{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "14555430", "metadata": {}, "outputs": [], "source": [ "from pprint import pprint\n", "\n", "import pystatis" ] }, { "cell_type": "markdown", "id": "151ca2e5", "metadata": {}, "source": [ "`pystatis` Presentation for Data Journalists\n", "============================================" ] }, { "cell_type": "code", "execution_count": 2, "id": "bbf0b1de", "metadata": {}, "outputs": [], "source": [ "pystatis.clear_cache()" ] }, { "cell_type": "markdown", "id": "baa7eec1", "metadata": {}, "source": [ "CorrelAid\n", "---------\n", "\n", "https://www.correlaid.org/en/about/\n", "\n", "### Our Mission\n", "~~~~~~~~~~~~~~~" ] }, { "cell_type": "markdown", "id": "e85b575c", "metadata": {}, "source": [ "CorrelAid is a **non-profit community of data science enthusiasts** who want to change the world using data science. We dedicate our work to the humans, initiatives and organizations that strive to make the world a better place.\n", "\n", "We value open knowledge management and transparency in our work wherever possible while complying with GDPR regulations and following strong principles of data ethics.\n", "\n", "### Our Work\n", "~~~~~~~~~~~~" ] }, { "cell_type": "markdown", "id": "33bc0783", "metadata": {}, "source": [ "Our work is based on three pillars:\n", "\n", "1. **Using data**: We enable data analysts and scientists to apply their knowledge for the common good and social organizations to increase their impact on society by **conducting pro-bono data for good (Data4Good) projects** and providing consulting on data topics.\n", "2. **Education**: We strongly believe in sharing our knowledge. It is not for nothing that we have chosen \"education\" as our association's official purpose. This is why we offer numerous education formats for nonprofits and volunteers. In addition, we share our knowledge, code, and materials publicly.\n", "3. **Community**: Our community is the basis of our work. We unite data scientists of different backgrounds and experience levels. We organize ourselves both online and on-site within our CorrelAidX local groups." ] }, { "cell_type": "markdown", "id": "ce8ea466", "metadata": {}, "source": [ "`pystatis`\n", "----------\n", "\n", "`pystatis` is a small Python library to conveniently wrap the different GENESIS web services (APIs) in a centralized and user-friendly manner.\n", "\n", "It allows users to browse the different databases and download the desired tables from all supported databases in a convenient `pandas` `DataFrame` object, suited for further analysis." ] }, { "cell_type": "markdown", "id": "9d462d61", "metadata": {}, "source": [ "### Setup\n", "~~~~~~~~~" ] }, { "cell_type": "markdown", "id": "d25940a8", "metadata": {}, "source": [ "We won't cover the initial only-once setup here because the user has to enter their credentials for the supported databases (GENESIS, Regionalstatistik, Zensus). But there is a dedicated notebook [Setup](./00_Setup.ipynb) with examples and explanations.