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zr8dl!OUuyc@eAOm-ILYNOvU`YR3!nMT6*tyvtPV)>6-&*O6z=>y-_Fj-Pc%`t%KSD zKP0%=Pu@Vs!kfqxv?_hWi)+_5>q-^&tk(s0!7hPD{^*GlAMrv}+yhk^-m~37EtXx1 zH8}%I4sd3^Cbe`cMy`a%#7W3H;W-V}>mh*xFZvuDcbr*P3gX}%C~Y(~-{+YYu{pSh zX&N$@D3M1e!Xz+A?yjqV$BoGOnnxmZ)01}5#u2&n69Y7ZC{m#v<89Mize(^wj?)oa%LegFPcdwa*Em3kYFkCsk3Fo^KeR&U0fIsL+OYJdE5|7S8v zc2$+Mala>ibnYyr;YoxlakhSb4WKD>V8{RXgQmt8`ZdtG;vOA5{i{H~BXV1}YQ-C@ z&4$HKN6L?@(jt>TM=-v!;b+tNzuUx`)z9zTc|#-VuGUMU+Mhy;E1;)x zFQVrZWKmwTj+x$y1UwU<2IC0&eSwimKxpW=;|R&mG9xn3^nddwT<#-uF^+p$9JCqa z$j$X2@@T2G@2*RtU@+$1FVpflK!$WPY&2LQ2pI#G_Lels>^Created with SnapAggregateparse: true +Node Type: Aggregate +Strategy: Hashed +Partial Mode: Simple +Parallel Aware: false +Group Key: ('RPA'::text),a.numero_registre_rpa,a.nom,a.type_residence,a.unites_residence,b.clsc_code,b.region,a.geometry +_serial: 1 +Appendparse: true +Node Type: Append +Parent Relationship: Outer +Parallel Aware: false +Subplans Removed: 0 +total_time: undefined +parent_node: 1 +_serial: 2 +Hash Inner Joinparse: true +Node Type: Hash Join +Parent Relationship: Member +Parallel Aware: false +Join Type: Inner +Inner Unique: false +Hash Cond: (a.numero_registre_rpa = b.numero_registre_rpa) +total_time: undefined +parent_node: 1_1 +_serial: 3 +rpa_detailsparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: rpa_details +Alias: a +total_time: undefined +parent_node: 1_1_1 +_serial: 4 +Hashparse: true +Node Type: Hash +Parent Relationship: Inner +Parallel Aware: false +total_time: undefined +parent_node: 1_1_1 +_serial: 5 +rpa_sommaireparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: rpa_sommaire +Alias: b +total_time: undefined +parent_node: 1_1_1_2 +_serial: 6 +SubQuery Scanparse: true +Node Type: Subquery Scan +Parent Relationship: Member +Parallel Aware: false +Alias: *SELECT* 2 +total_time: undefined +parent_node: 1_1 +_serial: 7 +Hash Inner Joinparse: true +Node Type: Hash Join +Parent Relationship: Subquery +Parallel Aware: false +Join Type: Inner +Inner Unique: false +Hash Cond: (a_1.code_installation = b_1."INSTAL_COD") +total_time: undefined +parent_node: 1_1_2 +_serial: 8 +capacite_services-_installationparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: capacite_services_installation +Alias: a_1 +Filter: ((capacite_service = 'C'::text) AND (mct_capacite_service = 'CHSLD'::text)) +total_time: undefined +parent_node: 1_1_2_1 +_serial: 9 +Hashparse: true +Node Type: Hash +Parent Relationship: Inner +Parallel Aware: false +total_time: undefined +parent_node: 1_1_2_1 +_serial: 10 +installationsparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: installations +Alias: b_1 +total_time: undefined +parent_node: 1_1_2_1_2 +_serial: 11 + \ No newline at end of file diff --git a/pgadmin_sql/explain_plan_1613623951711.svg b/pgadmin_sql/explain_plan_1613623951711.svg new file mode 100644 index 0000000..93e7eb5 --- /dev/null +++ b/pgadmin_sql/explain_plan_1613623951711.svg @@ -0,0 +1,154 @@ +Created with SnapWindow Aggregateparse: true +Node Type: WindowAgg +Parallel Aware: false +_serial: 1 +Sortparse: true +Node Type: Sort +Parent Relationship: Outer +Parallel Aware: false +Sort Key: aa.territoire_clsc +total_time: undefined +parent_node: 1 +_serial: 2 +SubQuery Scanparse: true +Node Type: Subquery Scan +Parent Relationship: Outer +Parallel Aware: false +Alias: aa +total_time: undefined +parent_node: 1_1 +_serial: 3 +Aggregateparse: true +Node Type: Aggregate +Strategy: Hashed +Partial Mode: Simple +Parent Relationship: Subquery +Parallel Aware: false +Group Key: ('RPA'::text),a.numero_registre_rpa,a.nom,a.type_residence,a.unites_residence,b.clsc_code,b.region,(st_transform(a.geometry, 3798)) +total_time: undefined +parent_node: 1_1_1 +_serial: 4 +Appendparse: true +Node Type: Append +Parent Relationship: Outer +Parallel Aware: false +Subplans Removed: 0 +total_time: undefined +parent_node: 1_1_1_1 +_serial: 5 +Hash Inner Joinparse: true +Node Type: