Maël DAIM
2 years ago
parent
e0cbe397eb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "03338ae6",
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"metadata": {},
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"source": [
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"# Statistiques\n",
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"\n",
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"### Préparation des données et insertion dans les dataframe.\n",
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"Ainsi aue le nettoyage des données (suppression des données redondantes et les données non renseignées) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "ad4af851",
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"metadata": {},
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"outputs": [
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{
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"ename": "ModuleNotFoundError",
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"evalue": "No module named 'plotly'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
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"Input \u001b[0;32mIn [2]\u001b[0m, in \u001b[0;36m<cell line: 9>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpatches\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mmpatches\u001b[39;00m\n\u001b[1;32m 8\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mre\u001b[39;00m\n\u001b[0;32m----> 9\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mplotly\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mexpress\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpx\u001b[39;00m\n\u001b[1;32m 11\u001b[0m data \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m./csv/Report_2022.csv\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 12\u001b[0m df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame(data)\n",
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"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'plotly'"
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]
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}
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],
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"source": [
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"import pandas as pd \n",
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"import psycopg2 as psy \n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import subprocess as sp\n",
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"import seaborn as sns\n",
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"import matplotlib.patches as mpatches\n",
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"import re\n",
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"import plotly.express as px\n",
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"\n",
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"data = pd.read_csv(r'./csv/Report_2022.csv')\n",
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"df_2022 = pd.DataFrame(data)\n",
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"df_2022 = df.drop_duplicates()\n",
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"df_2022 = df.dropna()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "7dbda889",
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"metadata": {},
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"source": [
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"Map des globales score sur"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "f66aef89",
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"metadata": {},
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'px' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"Input \u001b[0;32mIn [3]\u001b[0m, in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m sns\u001b[38;5;241m.\u001b[39mset(rc\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maxes.facecolor\u001b[39m\u001b[38;5;124m\"\u001b[39m:\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m#d1f0ec\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgrid.color\u001b[39m\u001b[38;5;124m\"\u001b[39m:\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m#b7c7c9\u001b[39m\u001b[38;5;124m\"\u001b[39m})\n\u001b[0;32m----> 3\u001b[0m fig \u001b[38;5;241m=\u001b[39m \u001b[43mpx\u001b[49m\u001b[38;5;241m.\u001b[39mchoropleth(df_2022, locations\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mISO Code\u001b[39m\u001b[38;5;124m'\u001b[39m, color\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mGlobal Score\u001b[39m\u001b[38;5;124m'\u001b[39m, hover_name \u001b[38;5;241m=\u001b[39m df_2022\u001b[38;5;241m.\u001b[39mindex, hover_data\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPosition 2022\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRegion\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mContinent\u001b[39m\u001b[38;5;124m\"\u001b[39m], title\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mGlobal Score Map\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 4\u001b[0m fig\u001b[38;5;241m.\u001b[39mshow()\n",
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"\u001b[0;31mNameError\u001b[0m: name 'px' is not defined"
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]
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}
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],
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"source": [
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"sns.set(rc={\"axes.facecolor\":\"#d1f0ec\", \"grid.color\":\"#b7c7c9\"})\n",
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"\n",
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"fig = px.choropleth(df_2022, locations='ISO Code', color='Global Score', hover_name = df_2022.index, hover_data=[\"Position 2022\", \"Region\", \"Continent\"], title='Global Score Map')\n",
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"fig.show()\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0f0c4172",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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