\n", "\n", "Main Use Cases\n", "--------------\n", "\n", "### Find\n", "~~~~~~~~" ] }, { "cell_type": "markdown", "id": "48011553", "metadata": {}, "source": [ "`pystatis.Find` allows a user to use a keyword to browse the data available on the chosen database. Finds 3 different objects:\n", "- Tables: the tables containing the relevant keyword in title\n", "- Statistics: statistics is the larger collections of tables on the topic, finds the ones with keyword in title\n", "- Variables: variables are the values (DE: Merkmal) in columns of the tables, find ones with keyword in label\n", "\n", "Returns the titles of relevant tables/statistics/variables and their [EVAS](https://www.destatis.de/DE/Service/Bibliothek/Abloesung-Fachserien/uebersicht-fs.html) number – useful tool to look these up (EVAS is necessary for the Table method)\n", "\n", "1. call Find using a keyword `query=` and specifying a database `db_name=`\n", "2. actually query the API and print the results using `.run()`\n", "3. access the various objects, their EVAS numbers, or preview using metadata" ] }, { "cell_type": "code", "execution_count": 3, "id": "27ff0988", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "##### Results #####\n", "----------------------------------------\n", "# Number of tables: 5\n", "# Preview:\n", "| | Code | Content | Time |\n", "|---:|:----------------|:-------------------------------------------------------------------------------------------|:-------|\n", "| 0 | 32121-01-02-4 | Haushaltsabfälle - Jahr - regionale Tiefe: Kreise und krfr. Städte | |\n", "| 1 | 32121-01-02-4-B | Haushaltsabfälle - Jahr - regionale Ebenen | |\n", "| 2 | 32151-01-01-4 | Primär nachgewiesene Abfallmengen - Jahressumme - regionale Tiefe: Kreise und krfr. Städte | |\n", "| 3 | 32151-01-01-4-B | Primär nachgewiesene Abfallmengen - Jahressumme - regionale Ebenen | |\n", "| 4 | AI019 | Regionalatlas Deutschland Themenbereich \"Umwelt\" Indikatoren zu \"Haushaltsabfälle\" | |\n", "----------------------------------------\n", "# Number of statistics: 3\n", "# Preview:\n", "| | Code | Content | Cubes | Information |\n", "|---:|-------:|:----------------------------------------------------------------------|--------:|:--------------|\n", "| 0 | 32121 | Erhebung der öffentlich-rechtlichen Abfallentsorgung | 8 | true |\n", "| 1 | 32151 | Erhebung der gefährlichen Abfälle, über die Nachweise zu führen sind | 8 | true |\n", "| 2 | 99910 | Regionalatlas Deutschland | 208 | true |\n", "----------------------------------------\n", "# Number of variables: 3\n", "# Preview:\n", "| | Code | Content | Type | Values | Information |\n", "|---:|:-------|:--------------------------------------------------|:---------|---------:|:--------------|\n", "| 0 | ABFA01 | Abfallarten von Haushaltsabfällen | sachlich | 6 | false |\n", "| 1 | AI1904 | Abfälle aus der Biotonne je EW | Wert | -1 | true |\n", "| 2 | RVUEA1 | Reg. Verbleib der überwachungsbedürftigen Abfälle | sachlich | 2 | false |\n", "----------------------------------------\n", "# Number of cubes: 16\n", "# Preview:\n", "| | Code | Content | State | Time | LatestUpdate | Information |\n", "|---:|:-----------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------|:----------|:---------------------|:--------------|\n", "| 0 | 32121BJ002 | Erhebung der öffentlich-rechtlichen Abfallentsorgung, Aufkommen an Haushaltsabfällen (oh.Elektroaltger.), Deutschland, Abfallarten von Haushaltsabfällen, Jahr | vollständig mit Werten | 2004-2021 | 12.05.2023 08:58:59h | false |\n", "| 1 | 32121KJ002 | Erhebung der öffentlich-rechtlichen Abfallentsorgung, Aufkommen an Haushaltsabfällen (oh.Elektroaltger.), Kreise und kreisfreie Städte, Abfallarten von Haushaltsabfällen, Jahr | vollständig mit Werten | 2004-2021 | 09.10.2023 13:13:52h | false |\n", "| 2 | 32121LJ002 | Erhebung der öffentlich-rechtlichen Abfallentsorgung, Aufkommen an Haushaltsabfällen (oh.Elektroaltger.), Bundesländer, Abfallarten von Haushaltsabfällen, Jahr | vollständig mit Werten | 2004-2021 | 01.09.2023 14:41:23h | false |\n", "| 3 | 32121RJ002 | Erhebung der öffentlich-rechtlichen Abfallentsorgung, Aufkommen an Haushaltsabfällen (oh.Elektroaltger.), Regierungsbezirke / Statistische Regionen, Abfallarten von Haushaltsabfällen, Jahr | vollständig mit Werten | 2004-2021 | 01.09.2023 14:41:23h | false |\n", "| 4 | 32151BJ001 | Erhebung der gefährlichen Abfälle, über die Nachweise zu führen sind , Erzeuger von primär nachgewiesenen Abfallmengen, Abgegebene Abfallmenge an Entsorger, Deutschland, Jahr | vollständig mit Werten | 2001-2021 | 26.07.2023 14:30:27h | false |\n", "----------------------------------------\n", "# Use object.tables, object.statistics, object.variables or object.cubes to get all results.\n", "----------------------------------------\n" ] } ], "source": [ "results = pystatis.Find(query=\"Abfall\", db_name=\"regio\")\n", "results.run()" ] }, { "cell_type": "markdown", "id": "42bb915b", "metadata": {}, "source": [ "If interested in specific object, can run `results.tables`, `results.statistics`, or `results.variables` directly." ] }, { "cell_type": "code", "execution_count": 4, "id": "7af5949f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "| | Code | Content | Time |\n", "|---:|:----------------|:-------------------------------------------------------------------------------------------|:-------|\n", "| 0 | 32121-01-02-4 | Haushaltsabfälle - Jahr - regionale Tiefe: Kreise und krfr. Städte | |\n", "| 1 | 32121-01-02-4-B | Haushaltsabfälle - Jahr - regionale Ebenen | |\n", "| 2 | 32151-01-01-4 | Primär nachgewiesene Abfallmengen - Jahressumme - regionale Tiefe: Kreise und krfr. Städte | |\n", "| 3 | 32151-01-01-4-B | Primär nachgewiesene Abfallmengen - Jahressumme - regionale Ebenen | |\n", "| 4 | AI019 | Regionalatlas Deutschland Themenbereich \"Umwelt\" Indikatoren zu \"Haushaltsabfälle\" | |" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "results.tables" ] }, { "cell_type": "markdown", "id": "fb64eaf2", "metadata": {}, "source": [ "Add `.df` to convert to a dataframe for easier handling." ] }, { "cell_type": "code", "execution_count": 5, "id": "e4bc3879", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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CodeContentTime
032121-01-02-4Haushaltsabfälle - Jahr - regionale Tiefe: Kreise und krfr. Städte
132121-01-02-4-BHaushaltsabfälle - Jahr - regionale Ebenen
232151-01-01-4Primär nachgewiesene Abfallmengen - Jahressumme - regionale Tiefe: Kreise und krfr. Städte
332151-01-01-4-BPrimär nachgewiesene Abfallmengen - Jahressumme - regionale Ebenen
4AI019Regionalatlas Deutschland Themenbereich \"Umwelt\" Indikatoren zu \"Haushaltsabfälle\"
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" ], "text/plain": [ " Code Content Time\n", "0 32121-01-02-4 Haushaltsabfälle - Jahr - regionale Tiefe: Kreise und krfr. Städte \n", "1 32121-01-02-4-B Haushaltsabfälle - Jahr - regionale Ebenen \n", "2 32151-01-01-4 Primär nachgewiesene Abfallmengen - Jahressumme - regionale Tiefe: Kreise und krfr. Städte \n", "3 32151-01-01-4-B Primär nachgewiesene Abfallmengen - Jahressumme - regionale Ebenen \n", "4 AI019 Regionalatlas Deutschland Themenbereich \"Umwelt\" Indikatoren zu \"Haushaltsabfälle\" " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "results.tables.df" ] }, { "cell_type": "markdown", "id": "7e32a668", "metadata": {}, "source": [ "We can then access the relevant codes with `.get_code([#])`. Doing this returns a list of codes from specified rows which may be useful to run in the Table method." ] }, { "cell_type": "code", "execution_count": 