Hash Join +Parent Relationship: Member +Parallel Aware: false +Join Type: Inner +Inner Unique: false +Hash Cond: (a.numero_registre_rpa = b.numero_registre_rpa) +total_time: undefined +parent_node: 1_1_1_1_1 +_serial: 6 +rpa_detailsparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: rpa_details +Alias: a +total_time: undefined +parent_node: 1_1_1_1_1_1 +_serial: 7 +Hashparse: true +Node Type: Hash +Parent Relationship: Inner +Parallel Aware: false +total_time: undefined +parent_node: 1_1_1_1_1_1 +_serial: 8 +rpa_sommaireparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: rpa_sommaire +Alias: b +total_time: undefined +parent_node: 1_1_1_1_1_1_2 +_serial: 9 +SubQuery Scanparse: true +Node Type: Subquery Scan +Parent Relationship: Member +Parallel Aware: false +Alias: *SELECT* 2 +total_time: undefined +parent_node: 1_1_1_1_1 +_serial: 10 +Hash Inner Joinparse: true +Node Type: Hash Join +Parent Relationship: Subquery +Parallel Aware: false +Join Type: Inner +Inner Unique: false +Hash Cond: (a_1.code_installation = b_1."INSTAL_COD") +total_time: undefined +parent_node: 1_1_1_1_1_2 +_serial: 11 +Hash Inner Joinparse: true +Node Type: Hash Join +Parent Relationship: Outer +Parallel Aware: false +Join Type: Inner +Inner Unique: true +Hash Cond: ((a_1.code_installation = capacite_services_installation.code_installation) AND (a_1.date_extraction = (max(capacite_services_installation.date_extraction)))) +total_time: undefined +parent_node: 1_1_1_1_1_2_1 +_serial: 12 +capacite_services-_installationparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: capacite_services_installation +Alias: a_1 +Filter: ((capacite_service = 'C'::text) AND (mct_capacite_service = 'CHSLD'::text)) +total_time: undefined +parent_node: 1_1_1_1_1_2_1_1 +_serial: 13 +Hashparse: true +Node Type: Hash +Parent Relationship: Inner +Parallel Aware: false +total_time: undefined +parent_node: 1_1_1_1_1_2_1_1 +_serial: 14 +Aggregateparse: true +Node Type: Aggregate +Strategy: Hashed +Partial Mode: Simple +Parent Relationship: Outer +Parallel Aware: false +Group Key: capacite_services_installation.code_installation +total_time: undefined +parent_node: 1_1_1_1_1_2_1_1_2 +_serial: 15 +capacite_services-_installationparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: capacite_services_installation +Alias: capacite_services_installation +total_time: undefined +parent_node: 1_1_1_1_1_2_1_1_2_1 +_serial: 16 +Hashparse: true +Node Type: Hash +Parent Relationship: Inner +Parallel Aware: false +total_time: undefined +parent_node: 1_1_1_1_1_2_1 +_serial: 17 +installationsparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: installations +Alias: b_1 +total_time: undefined +parent_node: 1_1_1_1_1_2_1_2 +_serial: 18 + \ No newline at end of file diff --git a/pgadmin_sql/explain_plan_1613624140447.svg b/pgadmin_sql/explain_plan_1613624140447.svg new file mode 100644 index 0000000..647ff95 --- /dev/null +++ b/pgadmin_sql/explain_plan_1613624140447.svg @@ -0,0 +1,171 @@ +Created with SnapWindow Aggregateparse: true +Node Type: WindowAgg +Parallel Aware: false +_serial: 1 +Sortparse: true +Node Type: Sort +Parent Relationship: Outer +Parallel Aware: false +Sort Key: aa.territoire_clsc +total_time: undefined +parent_node: 1 +_serial: 2 +SubQuery Scanparse: true +Node Type: Subquery Scan +Parent Relationship: Outer +Parallel Aware: false +Alias: aa +total_time: undefined +parent_node: 1_1 +_serial: 3 +Aggregateparse: true +Node Type: Aggregate +Strategy: Hashed +Partial Mode: Simple +Parent Relationship: Subquery +Parallel Aware: false +Group Key: ('RPA'::text),a.numero_registre_rpa,a.nom,a.type_residence,a.unites_residence,b.clsc_code,b.region,(st_transform(a.geometry, 3798)) +total_time: undefined +parent_node: 1_1_1 +_serial: 4 +Appendparse: true +Node Type: Append +Parent Relationship: Outer +Parallel Aware: false +Subplans Removed: 0 +total_time: undefined +parent_node: 1_1_1_1 +_serial: 5 +Hash Inner Joinparse: true +Node