|
|
| import streamlit as st |
| import pandas as pd |
| import plotly.express as px |
| from data_manager import get_data |
| from wordcloud import WordCloud, STOPWORDS |
| import matplotlib.pyplot as plt |
|
|
| def display_companies_by_sector(df): |
| sector_counts = df['libelle_section_naf'].value_counts().reset_index() |
| sector_counts.columns = ['Secteur', 'Nombre'] |
| fig = px.bar(sector_counts, x='Secteur', y='Nombre', |
| color='Nombre', labels={'Nombre': ''}, template='plotly_white') |
| fig.update_layout(xaxis_tickangle=-45, showlegend=False) |
| fig.update_traces(showlegend=False) |
| st.plotly_chart(fig) |
|
|
| def display_company_sizes(df): |
| fig = px.histogram(df, x='tranche_effectif_entreprise', |
| labels={'tranche_effectif_entreprise':"Taille de l'entreprise", 'count':'Nombre'}, template='plotly_white') |
| fig.update_traces(marker_color='green') |
| fig.update_layout(yaxis_title="Nombre") |
| st.plotly_chart(fig) |
|
|
| def display_companies_by_commune(df): |
| commune_counts = df['commune'].value_counts(normalize=True).reset_index() |
| commune_counts.columns = ['Commune', 'Pourcentage'] |
| fig = px.pie(commune_counts, values='Pourcentage', names='Commune', |
| template='plotly_white', hole=.3) |
| fig.update_traces(textinfo='percent+label') |
| st.plotly_chart(fig) |
|
|
| def display_rse_actions_wordcloud(df): |
| st.header("Nuage de mots Actions RSE") |
| |
| custom_stopwords = set(["l", "d", "d ", "des", "qui", "ainsi", "toute", "hors", "plus", "cette", "afin", "via", "d'", "sa", "dans", "ont", "avec", "aux", "ce", "chez", "ont", "cela", "la", "un", "avons", "par", "c'est", "s'est", "aussi", "leurs", "d'un", "nos", "les", "sur", "ses", "tous", "nous", "du", "notre", "de", "et", "est", "pour", "le", "une", "se", "en", "au", "à", "que", "sont", "leur", "son"]) |
| stopwords = STOPWORDS.union(custom_stopwords) |
| |
| text = " ".join(action for action in df['action_rse'].dropna()) |
| |
| wordcloud = WordCloud(stopwords=stopwords, background_color="white", width=800, height=400).generate(text) |
| |
| fig, ax = plt.subplots() |
| ax.imshow(wordcloud, interpolation='bilinear') |
| ax.axis('off') |
| st.pyplot(fig) |
|
|
| def main(): |
| data, _ = get_data() |
| df = pd.DataFrame(data) |
| |
| if not df.empty: |
| st.markdown("## OPEN DATA Bordeaux Métropole RSE") |
| st.markdown("### Statistiques sur les entreprises engagées RSE") |
| |
| st.header("Répartition des entreprises par secteur d'activité") |
| display_companies_by_sector(df) |
| st.header("Distribution des tailles d'entreprises") |
| display_company_sizes(df) |
| st.header("Pourcentage d'entreprises par Commune") |
| display_companies_by_commune(df) |
| display_rse_actions_wordcloud(df) |
|
|
| if __name__ == "__main__": |
| main() |
|
|
