From 335fc31bc96cf5056cfd0088d9481445417e4fca Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Sat, 10 Sep 2016 17:35:46 +0200 Subject: [PATCH 01/14] diff json --- diff_json.py | 78 ++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 78 insertions(+) create mode 100644 diff_json.py diff --git a/diff_json.py b/diff_json.py new file mode 100644 index 0000000..d9cda2a --- /dev/null +++ b/diff_json.py @@ -0,0 +1,78 @@ +# -*- coding: utf-8 -*- +""" +Created on Sat Sep 10 14:31:31 2016 + +@author: aeidelman +""" + +import os +import json + +files = os.listdir('json') +files.sort() +names = [file[:-4] for file in files] + +for k in range(1,len(files) - 1): + file1 = files[k] + f = open('json/' + file1) + v1 = json.load(f) + + file2 = files[k+1] + f = open('json/' + file2) + v2 = json.load(f) + + + + + # difference de keys... + set1 = set(v1) + set2 = set(v2) + dans2_pas_dans1 = set2 - set1 + dans1_pas_dans2 = set1 - set2 + + # la différence entre tous les éléments + differences = list() + for entite in v1.keys(): + if entite in v2.keys(): + dict1 = v1[entite] + dict2 = v2[entite] + + keys1 = set(dict1.keys()) + keys2 = set(dict2.keys()) + + for champs in keys1 & keys2: + value1 = dict1[champs] + value2 = dict2[champs] + if value2 != value1: + differences += [(entite, champs, + value1, value2)] + + for champs in keys2 - keys1: + differences += [(entite, champs, + '', dict2[champs])] + + for champs in keys1 - keys2: + differences += [(entite, champs, + dict1[champs], '')] + + #import pdb + #pdb.set_trace() + + # analyse des différences + import pandas as pd + diff_df = pd.DataFrame(differences) + changes = diff_df[2] + '\n devient \n ' + diff_df[3] + + print(diff_df[0].value_counts().head()) + print(diff_df[1].value_counts()) + + for row in changes.value_counts().head(10).items(): + print('On a {0} changements où \n {1} \n'.format(row[1], row[0])) + + un_pb = 'df/Ministeres_Ministere_de_l_economie_de_l_industrie_et_de_l_emploi' + diff_df[diff_df[3] == un_pb] + + # inversions + inversion = (diff_df[2] + diff_df[3]).isin(diff_df[3] + diff_df[2]) + + From 35517eb00be67c2132aa79804cd3d3a598b895ce Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Fri, 4 Nov 2016 10:59:01 +0100 Subject: [PATCH 02/14] better diff --- diff.py | 105 +++++++++++++++++++++++++++++++++++++++++++++++--------- 1 file changed, 89 insertions(+), 16 deletions(-) diff --git a/diff.py b/diff.py index a1257a4..1692855 100644 --- a/diff.py +++ b/diff.py @@ -4,6 +4,7 @@ Etudie les differences d'une version de l'annuaire à l'autre +TODO: retirer les updates_the de l'analyse, ils redondent """ import os @@ -17,26 +18,98 @@ def load(name): file = os.path.join('csv', name) tab = pd.read_csv(file) - tab.drop('_merge', axis=1, inplace=True) return tab -tab1 = load(name1) -tab2 = load(name2) -merge = tab1.merge(tab2, on = ['index', 'parent'], + +def diff_csv(name1, name2, verbose=True): + ''' effectue la différence des deux csv + retourne les lignes pour lesquelles les informations + dans ''' + tab1 = load(name1) + tab2 = load(name2) + + merge = tab1.merge(tab2, on = ['index', 'parent'], indicator=True, how='outer') - -merge._merge.value_counts() + + if verbose: + print(merge._merge.value_counts()) + + cols_x = [col for col in merge.columns if col[-2:] == '_x'] + cols_y = [col for col in merge.columns if col[-2:] == '_y'] + + merge_y = merge[cols_y].rename(columns=dict(x for x in zip(cols_y, cols_x))) + similar = merge[cols_x] == merge_y + differents = ~similar.all(axis=1) + if verbose: + print("il y a {} differences sur {} entités".format( + sum(differents), + len(merge)) + ) + + if verbose: + print((~similar).sum()) + + diff = merge[differents] + diff[cols_x] = diff[cols_x].mask(similar) + diff[cols_y] = diff[cols_y].mask(similar) + diff[cols_x] += ' -> ' + merge_y[differents] + return diff[['index', 'parent'] + cols_x] -diff1 = merge[merge._merge != 'both'] -matchees = merge[merge._merge == 'both'] -cols_1 = [col for col in matchees.columns if col[-2:] == '_x'] +def revient_a_la_valeur_initiale(name1, name2, name3): + ''' regarde si les valeurs sont les mêmes dans name1 et name3 alors + qu'elles sont différentes dans name2 + ''' + tab1 = load(name1) + tab2 = load(name2) + tab3 = load(name2) + + merge = tab1.merge(tab2, on = ['index', 'parent']). \ + merge(tab3, on = ['index', 'parent']) + -del