Type: Hash Join +Parent Relationship: Member +Parallel Aware: false +Join Type: Inner +Inner Unique: false +Hash Cond: (a.numero_registre_rpa = b.numero_registre_rpa) +total_time: undefined +parent_node: 1_1_1_1_1 +_serial: 6 +rpa_detailsparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: rpa_details +Alias: a +total_time: undefined +parent_node: 1_1_1_1_1_1 +_serial: 7 +Hashparse: true +Node Type: Hash +Parent Relationship: Inner +Parallel Aware: false +total_time: undefined +parent_node: 1_1_1_1_1_1 +_serial: 8 +rpa_sommaireparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: rpa_sommaire +Alias: b +total_time: undefined +parent_node: 1_1_1_1_1_1_2 +_serial: 9 +SubQuery Scanparse: true +Node Type: Subquery Scan +Parent Relationship: Member +Parallel Aware: false +Alias: *SELECT* 2 +total_time: undefined +parent_node: 1_1_1_1_1 +_serial: 10 +Hash Inner Joinparse: true +Node Type: Hash Join +Parent Relationship: Subquery +Parallel Aware: false +Join Type: Inner +Inner Unique: false +Hash Cond: (b_1."INSTAL_COD" = a_1.code_installation) +total_time: undefined +parent_node: 1_1_1_1_1_2 +_serial: 11 +installationsparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: installations +Alias: b_1 +total_time: undefined +parent_node: 1_1_1_1_1_2_1 +_serial: 12 +Hashparse: true +Node Type: Hash +Parent Relationship: Inner +Parallel Aware: false +total_time: undefined +parent_node: 1_1_1_1_1_2_1 +_serial: 13 +Merge Inner Joinparse: true +Node Type: Merge Join +Parent Relationship: Outer +Parallel Aware: false +Join Type: Inner +Inner Unique: false +Merge Cond: ((a_1.code_installation = a1.code_installation) AND (a_1.date_extraction = a1.date_extraction)) +total_time: undefined +parent_node: 1_1_1_1_1_2_1_2 +_serial: 14 +Sortparse: true +Node Type: Sort +Parent Relationship: Outer +Parallel Aware: false +Sort Key: a_1.code_installation,a_1.date_extraction +total_time: undefined +parent_node: 1_1_1_1_1_2_1_2_1 +_serial: 15 +capacite_services-_installationparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: capacite_services_installation +Alias: a_1 +Filter: ((capacite_service = 'C'::text) AND (mct_capacite_service = 'CHSLD'::text)) +total_time: undefined +parent_node: 1_1_1_1_1_2_1_2_1_1 +_serial: 16 +Sortparse: true +Node Type: Sort +Parent Relationship: Inner +Parallel Aware: false +Sort Key: a1.code_installation,a1.date_extraction +total_time: undefined +parent_node: 1_1_1_1_1_2_1_2_1 +_serial: 17 +SubQuery Scanparse: true +Node Type: Subquery Scan +Parent Relationship: Outer +Parallel Aware: false +Alias: a1 +total_time: undefined +parent_node: 1_1_1_1_1_2_1_2_1_2 +_serial: 18 +Aggregateparse: true +Node Type: Aggregate +Strategy: Hashed +Partial Mode: Simple +Parent Relationship: Subquery +Parallel Aware: false +Group Key: capacite_services_installation.code_installation,capacite_services_installation.capacite_service,capacite_services_installation.mct_capacite_service +total_time: undefined +parent_node: 1_1_1_1_1_2_1_2_1_2_1 +_serial: 19 +capacite_services-_installationparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: capacite_services_installation +Alias: capacite_services_installation +total_time: undefined +parent_node: 1_1_1_1_1_2_1_2_1_2_1_1 +_serial: 20 + \ No newline at end of file diff --git a/pgadmin_sql/explain_plan_1613625117723.svg b/pgadmin_sql/explain_plan_1613625117723.svg new file mode 100644 index 0000000..cd7417e --- /dev/null +++ b/pgadmin_sql/explain_plan_1613625117723.svg @@ -0,0 +1,198 @@ +Created with SnapWindow Aggregateparse: true +Node Type: WindowAgg +Parallel Aware: false +_serial: 1 +Sortparse: true +Node Type: Sort +Parent Relationship: Outer +Parallel Aware: false +Sort Key: aaa.territoire_clsc +total_time: undefined +parent_node: 1 +_serial: 2 +SubQuery Scanparse: true +Node Type: Subquery Scan +Parent Relationship: Outer +Parallel Aware: false +Alias: aaa +total_time: undefined +parent_node: 1_1 +_serial: 3 +Aggregateparse: true +Node Type: Aggregate +Strategy: Sorted +Partial Mode: Simple +Parent Relationship: Subquery +Parallel Aware: false +Group Key: aa.type_milieu,aa.code,aa.nom,aa.statut,aa.territoire_clsc,aa.region,aa.geometry +total_time: undefined +parent_node: 1_1_1 +_serial: 4 +Sortparse: true +Node Type: Sort +Parent Relationship: Outer +Parallel Aware: false +Sort Key: aa.type_milieu,aa.code,aa.nom,aa.statut,aa.territoire_clsc,aa.region,aa.geometry +total_time: undefined +parent_node: 1_1_1_1 +_serial: 5 +SubQuery Scanparse: true +Node Type: Subquery Scan +Parent Relationship: Outer +Parallel Aware: false +Alias: aa +total_time: undefined +parent_node: 1_1_1_1_1 +_serial: 6 +Aggregateparse: true +Node Type: Aggregate +Strategy: Hashed +Partial Mode: Simple +Parent Relationship: Subquery +Parallel Aware: false +Group Key: ('RPA'::text),a.numero_registre_rpa,a.nom,a.type_residence,a.unites_residence,b.clsc_code,b.region,(st_transform(a.geometry, 3798)) +total_time: undefined +parent_node: 1_1_1_1_1_1 +_serial: 7 +Appendparse: true +Node Type: Append +Parent Relationship: Outer +Parallel Aware: false +Subplans Removed: 0 +total_time: undefined +parent_node: 1_1_1_1_1_1_1 +_serial: 8 +Hash Inner Joinparse: true +Node Type: Hash Join +Parent Relationship: Member +Parallel Aware: false +Join Type: Inner +Inner Unique: false +Hash Cond: (a.numero_registre_rpa = b.numero_registre_rpa) +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1 +_serial: 9 +rpa_detailsparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: rpa_details +Alias: a +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_1 +_serial: 10 +Hashparse: true +Node Type: Hash +Parent Relationship: Inner +Parallel Aware: false +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_1 +_serial: 11 +rpa_sommaireparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: rpa_sommaire +Alias: b +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_1_2 +_serial: 12 +SubQuery Scanparse: true +Node Type: Subquery Scan +Parent Relationship: Member +Parallel Aware: false +Alias: *SELECT* 2 +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1 +_serial: 13 +Hash Inner Joinparse: true +Node Type: Hash Join +Parent Relationship: Subquery +Parallel Aware: false +Join Type: Inner +Inner Unique: false +Hash Cond: (b_1."INSTAL_COD" = a_1.code_installation) +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_2 +_serial: 14 +installationsparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: installations +Alias: b_1 +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_2_1 +_serial: 15 +Hashparse: true +Node Type: Hash +Parent Relationship: Inner +Parallel Aware: false +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_2_1 +_serial: 16 +Merge Inner Joinparse: true +Node Type: Merge Join +Parent Relationship: Outer +Parallel Aware: false +Join Type: Inner +Inner Unique: false +Merge Cond: ((a_1.code_installation = a1.code_installation) AND (a_1.date_extraction = a1.date_extraction)) +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_2_1_2 +_serial: 17 +Sortparse: true +Node Type: Sort +Parent Relationship: Outer +Parallel Aware: false +Sort Key: a_1.code_installation,a_1.date_extraction +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_2_1_2_1 +_serial: 18 +capacite_services-_installationparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: capacite_services_installation +Alias: a_1 +Filter: ((capacite_service = 'C'::text) AND (mct_capacite_service = 'CHSLD'::text)) +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_2_1_2_1_1 +_serial: 19 +Sortparse: true +Node Type: Sort +Parent Relationship: Inner +Parallel Aware: false +Sort Key: a1.code_installation,a1.date_extraction +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_2_1_2_1 +_serial: 20 +SubQuery Scanparse: true +Node Type: Subquery Scan +Parent Relationship: Outer +Parallel Aware: false +Alias: a1 +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_2_1_2_1_2 +_serial: 