6, "id": "17564ec7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['32121-01-02-4', '32121-01-02-4-B', '32151-01-01-4']" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "results.tables.get_code([0, 1, 2])" ] }, { "cell_type": "markdown", "id": "dcc60b06", "metadata": {}, "source": [ "To then check that the object has the relevant data, we can preview the columns using the `.get_metadata()` method." ] }, { "cell_type": "code", "execution_count": 7, "id": "63123a8f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "TABLES 32121-01-02-4-B - 1\n", "Name:\n", "Erhebung der öffentlich-rechtlichen Abfallentsorgung\n", "--------------------\n", "Columns:\n", "Aufkommen an Haushaltsabfällen (oh.Elektroaltger.)\n", "--------------------\n", "Rows:\n", "Kreise und kreisfreie Städte\n", "----------------------------------------\n", "TABLES 32151-01-01-4 - 2\n", "Name:\n", "Erhebung der gefährlichen Abfälle, über die Nachweise zu führen sind \n", "--------------------\n", "Columns:\n", "Erzeuger von primär nachgewiesenen Abfallmengen\n", "Abgegebene Abfallmenge an Entsorger\n", "--------------------\n", "Rows:\n", "Kreise und kreisfreie Städte\n", "----------------------------------------\n" ] } ], "source": [ "results.tables.get_metadata([1, 2])" ] }, { "cell_type": "markdown", "id": "d7d7aa04", "metadata": {}, "source": [ "The `pystatis.Find` is a useful search tool to browse the database by any keyword. It is quicker than downloading a table and does not need the EVAS number to run.\n", "\n", "Use this to identify the tables of interest and to look up their EVAS as to use in the further analysis with a `pystatis.Table` method.\n", "\n", "### Table\n", "~~~~~~~~~" ] }, { "cell_type": "markdown", "id": "446063b1", "metadata": {}, "source": [ "`pystatis.Table` offers a simple Interface to get any table via its \"name\" ([EVAS](https://www.destatis.de/DE/Service/Bibliothek/Abloesung-Fachserien/uebersicht-fs.html) number).\n", "\n", "1. Create a new Table instance by passing `name=`\n", "2. Download the actual data with `.get_data(prettify=)`\n", "3. Access data via either `.raw_data` or `.data`, metadata via `.metadata`" ] }, { "cell_type": "code", "execution_count": 3, "id": "66d0e9cf", "metadata": {}, "outputs": [], "source": [ "# GENESIS - https://www-genesis.destatis.de/genesis//online?operation=table&code=31231-0001&bypass=true&levelindex=1&levelid=1706599948340#abreadcrumb\n", "t = pystatis.Table(name=\"31231-0001\") #" ] }, { "cell_type": "markdown", "id": "11a26d11", "metadata": {}, "source": [ "Per default, `prettify` is set to `True` and will return a more readable format. Here we show the original format first." ] }, { "cell_type": "code", "execution_count": 6, "id": "927c0a2c", "metadata": {}, "outputs": [], "source": [ "t.get_data(prettify=False)" ] }, { "cell_type": "code", "execution_count": 7, "id": "4308ec4d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['Statistik_Code;Statistik_Label;Zeit_Code;Zeit_Label;Zeit;1_Merkmal_Code;1_Merkmal_Label;1_Auspraegung_Code;1_Auspraegung_Label;WOH001__Wohnungen_in_Wohn-_und_Nichtwohngebaeuden__Anzahl;WOH004__Wohnungen_je_1000_Einwohner__Anzahl;FLC001__Wohnflaeche__1000_qm;FLC102__Wohnflaeche_je_Wohnung__qm;FLC103__Wohnflaeche_je_Einwohner__qm;RME001__Raeume__Anzahl;RME002__Raeume_je_Wohnung__Anzahl;RME003__Raeume_je_Einwohner__Anzahl',\n", " '31231;Fortschreibung Wohngebäude- und Wohnungsbestand;STAG;Stichtag;31.12.2015;DINSG;Deutschland insgesamt;DG;Deutschland;41446271;504;3794976;91,6;46,2;182295713;4,4;2,2',\n", " '31231;Fortschreibung