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| import streamlit as st | |
| from data_manager_bziiit import get_bziiit_data | |
| def display_labelled_companies(): | |
| st.markdown("## Entreprises Labellisées (source OPEN DATA bziiit)") | |
| st.markdown("### Découvrez les entreprises engagées avec au moins un label RSE") | |
| # Récupération des données bziiit | |
| bziiit_data = get_bziiit_data() | |
| # Filtrage des entreprises ayant au moins un label | |
| labelled_companies = [brand for brand in bziiit_data if brand['type'] == 'brand' and len(brand.get('labels', [])) > 0] | |
| # Calcul du nombre de labels par entreprise | |
| for brand in labelled_companies: | |
| brand['label_count'] = len(brand['labels']) | |
| # Calcul et affichage du nombre et du pourcentage d'entreprises labellisées | |
| total_companies = len([brand for brand in bziiit_data if brand['type'] == 'brand']) | |
| labelled_companies_count = len(labelled_companies) | |
| percentage_labelled = round((labelled_companies_count / total_companies) * 100) | |
| st.markdown(f"**Nb entreprises labellisées :** {labelled_companies_count} ({percentage_labelled}%)") | |
| # Tri des entreprises par le nombre de labels, ordre décroissant | |
| labelled_companies.sort(key=lambda x: x['label_count'], reverse=True) | |
| # Affichage des entreprises | |
| for i in range(0, len(labelled_companies), 5): | |
| cols = st.columns(5) | |
| image_placeholders = [col.empty() for col in cols] | |
| padding_placeholders = [col.empty() for col in cols] | |
| text_placeholders = [col.empty() for col in cols] | |
| for j in range(5): | |
| if i + j < len(labelled_companies): | |
| company = labelled_companies[i + j] | |
| with cols[j]: | |
| if company['logo_url'] != 'Unknown': | |
| image_placeholders[j].image(company['logo_url'], width=100) | |
| padding_placeholders[j].write("") # This will act as padding | |
| text_placeholders[j].write(company['name']) | |
| text_placeholders[j].write(f"Nb labels : {company['label_count']}") | |