21 +Aggregateparse: true +Node Type: Aggregate +Strategy: Hashed +Partial Mode: Simple +Parent Relationship: Subquery +Parallel Aware: false +Group Key: capacite_services_installation.code_installation,capacite_services_installation.capacite_service,capacite_services_installation.mct_capacite_service +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_2_1_2_1_2_1 +_serial: 22 +capacite_services-_installationparse: true +Node Type: Seq Scan +Parent Relationship: Outer +Parallel Aware: false +Relation Name: capacite_services_installation +Alias: capacite_services_installation +Filter: ((capacite_service = 'C'::text) AND (mct_capacite_service = 'CHSLD'::text)) +total_time: undefined +parent_node: 1_1_1_1_1_1_1_1_2_1_2_1_2_1_1 +_serial: 23 + \ No newline at end of file diff --git a/presentation.md b/presentation.md new file mode 100644 index 0000000..fbed2bc --- /dev/null +++ b/presentation.md @@ -0,0 +1,391 @@ +--- +title: Nettoyage et intégration de données hétéroclites. +author: francois@francoispelletier.org +--- + +## Le projet + +Le projet "cloche" est né suite au dépôt du projet de loi 61 au printemps 2020. Il cherche à établir un diagnostic de notre système de santé pour les personnes âgées et du système d'éducation à l'aide de données ouvertes, afin de suggérer les meilleurs endroits pour construire des nouvelles résidences et écoles. + +Pourquoi : Développer de nouvelles compétences. Aider notre gouvernement qui en arrache. + +## Infrastructure + +- Logiciels : + - Python + - PostgreSQL et PostGIS + - pgAdmin + - RStudio +- J'utilise des conteneurs [Docker](https://www.docker.com/) pour avoir une installation standardisée le plus possible. +- Les conteneurs sont assemblés avec [docker-compose](https://docs.docker.com/compose/) + +Voici mon installation : [docker-compose.yml](https://git.francoispelletier.org/francois/cloche-database/src/branch/master/docker-compose.yml) + +## Acquisition des données + +J'essaie autant que possible de télécharger les données de manière reproductible avec des scripts bash. +Les données sont acquises depuis différents sites du gouvernement, des sites GitHub et aussi via des demandes d'accès à l'information. + +## Capacités des installations - Préparation des données + +**Premier exemple* *: Source : [Capacités des installations](https://www.donneesquebec.ca/recherche/fr/dataset/m02-repartition-des-capacites-et-des-services-autorises-au-permis-par-installation/resource/7038bb19-ad37-49ae-b2d0-aec844d41970) + +Premièrement, on télécharge les données + +```bash +wget https://www.donneesquebec.ca/recherche/fr/dataset/e442a663-e069-4209-a4ba-7bd60f6c5fb4/resource/7038bb19-ad37-49ae-b2d0-aec844d41970/download/gouvernement-ouvert-20200702.csv \ +--output-document=capacite_services_installation_20200702.csv +``` + +Puis, on les lit dans Python avec Pandas + +```python +capacite_services_installation_20200702 =\ +pd.read_csv("/raw/donneesquebec/capacite_services_installation_20200702.csv") +``` + +Voici un exemple de données : + +Code : + +```python +capacite_services_installation_20200702.iloc[0].to_dict() +``` + +Résultat : + +```python +{'RSS_Etablissement' : '01 - Bas-Saint-Laurent', + 'RTS_Etablissement' : '011 - RTS du Bas-Saint-Laurent', + 'Code_Etablissement_(Regroupes_inclus_dans_CISSS/CIUSSS)' : 11045119.0, + 'Nom_Etablissement_(Regroupes_inclus_dans_CISSS/CIUSSS)' : 'CISSS DU BAS-SAINT-LAURENT', + 'Code_Etablissement' : 11045119, + 'Nom_Etablissement' : 'CISSS DU BAS-SAINT-LAURENT', + 'Statut' : 'Public', + 'Mode_financement' : 'Budget', + 'Territoire_CLSC_Installation' : '01161 - La Mitis', + 'Code_Installation' : 51216281, + 'Nom_Installation' : 'SERVICES PROFESSIONNELS - MRC MITIS', + 'MCT-Capacite/Service_Installation' : 'CRDI ', + 'Unite_mesure_Installation' : "Place(s) en centre d'activités de jour", + 'Capacite(C)_Service (S)_Installation' : 'C', + 'Capacite_Installation' : '20', + 'Date_extraction' : 'Produit le 2020-07-02'} +``` + +## Capacités des installations - séparer une colonne avec une expression régulière + +On remarquera que le champ `RSS_Etablissement` contient deux données : le code numérique de la région administrative et le nom de la région. + +Nous allons préférer utiliser un identifiant numérique, alors on sépare le champ en deux colonnes en utilisant la fonction extract qui prend en argument une expression régulière : + +```python +rss_mod = capacite_services_installation_20200702['RSS_Etablissement']\ +.str\ +.extract(r'(?P[0-9]+)\s\-\s(?P.