matchees['_merge'] -matchees.fillna('nan', inplace=True) -for col in cols_1: - nb_diff = sum(matchees[col] != matchees[col[:-1] + 'y']) - if nb_diff > 0: - print(col) - print(nb_diff) \ No newline at end of file + cols_x = [col for col in merge.columns if col[-2:] == '_x'] + cols_y = [col for col in merge.columns if col[-2:] == '_y'] + cols_z = [col[:-2] for col in cols_x ] + + merge_y = merge[cols_y].rename(columns=dict(x for x in zip(cols_y, cols_x))) + merge_z = merge[cols_z].rename(columns=dict(x for x in zip(cols_z, cols_x))) + similar_x_z = merge[cols_x] == merge_z + different_x_y = merge[cols_x] != merge_y + similar_y_z = merge_y == merge_z + return similar_x_z & different_x_y +#matchees = merge[merge._merge == 'both'] +#del matchees['_merge'] +# +#matchees.fillna('nan', inplace=True) +# +# +#return differents + +if __name__ == '__main__': + test = revient_a_la_valeur_initiale('annuaire_20161019.csv', + 'annuaire_20161026.csv', + 'annuaire_20161102.csv') + + differents1 = diff_csv('annuaire_20161022.csv', 'annuaire_20161026.csv') + differents2 = diff_csv('annuaire_20161026.csv', 'annuaire_20161102.csv') + differents3 = diff_csv('annuaire_20161022.csv', 'annuaire_20161102.csv') + + for col in differents1.columns: + if differents1[col].nunique() > 1: + print(differents1[col].value_counts()) + print(differents2[col].value_counts()) + print('\n') + + +#Il y a des choses étonnantes dans les adresses des sites web par exemple. +#http://www.defense.gouv.fr/dga -> http://www.ixarm.com 39 +#http://www.education.gouv.fr -> http://www.enseignementsup-recherche.gouv.fr 37 +#http://www.enseignementsup-recherche.gouv.fr -> http://www.education.gouv.fr 35 +#http://www.ixarm.com -> http://www.defense.gouv.fr/dga 31 +# +#http://www.education.gouv.fr -> http://www.enseignementsup-recherche.gouv.fr 40 +#http://www.ixarm.com -> http://www.defense.gouv.fr/dga 38 +#http://www.defense.gouv.fr/dga -> http://www.ixarm.com 35 +#http://www.enseignementsup-recherche.gouv.fr -> http://www.education.gouv.fr 34 \ No newline at end of file From 5667d2258155492b8aa746596a52e5c8ba88be70 Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Fri, 4 Nov 2016 11:28:40 +0100 Subject: [PATCH 03/14] drop option in diff --- diff.py | 44 ++++++++++++++++++++++++++++++-------------- 1 file changed, 30 insertions(+), 14 deletions(-) diff --git a/diff.py b/diff.py index 1692855..437a60a 100644 --- a/diff.py +++ b/diff.py @@ -15,19 +15,24 @@ name1, name2 = files[:2] -def load(name): +def load(name, drop=None): file = os.path.join('csv', name) tab = pd.read_csv(file) + if drop is not None: + assert isinstance(drop, list) + assert all([x in tab.columns for x in drop]) + to_keep = [x for x in tab.columns if x not in drop] + tab = tab[to_keep] return tab -def diff_csv(name1, name2, verbose=True): +def diff_csv(name1, name2, verbose=True, drop=None): ''' effectue la différence des deux csv retourne les lignes pour lesquelles les informations dans ''' - tab1 = load(name1) - tab2 = load(name2) + tab1 = load(name1, drop) + tab2 = load(name2, drop) merge = tab1.merge(tab2, on = ['index', 'parent'], indicator=True, how='outer') @@ -57,13 +62,13 @@ def diff_csv(name1, name2, verbose=True): return diff[['index', 'parent'] + cols_x] -def revient_a_la_valeur_initiale(name1, name2, name3): +def revient_a_la_valeur_initiale(name1, name2, name3, drop=None): ''' regarde si les valeurs sont les mêmes dans name1 et name3 alors qu'elles sont différentes dans name2 ''' - tab1 = load(name1) - tab2 = load(name2) - tab3 = load(name2) + tab1 = load(name1, drop) + tab2 = load(name2, drop) + tab3 = load(name2, drop) merge = tab1.merge(tab2, on = ['index', 'parent']). \ merge(tab3, on = ['index', 'parent']) @@ -91,16 +96,27 @@ def revient_a_la_valeur_initiale(name1, name2, name3): test = revient_a_la_valeur_initiale('annuaire_20161019.csv', 'annuaire_20161026.csv', 'annuaire_20161102.csv') - - differents1 = diff_csv('annuaire_20161022.csv', 'annuaire_20161026.csv') - differents2 = diff_csv('annuaire_20161026.csv', 'annuaire_20161102.csv') - differents3 = diff_csv('annuaire_20161022.csv', 'annuaire_20161102.csv') + basic_drop = ['http://www.mondeca.com/system/basicontology#updated_the', + 'an/telecopie', 'an/telephone'] + differents1 = diff_csv('annuaire_20161022.csv', 'annuaire_20161026.csv', + drop = basic_drop) + differents2 = diff_csv('annuaire_20161026.csv', 'annuaire_20161102.csv', + drop = basic_drop) + differents3 = diff_csv('annuaire_20161022.csv', 'annuaire_20161102.csv', + drop = basic_drop) for col in differents1.columns: if differents1[col].nunique() > 1: - print(differents1[col].value_counts()) - print(differents2[col].value_counts()) + print(differents1[col].value_counts().head()) + print(differents2[col].value_counts().head()) print('\n') + + for tab in [differents1, differents2, differents3]: + print('en tout on a {} changement'.format(len(tab))) + changements = tab.notnull().sum() + changements.drop(['parent', 'index'], inplace=True) + changements.sort_values(ascending=False, inplace=True) + print(changements.head(6)) #Il y a des choses étonnantes dans les adresses des sites web par exemple. From 4c280fd7cd01b11ad373005170d4eba7c153eb40 Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Mon, 7 Nov 2016 17:47:17 +0100 Subject: [PATCH 04/14] mention enrich data with SIRENE --- README.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/README.md b/README.md index be8f9a0..64f5799 100644 --- a/README.md +++ b/README.md @@ -19,3 +19,7 @@ Toute contribution est la bienvenue ! Je voudrais aussi permettre de visualiser les évolutions : quelles organisations changent et quand ? Pour cela, il faudrait un historique des données. + +* Ajouter les données de la base SIRENE pour enrichir la base. +Un [exemple](http://data.enseignementsup-recherche.gouv.fr/pages/explorer/?sort=modified&refine.publisher=Minist%C3%A8re%20de%20l%27%C3%89ducation%20nationale,%20de%20l%27Enseignement%20sup%C3%A9rieur%20et%20de%20la%20Recherche&q=siret) d'administration avec un siret (à étudier). +Voir comment les données sont dans le fichier SIRENE. Est-ce que l'on peut faire un lien avec les données From 0a605b731e75902851efa6b59ca5b69d60fbe3f9 Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Thu, 10 Nov 2016 22:33:34 +0100 Subject: [PATCH 05/14] init SIRENE --- SIRENE/README.md | 32 ++++++++++++++++++++++++++++++++ SIRENE/read_Sirene.py | 39 +++++++++++++++++++++++++++++++++++++++ 2 files changed, 71 insertions(+) create mode 100644 SIRENE/README.md create mode 100644 SIRENE/read_Sirene.py diff --git a/SIRENE/README.md b/SIRENE/README.md new file mode 100644 index 0000000..6468542 --- /dev/null +++ b/SIRENE/README.md @@ -0,0 +1,32 @@ +Ce dossier rassemble les informations sur les +service public telles que contenu dans la base Sirene. + +Projet +==== + +Relier les entrées de la base Sirene avec les données de l'annuaire de +l'administration publiées. Sont-elles cohérentes ? Lesquelles font +référence ? + + +Faisabilité +==== + +Les données existent. En effet sur [cette page](http://www.insee.fr/fr/methodes/default.asp?page=definitions/sirene-secteur-public.htm) du site de l'Insee, on trouve le passage suivant : +Ou encore mieux [là](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/agregatnaf2008/agregatnaf2008.htm) + + C'est en 1983 que la mission d'immatriculation au répertoire a été étendue au secteur public. L'unité SIREN est appelée organisme lorsqu'elle relève du secteur non marchand. Elle couvre donc normalement les personnes morales que constituent l'État, les collectivités territoriales et les établissements publics. + + Toutefois, certaines institutions et certains services de l'État, bien que non dotés de la personnalité juridique, sont identifiés comme organismes lorsqu'ils jouissent d'une « quasi-personnalité juridique ». C'est le cas des autorités constitutionnelles, des autorités administratives indépendantes, des ministères, des directions d'administration centrale ainsi que des services extérieurs, territorialisés ou non. + L'unité SIRET de type établissement correspond soit à une implantation géographique distincte où s'exerce une activité, soit à une implantation géographique pour laquelle il existe un budget annexe. Ceci signifie que, contrairement au secteur privé, à une même adresse il peut exister plusieurs numéros SIRET pour un même numéro SIREN. + + + +Méthode +==== + +Comment repérer les administrations publiques ? +Plusieurs idées : + +* utiliser le code naf et en particulier [celles commençant par 84](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/naf2008/n1_o.htm) +* utiliser [la nomenclature des catégories