Wohngebäude- und Wohnungsbestand;STAG;Stichtag;31.12.2016;DINSG;Deutschland insgesamt;DG;Deutschland;41703347;505;3822507;91,7;46,3;183354291;4,4;2,2',\n", " '31231;Fortschreibung Wohngebäude- und Wohnungsbestand;STAG;Stichtag;31.12.2017;DINSG;Deutschland insgesamt;DG;Deutschland;41968066;507;3850742;91,8;46,5;184427760;4,4;2,2',\n", " '31231;Fortschreibung Wohngebäude- und Wohnungsbestand;STAG;Stichtag;31.12.2018;DINSG;Deutschland insgesamt;DG;Deutschland;42235402;509;3878901;91,8;46,7;185491224;4,4;2,2',\n", " '31231;Fortschreibung Wohngebäude- und Wohnungsbestand;STAG;Stichtag;31.12.2019;DINSG;Deutschland insgesamt;DG;Deutschland;42512771;511;3908347;91,9;47,0;186594482;4,4;2,2',\n", " '31231;Fortschreibung Wohngebäude- und Wohnungsbestand;STAG;Stichtag;31.12.2020;DINSG;Deutschland insgesamt;DG;Deutschland;42803737;515;3938871;92,0;47,4;187746588;4,4;2,3',\n", " '31231;Fortschreibung Wohngebäude- und Wohnungsbestand;STAG;Stichtag;31.12.2021;DINSG;Deutschland insgesamt;DG;Deutschland;43084122;518;3967765;92,1;47,7;188829383;4,4;2,3',\n", " '31231;Fortschreibung Wohngebäude- und Wohnungsbestand;STAG;Stichtag;31.12.2022;DINSG;Deutschland insgesamt;DG;Deutschland;43366919;514;3996995;92,2;47,4;189920514;4,4;2,3']" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "t.raw_data.splitlines()" ] }, { "cell_type": "code", "execution_count": 8, "id": "d37138dd", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Statistik_CodeStatistik_LabelZeit_CodeZeit_LabelZeit1_Merkmal_Code1_Merkmal_Label1_Auspraegung_Code1_Auspraegung_LabelWOH001__Wohnungen_in_Wohn-_und_Nichtwohngebaeuden__AnzahlWOH004__Wohnungen_je_1000_Einwohner__AnzahlFLC001__Wohnflaeche__1000_qmFLC102__Wohnflaeche_je_Wohnung__qmFLC103__Wohnflaeche_je_Einwohner__qmRME001__Raeume__AnzahlRME002__Raeume_je_Wohnung__AnzahlRME003__Raeume_je_Einwohner__Anzahl
031231Fortschreibung Wohngebäude- und WohnungsbestandSTAGStichtag31.12.2015DINSGDeutschland insgesamtDGDeutschland41446271504379497691,646,21822957134,42,2
131231Fortschreibung Wohngebäude- und WohnungsbestandSTAGStichtag31.12.2016DINSGDeutschland insgesamtDGDeutschland41703347505382250791,746,31833542914,42,2
231231Fortschreibung Wohngebäude- und WohnungsbestandSTAGStichtag31.12.2017DINSGDeutschland insgesamtDGDeutschland41968066507385074291,846,51844277604,42,2
331231Fortschreibung Wohngebäude- und WohnungsbestandSTAGStichtag31.12.2018DINSGDeutschland insgesamtDGDeutschland42235402509387890191,846,71854912244,42,2
431231Fortschreibung Wohngebäude- und WohnungsbestandSTAGStichtag31.12.2019DINSGDeutschland insgesamtDGDeutschland42512771511390834791,947,01865944824,42,2
531231Fortschreibung Wohngebäude- und WohnungsbestandSTAGStichtag31.12.2020DINSGDeutschland insgesamtDGDeutschland42803737515393887192,047,41877465884,42,3
631231Fortschreibung Wohngebäude- und WohnungsbestandSTAGStichtag31.12.2021DINSGDeutschland insgesamtDGDeutschland43084122518396776592,147,71888293834,42,3
731231Fortschreibung Wohngebäude- und WohnungsbestandSTAGStichtag31.12.2022DINSGDeutschland insgesamtDGDeutschland43366919514399699592,247,41899205144,42,3