+$)') +``` + +Remarquez la syntaxe `?P<>` qui débute un groupe de capture délimité par des parenthèses. Ceci permet de nommer les groupes, qui deviendront des colonnes d'un DataFrame. + +--- + +**Conseil* *: Pour avoir le détail d'une expression régulière, j'utilise le site regex101.com + +![Site regex101.com, volet gauche](regex101-expression-test.png) +![Site regex101.com, volet droite](regex101-explanation-match.png) + +--- + +On remplace ensuite les valeurs manquantes pour éviter les erreurs : + +```python +rss_mod.fillna(0, inplace=True) +``` + +On importe ces nouvelles colonnes dans le DataFrame principal + +```python +capacite_services_installation_20200702['RSS'] = rss_mod['RSS'].astype(int) +capacite_services_installation_20200702['RSS_nom'] = rss_mod['RSS_nom'] +``` + +On supprime la colonne originale + +```python +del capacite_services_installation_20200702['RSS_Etablissement'] +``` + +## Capacités des installations - nettoyer une colonne + +La colonne "Date extration" contient une date, précédée de la chaine "Produit le ". + +Nous souhaitons convertir ce champ en date. + +On supprime la chaine de caractère superflue avec la méthode `replace`, puis on convertit la colonne au format date avec la fonction `to_datetime` de Pandas, avec les paramètres par défaut, puisque la date est déjà en format [ISO 8601](https://fr.wikipedia.org/wiki/ISO_8601). + +```python +capacite_services_installation_20200702['Date_extraction']=\ +pd.to_datetime(capacite_services_installation_20200702['Date_extraction']\ + .str\ + .replace(r'Produit le ','')) +``` + +--- + +**Conseil* *: Convertissez toujours vos dates en ISO 8601. Vous allez apprendre à aimer les dates ! + +--- + +## Capacités des installations - Caractère vers numérique + +Vous retrouverez parfois des manières originales de marquer les valeurs manquantes. Souvent, celles-ci auront pour conséquence qu'une colonne numérique sera lue comme une colonne caractère. Vous voulez donc la convertir en valeur numérique. + +```python +capacite_services_installation_20200702['Capacite_Installation']=\ +capacite_services_installation_20200702['Capacite_Installation']\ +.str\ +.replace('n.a.','0')\ +.astype(int) +``` + +## Capacités des installations - Chargement des données + +Comme j'écris dans une base de données PostgreSQL, j'utilise le module `psycopg2`. + +Je me suis fait quelques fonctions pour aider + +- [connect](https://git.francoispelletier.org/francois/cloche-database/src/branch/master/notebooks/chargement/psycopg2_conn.py) +- [schema_if_not_exists](https://git.francoispelletier.org/francois/cloche-database/src/branch/master/notebooks/chargement/psycopg2_schema_if_not_exists.py) +- [table_if_not_exists](https://git.francoispelletier.org/francois/cloche-database/src/branch/master/notebooks/chargement/psycopg2_table_if_not_exists.py) + +J'ai aussi utilisé une technique d'importation rapide qui utilise le module de bas niveau `StringIO`, emprunté de la [page GitHub](https://github.com/NaysanSaran/pandas2postgresql) de [Naysan Saran](https://naysan.ca/2020/06/21/pandas-to-postgresql-using-psycopg2-copy_from/). Merci ! + +Pour charger les données dans une table de la base de données PostgreSQL, je crée le DDL à la main + +TODO : générer le string `create_statement` automatiquement ! + +```python +ps_table.table_if_not_exists(conn=conn, + table="msss_gouv_qc_ca.capacite_services_installation", + create_statement=""" + id integer