juridiques](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/cj/cj-arbre.htm) diff --git a/SIRENE/read_Sirene.py b/SIRENE/read_Sirene.py new file mode 100644 index 0000000..f0bf645 --- /dev/null +++ b/SIRENE/read_Sirene.py @@ -0,0 +1,39 @@ +# -*- coding: utf-8 -*- +""" +@author: aeidelman +""" + +import os +import pandas as pd + +path = '/home/sgmap/data/SIRENE' + +# avantage +path_file = os.path.join(path, + 'sirc-266_266_13705_201606_L_P_20161010_121909418-secondtry.csv') + +tab = pd.read_csv(path_file, sep=';', nrows=1000, + encoding='cp1252' +# usecols = categorical_vars + ['avant_montant_ttc'] + ) + +assert all(tab.APET700.str.len() == 5) +public = tab[tab.APET700.str[:2] == '84'] +print(len(public)) + +xxx + +#av['year'] = av['avant_date_signature'].str[6:] +iter_csv = pd.read_csv(path_file, sep=';', + encoding='cp1252', + iterator=True, + chunksize=100000) + +df = pd.concat([tab[tab.APET700.str[:2] == '84'] + for tab in iter_csv]) + +path_output = os.path.join(path, 'sirene84.csv') +df.to_csv(path_output, sep=';', + encoding='cp1252', + iterator=True, + index=False) \ No newline at end of file From f78cddb8aacde6293a1ac95970d3242dce6e6aef Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Mon, 14 Nov 2016 16:11:43 +0100 Subject: [PATCH 06/14] Update README.md --- SIRENE/README.md | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/SIRENE/README.md b/SIRENE/README.md index 6468542..f69a4d2 100644 --- a/SIRENE/README.md +++ b/SIRENE/README.md @@ -1,24 +1,24 @@ Ce dossier rassemble les informations sur les service public telles que contenu dans la base Sirene. -Projet -==== +# Projet -Relier les entrées de la base Sirene avec les données de l'annuaire de -l'administration publiées. Sont-elles cohérentes ? Lesquelles font -référence ? +La base Sirene est une donnée de référence. Ce n'est pas pour autant qu'elle se suffit à elle-même. En effet, elle a des liens avec au moins deux autres données de référence : la **base adresses nationale** et l'**annuaire des services publics**. +Dans ce repo nous nous intéresserons essentiellement au lien entre la base SIRENE et l'annuaire des services publics. + +Relier les entrées de la base Sirene avec les données de l'annuaire de l'administration publiées. Sont-elles cohérentes entre elles ? Lesquelles font référence ? Comment une modification de l'une des deux bases doit se propager à l'autre ? -Faisabilité -==== + +## Faisabilité Les données existent. En effet sur [cette page](http://www.insee.fr/fr/methodes/default.asp?page=definitions/sirene-secteur-public.htm) du site de l'Insee, on trouve le passage suivant : Ou encore mieux [là](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/agregatnaf2008/agregatnaf2008.htm) - C'est en 1983 que la mission d'immatriculation au répertoire a été étendue au secteur public. L'unité SIREN est appelée organisme lorsqu'elle relève du secteur non marchand. Elle couvre donc normalement les personnes morales que constituent l'État, les collectivités territoriales et les établissements publics. - - Toutefois, certaines institutions et certains services de l'État, bien que non dotés de la personnalité juridique, sont identifiés comme organismes lorsqu'ils jouissent d'une « quasi-personnalité juridique ». C'est le cas des autorités constitutionnelles, des autorités administratives indépendantes, des ministères, des directions d'administration centrale ainsi que des services extérieurs, territorialisés ou non. - L'unité SIRET de type établissement correspond soit à une implantation géographique distincte où s'exerce une activité, soit à une implantation géographique pour laquelle il existe un budget annexe. Ceci signifie que, contrairement au secteur privé, à une même adresse il peut exister plusieurs numéros SIRET pour un même numéro SIREN. +>C'est en 1983 que la mission d'immatriculation au répertoire a été étendue au secteur public. L'unité SIREN est appelée organisme lorsqu'elle relève du secteur non marchand. Elle couvre donc normalement les personnes morales que constituent l'État, les collectivités territoriales et les établissements publics. +> +>Toutefois, certaines institutions et certains services de l'État, bien que non dotés de la personnalité juridique, sont identifiés comme organismes lorsqu'ils jouissent d'une « quasi-personnalité juridique ». C'est le cas des autorités constitutionnelles, des