Data.gouv.fr_Visualisation_carte_de_France_éducation.ipynb

Kernel: Python 3

Data.gouv.fr - Visualisation de la carte de France des établissements éducatifs

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Tags: #Data.gouv.fr

Author: Paul Gilbert

Last update: 2024-02-29 (Created: 2024-02-29)

Description: This notebook demonstrates how to extract schools information ("identifiant", "latitude" and "longitude" from Data.gouv.fr API and then visualize it on a map with plotly.express.

References:

• Data education.gouv.fr

• Naas Documentation

Input

Import libraries

import pandas as pd
import requests
import json
import plotly.express as px
import ipywidgets as widgets
from IPython.display import display

Setup variables

• url: Link to data source in JSON.

• output_csv: CSV output path.

url = 'https://data.education.gouv.fr/api/explore/v2.1/catalog/datasets/fr-en-annuaire-education/exports/json'
output_csv = "Education_France.csv"

Model

Get data from 'data.education.gouv.fr'

def get_data(url):                                                                            
    res = requests.get(url)
    if res.status_code == 200:
        return pd.DataFrame(res.json())
    
df = get_data(url)
print('Etablissements:', len(df))
df.head(3)

Visualize the schools on a map with plotly.express

# Create dropdown widget
dropdown_type = widgets.Dropdown(
    options=df['type_etablissement'].unique().tolist(),
    value='Ecole',
    description="Type d'établissement"
)

dropdown_region = widgets.Dropdown(
    options=sorted(df.libelle_region.unique().tolist()),
    value='Ile-de-France',
    description="Région"
)

# Function to update plot
def update_plot(
    type_etablissement,
    region,
):
    filtered_df = df[(df['type_etablissement'] == type_etablissement) & (df['libelle_region'] == region)]
    fig = px.scatter_mapbox(
        filtered_df, 
        lat="latitude", 
        lon="longitude",
        color="nombre_d_eleves",
        color_continuous_scale=px.colors.cyclical.IceFire,
        zoom=6, 
        height=1200,
        width=1200
    )
    
    fig.update_layout(mapbox_style="open-street-map")
    fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
    fig.show()

# Use widgets.interact to create the interactive plot
widgets.interact(update_plot, type_etablissement=dropdown_type, region=dropdown_region)

Output

Save DataFrame to csv

df.to_csv(output_csv, index=False)