03-21 00:00:00] => 14 days 00:00:00\n",
+ "[1959-05-23 00:00:00,1959-06-06 00:00:00] => 14 days 00:00:00\n",
+ "[1959-08-08 00:00:00,1959-08-22 00:00:00] => 14 days 00:00:00\n",
+ "[1962-08-18 00:00:00,1962-09-15 00:00:00] => 28 days 00:00:00\n",
+ "[1962-12-22 00:00:00,1963-01-05 00:00:00] => 14 days 00:00:00\n",
+ "[1963-02-09 00:00:00,1963-02-23 00:00:00] => 14 days 00:00:00\n",
+ "[1963-04-27 00:00:00,1963-05-11 00:00:00] => 14 days 00:00:00\n",
+ "[1963-11-16 00:00:00,1963-11-30 00:00:00] => 14 days 00:00:00\n",
+ "[1964-01-18 00:00:00,1964-05-30 00:00:00] => 133 days 00:00:00\n",
+ "[1964-06-06 00:00:00,1964-06-27 00:00:00] => 21 days 00:00:00\n",
+ "[1964-08-01 00:00:00,1964-08-15 00:00:00] => 14 days 00:00:00\n",
+ "[1966-07-09 00:00:00,1966-08-06 00:00:00] => 28 days 00:00:00\n",
+ "[1966-10-29 00:00:00,1966-11-12 00:00:00] => 14 days 00:00:00\n",
+ "[1967-01-14 00:00:00,1967-02-04 00:00:00] => 21 days 00:00:00\n",
+ "[1976-06-19 00:00:00,1976-07-03 00:00:00] => 14 days 00:00:00\n",
+ "[1984-03-24 00:00:00,1984-04-28 00:00:00] => 35 days 00:00:00\n",
+ "[1985-07-27 00:00:00,1985-08-10 00:00:00] => 14 days 00:00:00\n",
+ "[2003-06-07 00:00:00,2003-06-21 00:00:00] => 14 days 00:00:00\n",
+ "[2003-10-04 00:00:00,2003-10-25 00:00:00] => 21 days 00:00:00\n",
+ "[2005-02-19 00:00:00,2005-03-26 00:00:00] => 35 days 00:00:00\n",
+ "[2006-02-04 00:00:00,2006-02-25 00:00:00] => 21 days 00:00:00\n",
+ "[2007-01-20 00:00:00,2007-02-03 00:00:00] => 14 days 00:00:00\n",
+ "[2012-09-29 00:00:00,2012-10-20 00:00:00] => 21 days 00:00:00\n",
+ "[2020-01-11 00:00:00,2020-01-25 00:00:00] => 14 days 00:00:00\n",
+ "[2022-11-26 00:00:00,2022-12-17 00:00:00] => 21 days 00:00:00\n"
+ ]
+ }
+ ],
+ "source": [
+ "timestamp = sorted_data.index\n",
+ "for t1, t2 in zip(timestamp[:-1], timestamp[1:]):\n",
+ " delta = t2 - t1\n",
+ " # print(delta)\n",
+ " if delta > pd.Timedelta('7d'):\n",
+ " print(f\"[{t1},{t2}] => {delta}\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "hideCode": false,
+ "hidePrompt": false
+ },
+ "source": [
+ "Il y avait de nombreuses données manquantes."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {
+ "hideCode": false,
+ "hidePrompt": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "sorted_data['value'].plot()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
"metadata": {},
- "outputs": [],
"source": [
- "l_index = sorted_data.index\n",
- "l_index.head(5)"
+ "On a un signal oscillant, mais toujours croissant."
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 17,
"metadata": {},
- "outputs": [],
- "source": []
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 17,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "sorted_data['value'][:200].plot()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "sorted_data['value'][:150].plot()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "hideCode": false,
+ "hideOutput": true,
+ "hidePrompt": false
+ },
+ "source": [
+ "La période du signal semble annuel, avec un pic vers le mois de juin et le plus bas vers octobre-novembre."
+ ]
}
],
"metadata": {
+ "hide_code_all_hidden": false,
"kernelspec": {
"display_name": "Python 3",
"language": "python",