autorités administratives indépendantes, des ministères, des directions d'administration centrale ainsi que des services extérieurs, territorialisés ou non. +>L'unité SIRET de type établissement correspond soit à une implantation géographique distincte où s'exerce une activité, soit à une implantation géographique pour laquelle il existe un budget annexe. Ceci signifie que, contrairement au secteur privé, à une même adresse il peut exister plusieurs numéros SIRET pour un même numéro SIREN. @@ -28,5 +28,5 @@ Méthode Comment repérer les administrations publiques ? Plusieurs idées : -* utiliser le code naf et en particulier [celles commençant par 84](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/naf2008/n1_o.htm) -* utiliser [la nomenclature des catégories juridiques](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/cj/cj-arbre.htm) +*utiliser le code naf et en particulier [celles commençant par 84](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/naf2008/n1_o.htm) +*utiliser [la nomenclature des catégories juridiques](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/cj/cj-arbre.htm) From 1df1ee8be0287bcdad6a3ebb2f61118cab579b0e Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Mon, 14 Nov 2016 16:18:49 +0100 Subject: [PATCH 07/14] Update README.md --- SIRENE/README.md | 28 +++++++++++++++++++++++----- 1 file changed, 23 insertions(+), 5 deletions(-) diff --git a/SIRENE/README.md b/SIRENE/README.md index f69a4d2..0b2a866 100644 --- a/SIRENE/README.md +++ b/SIRENE/README.md @@ -18,15 +18,33 @@ Ou encore mieux [là](http://www.insee.fr/fr/methodes/default.asp?page=nomenclat >C'est en 1983 que la mission d'immatriculation au répertoire a été étendue au secteur public. L'unité SIREN est appelée organisme lorsqu'elle relève du secteur non marchand. Elle couvre donc normalement les personnes morales que constituent l'État, les collectivités territoriales et les établissements publics. > >Toutefois, certaines institutions et certains services de l'État, bien que non dotés de la personnalité juridique, sont identifiés comme organismes lorsqu'ils jouissent d'une « quasi-personnalité juridique ». C'est le cas des autorités constitutionnelles, des autorités administratives indépendantes, des ministères, des directions d'administration centrale ainsi que des services extérieurs, territorialisés ou non. +> >L'unité SIRET de type établissement correspond soit à une implantation géographique distincte où s'exerce une activité, soit à une implantation géographique pour laquelle il existe un budget annexe. Ceci signifie que, contrairement au secteur privé, à une même adresse il peut exister plusieurs numéros SIRET pour un même numéro SIREN. -Méthode -==== +## Méthode + +### Comment repérer les administrations publiques dans la base Sirene ? -Comment repérer les administrations publiques ? Plusieurs idées : -*utiliser le code naf et en particulier [celles commençant par 84](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/naf2008/n1_o.htm) -*utiliser [la nomenclature des catégories juridiques](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/cj/cj-arbre.htm) +* utiliser le code naf et en particulier [celles commençant par 84](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/naf2008/n1_o.htm) +* utiliser [la nomenclature des catégories juridiques](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/cj/cj-arbre.htm) + +### Comment faire le lien entre SIRENE et Annuaire ? + +La meilleure idée semble d'utiliser les noms des entités. On remarquera tout de suite que les formats sont différents (majuscules non accentuées dans un cas, simili Camel Case accentué dans l'autre). + +Est-ce que les adresses peuvent aider ? + +D'autres idées ? + +### Quel est le meilleure agencement des données de SIRENE et de l'annuaire ? + +Des questions sont ouvertes : +* Comment gère-t-on les changements de noms ? +* Que faire des incohérences actuelles (s'il y en a). +* Quelle(s) adresse(s) doit-être conservée(s) ? Celle de l'annuaire ? Celle de SIRENE ? +* ... + From 207b60a5aa6dbaf9fc7e0d420867e2cbeb5128d0 Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Mon, 14 Nov 2016 16:20:38 +0100 Subject: [PATCH 08/14] Update README.md --- SIRENE/README.