not null, + Code_Etablissement_Reg integer, + Nom_Etablissement_Reg text, + Code_Etablissement integer, + Nom_Etablissement text, + Statut text, + Mode_financement text, + Code_Installation integer, + Nom_Installation text, + MCT_Capacite_Service text, + Unite_mesure_Installation text, + Capacite_Service text, + Capacite_Installation integer, + Date_extraction date, + RSS integer, + RSS_nom text, + RTS integer, + RTS_nom text, + Territoire_CLSC integer, + Territoire_CLSC_nom text + """) +``` + +Ensuite, je charge les données dans la table que j'ai créée + +```python +cfs.copy_from_stringio(conn=conn, + df=capacite_services_installation_20200702, + table="msss_gouv_qc_ca.capacite_services_installation") +``` + +## Effectif du réseau de la santé - Préparation des données + +**Second exemple* *: Source : [Portrait des effectifs du réseau de la santé et des services sociaux](https://www.donneesquebec.ca/recherche/fr/dataset/portrait-des-effectifs-du-reseau-de-la-sante-et-des-services-sociaux) + +Premièrement, on télécharge les données + +```bash +wget https://www.donneesquebec.ca/recherche/fr/dataset/25dabc10-e61a-491c-a0de-98b4d788b4d2/resource/36a2b8b4-899c-408d-92bb-5ae9383eb89c/download/a---donneesparcategoriesetsous-categoriesdepersonnelconcernant.csv \ +--output-document=a_categorie_ss_personnel_etc_emploi.csv +``` + +Puis, on les lit dans Python avec Pandas, en utilisant la colonne `NUMEROTATION` comme index. + +```python +a_categorie_ss_personnel_etc_emploi =\ +pd.read_csv("/raw/msss_gouv_qc_ca/a_categorie_ss_personnel_etc_emploi.csv", + index_col="NUMEROTATION") +``` + +Exemple de donnes : + +Code : + +```python +a_categorie_ss_personnel_etc_emploi.iloc[0].to_dict() +``` + +Résultat : + +```python +{'VARIABLES' : "Nombre de personnes en emploi au 31 mars de l'année", + 'CATEGORIE_PERSONNEL' : '11 - Infirmière', + '2019_TOTAL_EFFECTIF' : '31 296', + '2018_TOTAL_EFFECTIF' : '31 778', + '2017_TOTAL_EFFECTIF' : '32 310', + '2016_TOTAL_EFFECTIF' : '33 434', + '2015_TOTAL_EFFECTIF' : '33 805', + '2014_TOTAL_EFFECTIF' : '35 011', + '2013_TOTAL_EFFECTIF' : '35 114', + '2012_TOTAL_EFFECTIF' : '35 275', + '2011_TOTAL_EFFECTIF' : '35 670', + '2010_TOTAL_EFFECTIF' : '36 087', + 'TITRE_RAPPORT' : 'Données par catégories et sous-catégories de personnel concernant', + 'DATE_PRODUCTION' : '2019-12-01', + 'SOURCE' : 'Banque de données sur les cadres et salariés du réseau de la santé et des services sociaux (R25)', + 'PRODUIT_PAR' : 'Direction générale du personnel réseau et ministériel (DGPRM) du MSSS'} +``` + +## Effectif du réseau de la santé - Correction d'un nom de colonne + +On doit corriger le nom d'une colonne qui contient un tiret + +```python +a_categorie_ss_personnel_etc_emploi = a_categorie_ss_personnel_etc_emploi\ +.rename(columns={"CATEGORIE_SOUS-CATEGIE_PERSONNEL":"CATEGORIE_PERSONNEL"}) +``` + +## Effectif du réseau de la santé - Format large vers format long + +Les données des effectifs sont disposées selon le format "large" dans le fichier CSV, on désire donc les ramener sur le format "long" pour faciliter les traitements futurs en ayant des données normalisées. + +**Conseil* *: La forme normale de Boyce-Codd est la représentation de données la plus courante dans les bases de données relationnelles. C'est un des concepts les plus importants en informatique qui a permis l'essor des bases de données et de la science des données. Vous devriez toujours chercher à stocker vos données sous cette forme. + +```python +a_categorie_ss_personnel_etc_emploi_m = pd.melt(frame=a_categorie_ss_personnel_etc_emploi, + id_vars=['VARIABLES', + 'CATEGORIE_PERSONNEL', + 'TITRE_RAPPORT', + 'DATE_PRODUCTION', + 'SOURCE', + 'PRODUIT_PAR'], + value_vars=['2019_TOTAL_EFFECTIF', + '2018_TOTAL_EFFECTIF', + '2017_TOTAL_EFFECTIF', + '2016_TOTAL_EFFECTIF', + '2015_TOTAL_EFFECTIF', + '2014_TOTAL_EFFECTIF', + '2013_TOTAL_EFFECTIF', + '2012_TOTAL_EFFECTIF', + '2011_TOTAL_EFFECTIF', + '2010_TOTAL_EFFECTIF'], + var_name='ANNEE', + value_name='TOTAL_EFFECTIF' + ) +``` + +On