Style inputs, ajout donut type marché #65
This commit is contained in:
Colin Maudry
+211
-63
@@ -3,9 +3,15 @@ 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 dash import ALL, Input, Output, callback, ctx, 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.figures import (
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get_barchart_sources,
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get_duplicate_matrix,
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get_geographic_maps,
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make_card,
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make_donut,
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)
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from src.utils import (
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departements,
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df,
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@@ -38,6 +44,29 @@ for code, obj in departements.items():
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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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dbc.Modal(
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[
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dbc.ModalHeader(dbc.ModalTitle("Montants")),
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dbc.ModalBody(
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[
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dcc.Markdown(
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"""
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Les données saisies et publiées par les acheteurs comportent de nombreux montants farfelus qui sabotent les statistiques, au lieu de montants estimés avec rigueur. On parle de montant atteignant parfois les millions de milliards. Certains réutilisateurs mettent de côté ces marchés ou bien modifient les montants selon des règles fatalement arbitraires. J'ai fait le choix de ne quasiment pas modifier les données* afin de visibiliser le problème.
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Alors, on fait comment ?
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\* Les montants composés de plus de 11 chiffres, sans les décimales, [sont ramenés](https://github.com/ColinMaudry/decp-processing/blob/main/src/tasks/clean.py#L63-L71) à 12 311 111 111, un nombre qui reste très élevé et qui est facilement reconnaissable.
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"""
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),
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]
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),
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dbc.ModalFooter(
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dbc.Button("Fermer", id="montant-modal-close", className="ms-auto")
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),
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],
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id="montant-modal",
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is_open=False,
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),
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html.Div(
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className="container-fluid",
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children=[
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@@ -56,66 +85,109 @@ layout = [
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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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dbc.Col(
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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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),
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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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dbc.Col(
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dcc.Input(
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id="dashboard_acheteur_id",
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placeholder="SIRET",
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style={"width": "100%"},
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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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dbc.Col(
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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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),
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dbc.Row(
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dbc.Col(
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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="Département",
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options=options_departements,
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),
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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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dbc.Col(
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dcc.Input(
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id="dashboard_titulaire_id",
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placeholder="SIRET",
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style={"width": "100%"},
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),
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),
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),
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dbc.Row(
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dbc.Col(
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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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),
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dbc.Row(
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dbc.Col(
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dcc.Dropdown(
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id="dashboard_titulaire_departement_code",
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searchable=True,
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multi=True,
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placeholder="Département",
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options=options_departements,
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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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dbc.Col(
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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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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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dbc.Col(
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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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),
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dbc.Row(
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dbc.Col(
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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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@@ -140,21 +212,27 @@ layout = [
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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_id", "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_id", "value"),
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Input("dashboard_titulaire_categorie", "value"),
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Input("dashboard_titulaire_departement_code", "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_id,
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dashboard_acheteur_categorie,
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dashboard_acheteur_departement_code,
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dashboard_titulaire_id,
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dashboard_titulaire_categorie,
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dashboard_titulaire_departement_code,
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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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dashboard_marche_considerations_sociales,
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dashboard_marche_considerations_environnementales,
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):
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lff: pl.LazyFrame = df.lazy()
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lff = lff.select(
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@@ -165,6 +243,8 @@ def udpate_dashboard_cards(
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"montant",
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"considerationsSociales",
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"considerationsEnvironnementales",
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"sourceDataset",
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"type",
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)
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# Application des filtres
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@@ -180,40 +260,57 @@ def udpate_dashboard_cards(
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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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if dashboard_acheteur_id:
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lff = lff.filter(pl.col("acheteur_id").str.contains(dashboard_acheteur_id))
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else:
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if dashboard_acheteur_categorie:
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lff = lff.filter(
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pl.col("acheteur_categorie") == dashboard_acheteur_categorie
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)
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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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)
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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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if dashboard_titulaire_id:
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lff = lff.filter(pl.col("titulaire_id").str.contains(dashboard_titulaire_id))
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else:
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if dashboard_titulaire_categorie:
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lff = lff.filter(
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pl.col("titulaire_categorie") == dashboard_titulaire_categorie
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)
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if dashboard_titulaire_departement_code:
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lff = lff.filter(
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pl.col("titulaire_departement_code").is_in(
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dashboard_titulaire_departement_code
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)
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)
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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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if dashboard_marche_considerations_sociales:
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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.set_intersection(dashboard_marche_considerations_sociales)
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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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if dashboard_marche_considerations_environnementales:
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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.set_intersection(dashboard_marche_considerations_environnementales)
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.list.len()
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> 0
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)
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@@ -228,7 +325,8 @@ def udpate_dashboard_cards(
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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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total_montant = int(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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@@ -241,19 +339,69 @@ def udpate_dashboard_cards(
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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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html.P(
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[
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"Montant total (",
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html.Span(
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"?",
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id={"type": "modal-trigger", "index": "montant"},
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style={"cursor": "pointer", "textDecoration": "underline dotted"},
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),
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") : ",
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html.Strong(format_number(total_montant) + " €"),
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]
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),
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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_acheteur_categorie = make_donut(
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lff, "acheteur_categorie", nulls="Autres", per_uid=True
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)
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cards.append(
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make_card(
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title="Catégorie d'acheteur", fig=donut_acheteur_categorie, lg=12, xl=8
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)
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)
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donut_titulaire_categorie = make_donut(lff, "titulaire_categorie")
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donut_titulaire_categorie = make_donut(
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lff, "titulaire_categorie", per_uid=False, nulls="?"
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)
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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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donut_marche_type = make_donut(lff, "type", per_uid=True, nulls="?")
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cards.append(make_card(title="Type d'achat", fig=donut_marche_type))
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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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other_cards = []
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sources_barchart = get_barchart_sources(lff, type_date="dateNotification")
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other_cards.append(
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make_card(title="Sources de données", fig=sources_barchart, lg=12, xl=8)
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)
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duplicate_matrix = get_duplicate_matrix()
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other_cards.append(
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make_card(
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title="Matrice de doublons entre sources de données",
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subtitle="Ce graphique illustre les doublons de marchés publics entre sources, c'est-à-dire la proportion de marchés publiés par plus d'une source.",
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fig=duplicate_matrix,
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lg=12,
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xl=8,
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)
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)
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return dbc.Row(children=cards + geographic_maps + other_cards)
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@callback(
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Output("montant-modal", "is_open"),
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Input({"type": "modal-trigger", "index": ALL}, "n_clicks"),
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Input("montant-modal-close", "n_clicks"),
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prevent_initial_call=True,
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)
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def toggle_montant_modal(n_triggers, _close):
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return isinstance(ctx.triggered_id, dict) and any(n_triggers)
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Reference in New Issue
Block a user