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/SIRENE/README.md b/SIRENE/README.md index 0b2a866..360aaf7 100644 --- a/SIRENE/README.md +++ b/SIRENE/README.md @@ -13,7 +13,6 @@ Relier les entrées de la base Sirene avec les données de l'annuaire de l'admin ## Faisabilité Les données existent. En effet sur [cette page](http://www.insee.fr/fr/methodes/default.asp?page=definitions/sirene-secteur-public.htm) du site de l'Insee, on trouve le passage suivant : -Ou encore mieux [là](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/agregatnaf2008/agregatnaf2008.htm) >C'est en 1983 que la mission d'immatriculation au répertoire a été étendue au secteur public. L'unité SIREN est appelée organisme lorsqu'elle relève du secteur non marchand. Elle couvre donc normalement les personnes morales que constituent l'État, les collectivités territoriales et les établissements publics. > @@ -29,7 +28,7 @@ Ou encore mieux [là](http://www.insee.fr/fr/methodes/default.asp?page=nomenclat Plusieurs idées : -* utiliser le code naf et en particulier [celles commençant par 84](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/naf2008/n1_o.htm) +* utiliser le code [naf](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/agregatnaf2008/agregatnaf2008.htm) et en particulier [celles commençant par 84](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/naf2008/n1_o.htm) * utiliser [la nomenclature des catégories juridiques](http://www.insee.fr/fr/methodes/default.asp?page=nomenclatures/cj/cj-arbre.htm) ### Comment faire le lien entre SIRENE et Annuaire ? From 2a96b893e68c0735153dcf061bf7bf77dc973721 Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Tue, 15 Nov 2016 09:42:23 +0100 Subject: [PATCH 09/14] Update README.md --- README.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 64f5799..3d59913 100644 --- a/README.md +++ b/README.md @@ -21,5 +21,7 @@ Je voudrais aussi permettre de visualiser les évolutions : quelles organisation Pour cela, il faudrait un historique des données. * Ajouter les données de la base SIRENE pour enrichir la base. -Un [exemple](http://data.enseignementsup-recherche.gouv.fr/pages/explorer/?sort=modified&refine.publisher=Minist%C3%A8re%20de%20l%27%C3%89ducation%20nationale,%20de%20l%27Enseignement%20sup%C3%A9rieur%20et%20de%20la%20Recherche&q=siret) d'administration avec un siret (à étudier). -Voir comment les données sont dans le fichier SIRENE. Est-ce que l'on peut faire un lien avec les données + +On trouve ici un [exemple](http://data.enseignementsup-recherche.gouv.fr/pages/explorer/?sort=modified&refine.publisher=Minist%C3%A8re%20de%20l%27%C3%89ducation%20nationale,%20de%20l%27Enseignement%20sup%C3%A9rieur%20et%20de%20la%20Recherche&q=siret) d'administrations avec un siret (à étudier). + +Voir comment les données sont dans le fichier SIRENE. Est-ce que l'on peut faire un lien avec les données. From 57ac326cd5194245ae816ab5572c0e412ed6d9d2 Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Tue, 15 Nov 2016 10:02:03 +0100 Subject: [PATCH 10/14] Update README.md --- SIRENE/README.md | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/SIRENE/README.md b/SIRENE/README.md index 360aaf7..3308b0f 100644 --- a/SIRENE/README.md +++ b/SIRENE/README.md @@ -47,3 +47,10 @@ Des questions sont ouvertes : * Quelle(s) adresse(s) doit-être conservée(s) ? Celle de l'annuaire ? Celle de SIRENE ? * ... + +### Autres choses + +* Regarder les SIREN disparu des entités publiques (mais on a seulement les établissements actifs). +* Lorsqu'on a plusieurs établissements, est-ce que cela correspond à une arborescence de l'annuaire ? + + From a3506510c12c90a2ffbabb6808972cca4b55b95c Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Tue, 15 Nov 2016 10:12:58 +0100 Subject: [PATCH 11/14] use NJ --- SIRENE/read_Sirene.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/SIRENE/read_Sirene.py b/SIRENE/read_Sirene.py index f0bf645..d5ef6e1 100644 --- a/SIRENE/read_Sirene.py +++ b/SIRENE/read_Sirene.py @@ -12,16 +12,16 @@ path_file = os.path.join(path, 'sirc-266_266_13705_201606_L_P_20161010_121909418-secondtry.csv') -tab = pd.read_csv(path_file, sep=';', nrows=1000, - encoding='cp1252' +tab = pd.read_csv(path_file, sep=';', nrows=100000, + encoding='cp1252', #iso-8859-15 # usecols = categorical_vars + ['avant_montant_ttc'] ) assert all(tab.APET700.str.len() == 5) -public = tab[tab.APET700.str[:2] == '84'] -print(len(public)) -xxx +# public = tab[tab['NJ'].astype(str).str[0] == '7'] +# print(len(public)) + #av['year'] = av['avant_date_signature'].str[6:] iter_csv = pd.read_csv(path_file, sep=';', @@ -29,10 +29,10 @@ iterator=True, chunksize=100000) -df = pd.concat([tab[tab.APET700.str[:2] == '84'] +df = pd.concat([tab[tab['NJ'].astype(str).str[0] == '7'] for tab in iter_csv]) -path_output = os.path.join(path, 'sirene84.csv') +path_output = os.path.join(path, 'sirene_NJ_7.csv') df.to_csv(path_output, sep=';', encoding='cp1252', iterator=True, From 666ae01b9c11f862e1b956a1bd6e4e81eada80e8 Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Tue, 15 Nov 2016 11:33:05 +0100 Subject: [PATCH 12/14] Update README.md --- SIRENE/README.md | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/SIRENE/README.md b/SIRENE/README.md index 3308b0f..40890cd 100644 --- a/SIRENE/README.md +++ b/SIRENE/README.md @@ -54,3 +54,18 @@ Des questions sont ouvertes : * Lorsqu'on a plusieurs établissements, est-ce que cela correspond à une arborescence de l'annuaire ? +## Notes: + +### Mise à jour des données de l'administration dans SIRENE. + +Il y a trois fonctions publiques : +* Hospitalière : on essaie d'être cohérent avec FINESS (on ne rentre pas d'unité dans SIRENE qui n'a pas de numéro Finess). Il y a parfois plusieurs lignes quand il y a plusieurs lignes dans FINESS quand il y a plusieurs services mais pas dans SIRENE. +* Les collectivités territoriales : il y a des obligations fortes pour qu'elles utilisent SIREN, SIRET parce qu'elles emploient et passent des contrats. Les prefectures envoient les infos. Pas de gestions automatiques. +* La Dila (a priori) devrait transmettre automatiquement mais ça se fait mal. Rermarque: tout le monde doit avoir un SIREN/SIRET pour utiliser chorus. +Les services déconcentrés, c'est soit les prefectures, soit les administrations elle-même. + +Dans la fonction publique d'Etat, la personnalité juridique c'est l'Etat donc dans SIRENE, c'est par convention qu'on attribue à des SIREN qui va à des ordonnateurs. + +Les infos récupérées par l'Insee pour la base SIRENE, c'est le Nom, l'adresse, le ministère de tutelle. + + From 919a75f126f481ecd4345f9db11c4f12776734d8 Mon Sep 17 00:00:00 2001 From: AlexisEidelman Date: Wed, 16 Nov 2016 18:09:30 +0100 Subject: [PATCH 13/14] fin hackathon --- SIRENE/read_Sirene.py | 4 +- diff.py | 94 +++++++++++++++++++++++-------------------- load.py | 42 +++++++++++++++++++ 3 files changed, 94 insertions(+), 46 deletions(-) create mode 100644 load.py diff --git a/SIRENE/read_Sirene.py b/SIRENE/read_Sirene.py index d5ef6e1..858a705 100644 --- a/SIRENE/read_Sirene.py +++ b/SIRENE/read_Sirene.py @@ -29,10 +29,10 @@ iterator=True, chunksize=100000) -df = pd.concat([tab[tab['NJ'].astype(str).str[0] == '7'] +df = pd.concat([tab[tab['NJ'].astype(str).str[0].isin(['4','7'])] for tab in iter_csv]) -path_output = os.path.join(path, 'sirene_NJ_7.csv') +path_output = os.path.join(path, 'sirene_NJ_4_et_7.csv') df.to_csv(path_output, sep=';', encoding='cp1252', iterator=True, diff --git a/diff.py b/diff.py index 437a60a..3ee260b 100644 --- a/diff.py +++ b/diff.py @@ -10,29 +10,15 @@ import os import pandas as pd -files = os.listdir('csv') -files.sort() +from load import load_csv -name1, name2 = files[:2] -def load(name, drop=None): - file = os.path.join('csv', name) - tab = pd.read_csv(file) - if drop is not None: - assert isinstance(drop, list) - assert all([x in tab.columns for x in drop]) - to_keep = [x for x in tab.columns if x not in drop] - tab = tab[to_keep] - return tab - - - -def diff_csv(name1, name2, verbose=True, drop=None): +def diff_csv(name1, name2, verbose=True, keep=None, drop=None): ''' effectue la différence des deux csv retourne les lignes pour lesquelles les informations dans ''' - tab1 = load(name1, drop) - tab2 = load(name2, drop) + tab1 = load_csv(name1, drop, keep) + tab2 = load_csv(name2, drop, keep) merge = tab1.merge(tab2, on = ['index', 'parent'], indicator=True, how='outer') @@ -59,16 +45,16 @@ def diff_csv(name1, name2, verbose=True, drop=None): diff[cols_x] = diff[cols_x].mask(similar) diff[cols_y] = diff[cols_y].mask(similar) diff[cols_x] += ' -> ' + merge_y[differents] - return diff[['index', 'parent'] + cols_x] + return diff[['index', 'parent'] + cols_x + ['_merge']] -def revient_a_la_valeur_initiale(name1, name2, name3, drop=None): +def