extrait ensuite l'année de la colonne `ANNEE`: + +```python +a_categorie_ss_personnel_etc_emploi_m['ANNEE']=a_categorie_ss_personnel_etc_emploi_m['ANNEE']\ +.str\ +.extract(r'(?P[0-9]+)_TOTAL_EFFECTIF')\ +.astype(int) +``` + +## Éducation - Indices de défavorisation + +Source : [Éducation - Indices de défavorisation](http://www.education.gouv.qc.ca/references/tx-solrtyperecherchepublicationtx-solrpublicationnouveaute/resultats-de-la-recherche/detail/article/indices-de-defavorisation/) + +Téléchargement des données : + +```bash +wget http://www.education.gouv.qc.ca/fileadmin/site_web/documents/PSG/statistiques_info_decisionnelle/Indices-defavorisation-2018-2019.xlsx \ +--output-document=Indices-defavorisation-2018-2019.xlsx +``` + +Nous avons ici affaire à des chiffriers Excel qui contiennent des données qui ne sont pas directement exploitables. Nous allons donc faire du "Excel Mining" avec le module `xlrd` ([Site web](https://xlrd.readthedocs.io/en/latest/)). + +![Capture d'écran du fichier Excel Indices-defavorisation-2018-2019.xlsx](defavorisation-education-excel-mining.png) + +La grosse fonction qui fait tout ! + +TODO : Refactoriser en plusieurs petites fonctions + +```python +def indices_ecoles(loc,periode) : + wb = xlrd.open_workbook(loc) +# Décompte du nombre de feuilles + nb_sheets = wb.nsheets +# Liste pour contenir chacune des écoles + liste_ecoles = [] +# Boucle sur chacune des feuilles (commissions scolaires) + for sheet_no in range(nb_sheets): + + sheet = wb.sheet_by_index(sheet_no) + # Nous faisons l'extraction de certaines métadonnées + meta = { + 'periode':periode, + 'numero_cs':sheet.cell_value(1, 0), + 'nom_cs':sheet.cell_value(1, 1) + } + # On itère ensuite sur chaque ligne pour identifier + # les sections avec les écoles primaires et secondaires + for i in range(sheet.nrows) : + if sheet.cell_value(i, 1) == 'Écoles secondaires': + type_ecole = ['secondaire'] + if sheet.cell_value(i, 1) == 'Écoles primaires': + type_ecole = ['primaire'] + # Le code à 6 chiffres est un code d'école + res = re.search(r'\d{6}', str(sheet.cell_value(i, 0))) + if res != None : + if sheet.cell_value(i, 0) != meta['numero_cs']: + all_values = list(meta.values())+type_ecole+sheet.row_values(i) + all_values = [str(x).strip() for x in all_values] + liste_ecoles.append(all_values) + df_ecoles = pandas.DataFrame(liste_ecoles, + columns=['periode', + 'numero_cs', + 'nom_cs', + 'type_ecole', + 'code_ecole', + 'nom_ecole', + 'indice_seuil_faible_revenu', + 'rang_decile_sfr', + 'indice_milieu_socio_econo', + 'rang_decile_imse', + 'nb_eleves']) + df_ecoles[['numero_cs','code_ecole']] = df_ecoles[['numero_cs','code_ecole']].applymap(lambda x : x.replace(r'.0','')) + + return df_ecoles +``` + +On appelle la fonction + +```python +df_ecoles_2019 = indices_ecoles(loc[2],'2018-2019') +``` + +Et nous avons des données nettoyées ! + +![Données nettoyées pour l'année 2019](defavorisation-education-pandas.png) + +## Pour les curieux + +J'ai fait un web scraping de la base de données K10 du MSSS : [Registre des résidences privées pour aînés](http://k10.pub.msss.rtss.qc.ca/K10accueil.asp) avec [scrapy](https://scrapy.org/). + +- [registre_rpa-1.ipynb](https://git.francoispelletier.org/francois/cloche-database/src/branch/master/notebooks/chargement/registre_rpa-1.ipynb) +- [registre_rpa-2.ipynb](https://git.francoispelletier.org/francois/cloche-database/src/branch/master/notebooks/chargement/registre_rpa-2.ipynb) +- [registre_rpa-3.ipynb](https://git.francoispelletier.org/francois/cloche-database/src/branch/master/notebooks/chargement/registre_rpa-3.ipynb) +- [registre_rpa-4.ipynb](https://git.francoispelletier.org/francois/cloche-database/src/branch/master/notebooks/chargement/registre_rpa-4.ipynb) + +## Conclusion + +Bientôt ... + +- Extraction OCR de fichiers Excel imprimés, faxés puis numérisés (AKA 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