Statistiques => Observatoire #65
This commit is contained in:
Colin Maudry
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from datetime import datetime, timedelta
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import dash_bootstrap_components as dbc
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import polars as pl
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import polars.selectors as cs
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from dash import Input, Output, callback, dcc, html, register_page
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from src.figures import get_geographic_maps, make_card, make_donut
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from src.utils import (
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departements,
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df,
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format_number,
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get_enum_values_as_dict,
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meta_content,
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)
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name = "Observatoire"
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register_page(
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__name__,
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path="/observatoire",
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title="Observatoire | decp.info",
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name=name,
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description="Visualisez l'état de la publication des données essentielles des marchés publics en France.",
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image_url=meta_content["image_url"],
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order=3,
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)
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options_years = {}
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for year in reversed(range(2017, datetime.now().year + 1)):
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year = str(year)
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options_years[year] = year
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options_departements = {}
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for code, obj in departements.items():
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options_departements[code] = f"{obj['departement']} ({code})"
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layout = [
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dcc.Store(id="dashboard-filters"),
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dcc.Location(id="dashboard_url"),
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html.Div(
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className="container-fluid",
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children=[
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html.H2(name),
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dcc.Loading(
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overlay_style={"visibility": "visible", "filter": "blur(2px)"},
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id="loading-statistques",
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type="default",
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children=[
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dbc.Row(
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[
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dbc.Col(
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xl=3,
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lg=4,
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id="filters",
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children=[
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html.H5("Période d'attribution"),
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dbc.Row(
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dcc.Dropdown(
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id="dashboard_year",
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options=options_years,
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placeholder="12 derniers mois",
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),
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),
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html.H5("Acheteur"),
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dbc.Row(
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dcc.Dropdown(
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id="dashboard_acheteur_categorie",
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options=get_enum_values_as_dict(
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"acheteur_categorie"
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),
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placeholder="Catégorie",
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),
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),
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dbc.Row(
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dcc.Dropdown(
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id="dashboard_acheteur_departement_code",
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searchable=True,
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multi=True,
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placeholder="Code département acheteur",
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options=options_departements,
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),
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),
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html.H5("Titulaire"),
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dbc.Row(
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dcc.Dropdown(
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id="dashboard_titulaire_categorie",
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placeholder="Catégorie",
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options=get_enum_values_as_dict(
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"titulaire_categorie"
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),
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),
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),
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html.H5("Marché"),
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dbc.Row(
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dcc.Dropdown(
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id="dashboard_marche_type",
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placeholder="Type",
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options=get_enum_values_as_dict("type"),
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),
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),
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dbc.Row(
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dcc.Dropdown(
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id="dashboard_marche_considerationsSociales",
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placeholder="Considérations sociales",
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options=get_enum_values_as_dict(
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"considerationsSociales"
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),
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multi=True,
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),
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),
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dbc.Row(
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dcc.Dropdown(
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id="dashboard_marche_considerationsEnvironnementales",
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placeholder="Considérations environnementales",
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multi=True,
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options=get_enum_values_as_dict(
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"considerationsEnvironnementales"
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),
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),
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),
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],
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),
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dbc.Col(
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width=12,
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lg=8,
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xl=9,
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id="cards",
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children=[],
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),
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]
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)
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],
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),
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],
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),
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]
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@callback(
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Output("cards", "children"),
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Input("dashboard_year", "value"),
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Input("dashboard_acheteur_categorie", "value"),
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Input("dashboard_acheteur_departement_code", "value"),
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Input("dashboard_titulaire_categorie", "value"),
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Input("dashboard_marche_type", "value"),
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Input("dashboard_marche_considerationsSociales", "value"),
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Input("dashboard_marche_considerationsEnvironnementales", "value"),
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)
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def udpate_dashboard_cards(
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dashboard_year,
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dashboard_acheteur_categorie,
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dashboard_acheteur_departement_code,
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dashboard_titulaire_categorie,
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dashboard_marche_type,
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dashboard_marche_considerationsSociales,
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dashboard_marche_considerationsEnvironnementales,
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):
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lff: pl.LazyFrame = df.lazy()
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lff = lff.select(
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"uid",
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cs.starts_with("acheteur"),
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cs.starts_with("titulaire"),
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"dateNotification",
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"montant",
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"considerationsSociales",
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"considerationsEnvironnementales",
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)
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# Application des filtres
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## Période
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if dashboard_year:
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lff = lff.filter(pl.col("dateNotification").dt.year() == int(dashboard_year))
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else:
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lff = lff.filter(
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pl.col("dateNotification") > (datetime.now() - timedelta(days=365))
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)
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## Acheteur
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if dashboard_acheteur_categorie:
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lff = lff.filter(pl.col("acheteur_categorie") == dashboard_acheteur_categorie)
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if dashboard_acheteur_departement_code:
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lff = lff.filter(
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pl.col("acheteur_departement_code").is_in(
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dashboard_acheteur_departement_code
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)
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)
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## Titulaire
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if dashboard_titulaire_categorie:
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lff = lff.filter(pl.col("titulaire_categorie") == dashboard_titulaire_categorie)
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## Marché
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if dashboard_marche_type:
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lff = lff.filter(pl.col("type") == dashboard_marche_type)
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if dashboard_marche_considerationsSociales:
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lff = lff.filter(
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pl.col("considerationsSociales")
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.str.split(", ")
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.list.set_intersection(dashboard_marche_considerationsSociales)
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.list.len()
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> 0
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)
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if dashboard_marche_considerationsEnvironnementales:
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lff = lff.filter(
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pl.col("considerationsEnvironnementales")
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.str.split(", ")
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.list.set_intersection(dashboard_marche_considerationsEnvironnementales)
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.list.len()
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> 0
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)
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# Génération des métriques
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dff = lff.collect(engine="streaming")
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# À transformer en fonction
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nb_acheteurs = dff.select("acheteur_id").n_unique()
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nb_titulaires = dff.select("titulaire_id", "titulaire_typeIdentifiant").n_unique()
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df_per_uid = (
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dff.select("uid", "montant").group_by("uid").agg(pl.col("montant").first())
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)
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total_montant = df_per_uid.select(pl.col("montant").sum()).item()
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nb_marches = df_per_uid.height
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cards = []
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card_basic_counts = [
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html.P(["Nombre de marchés : ", html.Strong(str(format_number(nb_marches)))]),
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html.P(
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["Nombre d'acheteurs : ", html.Strong(str(format_number(nb_acheteurs)))]
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),
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html.P(
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["Nombre de titulaires : ", html.Strong(str(format_number(nb_titulaires)))]
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),
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html.P(["Montant total : ", html.Strong(format_number(total_montant) + " €")]),
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]
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cards.append(make_card(title="Résumé", paragraphs=card_basic_counts))
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donut_acheteur_categorie = make_donut(lff, "acheteur_categorie")
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cards.append(make_card(title="Catégorie d'acheteur", fig=donut_acheteur_categorie))
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donut_titulaire_categorie = make_donut(lff, "titulaire_categorie")
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cards.append(
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make_card(title="Catégorie d'entreprise", fig=donut_titulaire_categorie)
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)
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geographic_maps: list[dbc.Col] = get_geographic_maps(dff)
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return dbc.Row(children=cards + geographic_maps)
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