revient_a_la_valeur_initiale(name1, name2, name3, keep=None, drop=None): ''' regarde si les valeurs sont les mêmes dans name1 et name3 alors qu'elles sont différentes dans name2 ''' - tab1 = load(name1, drop) - tab2 = load(name2, drop) - tab3 = load(name2, drop) + tab1 = load_csv(name1, drop, keep) + tab2 = load_csv(name2, drop, keep) + tab3 = load_csv(name2, drop, keep) merge = tab1.merge(tab2, on = ['index', 'parent']). \ merge(tab3, on = ['index', 'parent']) @@ -93,32 +79,52 @@ def revient_a_la_valeur_initiale(name1, name2, name3, drop=None): #return differents if __name__ == '__main__': - test = revient_a_la_valeur_initiale('annuaire_20161019.csv', - 'annuaire_20161026.csv', - 'annuaire_20161102.csv') +# test = revient_a_la_valeur_initiale('annuaire_20161019.csv', +# 'annuaire_20161022.csv', +# 'annuaire_20161026.csv') +# basic_drop = ['http://www.mondeca.com/system/basicontology#updated_the', - 'an/telecopie', 'an/telephone'] + 'an/telecopie', 'an/telephone'] + keep_for_sirene = ['index', 'parent', + 'an/adressePhysiqueCodePostal', + 'an/adressePhysiqueVille', + 'http://www.w3.org/2000/01/rdf-schema#label', + ] differents1 = diff_csv('annuaire_20161022.csv', 'annuaire_20161026.csv', - drop = basic_drop) + keep=keep_for_sirene) differents2 = diff_csv('annuaire_20161026.csv', 'annuaire_20161102.csv', - drop = basic_drop) + keep=keep_for_sirene) differents3 = diff_csv('annuaire_20161022.csv', 'annuaire_20161102.csv', - drop = basic_drop) + keep=keep_for_sirene) + +# for col in differents3.columns: +# if differents1[col].nunique() > 5: +# print(differents1[col].value_counts().head()) +# print(differents2[col].value_counts().head()) +# print('\n') +# +# for tab in [differents1, differents2, differents3]: +# print('en tout on a {} changement'.format(len(tab))) +# changements = tab.notnull().sum() +# changements.drop(['parent', 'index'], inplace=True) +# changements.sort_values(ascending=False, inplace=True) +# print(changements.head(7)) + + diff_6_mois = diff_csv('annuaire_20160702.csv', 'annuaire_20161112.csv', + keep=keep_for_sirene) + both = diff_6_mois[diff_6_mois._merge == 'both'] + diff_label = both2['http://www.w3.org/2000/01/rdf-schema#label_x'] + diff_label = diff_label[diff_label.notnull()] + + result = '' + for changement in diff_label.values: + chgt = changement + chgt = chgt.replace('->','\n \t devient \n') + result += chgt + '\n --- \n' + + with open('chgt_noms_matcheds.txt', 'w') as f: + f.write(result) - for col in differents1.columns: - if differents1[col].nunique() > 1: - print(differents1[col].value_counts().head()) - print(differents2[col].value_counts().head()) - print('\n') - - for tab in [differents1, differents2, differents3]: - print('en tout on a {} changement'.format(len(tab))) - changements = tab.notnull().sum() - changements.drop(['parent', 'index'], inplace=True) - changements.sort_values(ascending=False, inplace=True) - print(changements.head(6)) - - #Il y a des choses étonnantes dans les adresses des sites web par exemple. #http://www.defense.gouv.fr/dga -> http://www.ixarm.com 39 #http://www.education.gouv.fr -> http://www.enseignementsup-recherche.gouv.fr 37 diff --git a/load.py b/load.py new file mode 100644 index 0000000..aebfa6e --- /dev/null +++ b/load.py @@ -0,0 +1,42 @@ +# -*- coding: utf-8 -*- +""" +Created on Sat Nov 5 18:29:54 2016 + +@author: aeidelman +""" + +import os +import inspect +import pandas as pd + +currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))) + +def load_csv(name, drop=None, keep=None): + file = os.path.join(currentdir, 'csv', name) + tab = pd.read_csv(file) + if drop is not None: + assert keep is None + assert isinstance(drop, list) + assert all([x in tab.columns for x in drop]) + to_keep = [x for x in tab.columns if x not in drop] + tab = tab[to_keep] + + if keep is not None: + assert drop is None + assert isinstance(keep, list) + assert all([x in tab.columns for x in keep]) + tab = tab[keep] + + return tab + +if __name__ == '__main__': + files = os.listdir('csv') + files.sort() + name1, name2 = files[:2] + test1 = load_csv(name1) + test2 = load_csv(name1, keep=['index','df/competences', + 'df/competenceGeographique', + 'df/ministereDeRattachement', + 'http://www.w3.org/2000/01/rdf-schema#label', + 'parent'] + ) \ No newline at end of file From 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