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import streamlit as st
import pandas as pd
import requests
import folium
from streamlit_folium import folium_static
def get_data():
url = "https://opendata.bordeaux-metropole.fr/api/records/1.0/search/?dataset=met_etablissement_rse&q=&rows=100"
response = requests.get(url)
if response.status_code == 200:
data = response.json()
records = data.get("records", [])
# Ensure that 'point_geo' is extracted correctly as a dictionary with 'lat' and 'lon'
cleaned_data = []
for record in records:
item = record["fields"]
point_geo = item.get("point_geo", {})
if isinstance(point_geo, dict):
lat = point_geo.get("lat")
lon = point_geo.get("lon")
if lat and lon:
item['latitude'] = lat
item['longitude'] = lon
cleaned_data.append(item)
return cleaned_data, data.get("nhits", 0)
else:
return [], 0
def display_map(data):
m = folium.Map(location=[44.837789, -0.57918], zoom_start=12)
for item in data:
lat = item.get('latitude')
lon = item.get('longitude')
if lat and lon:
folium.Marker(
[lat, lon],
icon=folium.Icon(color="green", icon="leaf"),
popup=item.get('Nom', 'Sans nom'),
).add_to(m)
folium_static(m)
def display_organisations_engagees():
st.markdown("## OPEN DATA RSE")
st.markdown("### Découvrez les organisations engagées RSE de la métropole de Bordeaux")
data, _ = get_data()
if data:
df = pd.DataFrame(data)
df = df.rename(columns={
"nom_courant_denomination": "Nom",
"commune": "Commune",
"libelle_section_naf": "Section NAF",
"tranche_effectif_entreprise": "Effectif",
"action_rse": "Action RSE"
})
df = df[["Nom", "Commune", "Section NAF", "Effectif", "Action RSE"]]
st.dataframe(df, width=None, height=None)
def main():
st.sidebar.title("Navigation")
app_mode = st.sidebar.radio("Choisissez l'onglet", ["Organisations engagées", "Localisation des Entreprises"])
if app_mode == "Organisations engagées":
display_organisations_engagees()
elif app_mode == "Localisation des Entreprises":
data, _ = get_data()
display_map(data)
if __name__ == "__main__":
main()
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