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" ], "text/plain": [ " Statistik_Code Statistik_Label Zeit_Code Zeit_Label Zeit 1_Merkmal_Code 1_Merkmal_Label 1_Auspraegung_Code 1_Auspraegung_Label WOH001__Wohnungen_in_Wohn-_und_Nichtwohngebaeuden__Anzahl WOH004__Wohnungen_je_1000_Einwohner__Anzahl FLC001__Wohnflaeche__1000_qm FLC102__Wohnflaeche_je_Wohnung__qm FLC103__Wohnflaeche_je_Einwohner__qm RME001__Raeume__Anzahl RME002__Raeume_je_Wohnung__Anzahl RME003__Raeume_je_Einwohner__Anzahl\n", "0 31231 Fortschreibung Wohngebäude- und Wohnungsbestand STAG Stichtag 31.12.2015 DINSG Deutschland insgesamt DG Deutschland 41446271 504 3794976 91,6 46,2 182295713 4,4 2,2\n", "1 31231 Fortschreibung Wohngebäude- und Wohnungsbestand STAG Stichtag 31.12.2016 DINSG Deutschland insgesamt DG Deutschland 41703347 505 3822507 91,7 46,3 183354291 4,4 2,2\n", "2 31231 Fortschreibung Wohngebäude- und Wohnungsbestand STAG Stichtag 31.12.2017 DINSG Deutschland insgesamt DG Deutschland 41968066 507 3850742 91,8 46,5 184427760 4,4 2,2\n", "3 31231 Fortschreibung Wohngebäude- und Wohnungsbestand STAG Stichtag 31.12.2018 DINSG Deutschland insgesamt DG Deutschland 42235402 509 3878901 91,8 46,7 185491224 4,4 2,2\n", "4 31231 Fortschreibung Wohngebäude- und Wohnungsbestand STAG Stichtag 31.12.2019 DINSG Deutschland insgesamt DG Deutschland 42512771 511 3908347 91,9 47,0 186594482 4,4 2,2\n", "5 31231 Fortschreibung Wohngebäude- und Wohnungsbestand STAG Stichtag 31.12.2020 DINSG Deutschland insgesamt DG Deutschland 42803737 515 3938871 92,0 47,4 187746588 4,4 2,3\n", "6 31231 Fortschreibung Wohngebäude- und Wohnungsbestand STAG Stichtag 31.12.2021 DINSG Deutschland insgesamt DG Deutschland 43084122 518 3967765 92,1 47,7 188829383 4,4 2,3\n", "7 31231 Fortschreibung Wohngebäude- und Wohnungsbestand STAG Stichtag 31.12.2022 DINSG Deutschland insgesamt DG Deutschland 43366919 514 3996995 92,2 47,4 189920514 4,4 2,3" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "t.data" ] }, { "cell_type": "markdown", "id": "1f193771", "metadata": {}, "source": [ "As you can see, the original format has a lot of redundant information and columns with metadata like the codes for the different variables. Let's rerun `get_data` with `prettify=True`." ] }, { "cell_type": "code", "execution_count": 9, "id": "6a433995", "metadata": {}, "outputs": [], "source": [ "t.get_data()" ] }, { "cell_type": "code", "execution_count": 10, "id": "88cb7561", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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StichtagDeutschland insgesamtWohnungen_in_Wohn-_und_NichtwohngebaeudenWohnungen_je_1000_EinwohnerWohnflaecheWohnflaeche_je_WohnungWohnflaeche_je_EinwohnerRaeumeRaeume_je_WohnungRaeume_je_Einwohner
031.12.2015Deutschland41446271504379497691,646,21822957134,42,2
131.12.2016Deutschland41703347505382250791,746,31833542914,42,2
231.12.2017Deutschland41968066507385074291,846,51844277604,42,2
331.12.2018Deutschland42235402509387890191,846,71854912244,42,2
431.12.2019Deutschland42512771511390834791,947,01865944824,42,2
531.12.2020Deutschland42803737515393887192,047,41877465884,42,3
631.12.2021Deutschland43084122518396776592,147,71888293834,42,3
731.12.2022Deutschland43366919514399699592,247,41899205144,42,3
\n", "
" ], "text/plain": [ " Stichtag Deutschland insgesamt Wohnungen_in_Wohn-_und_Nichtwohngebaeuden Wohnungen_je_1000_Einwohner Wohnflaeche Wohnflaeche_je_Wohnung Wohnflaeche_je_Einwohner Raeume Raeume_je_Wohnung Raeume_je_Einwohner\n", "0 31.12.2015 Deutschland 41446271 504 3794976 91,6 46,2 182295713 4,4 2,2\n", "1 31.12.2016 Deutschland 41703347 505 3822507 91,7 46,3 183354291 4,4 2,2\n", "2 31.12.2017 Deutschland 41968066 507 3850742 91,8 46,5 184427760 4,4 2,2\n", "3 31.12.2018 Deutschland 42235402 509 3878901 91,8 46,7 185491224 4,4 2,2\n", "4 31.12.2019 Deutschland 42512771 511 3908347 91,9 47,0 186594482 4,4 2,2\n", "5 31.12.2020 Deutschland 42803737 515 3938871 92,0 47,4 187746588 4,4 2,3\n", "6 31.12.2021 Deutschland 43084122 518 3967765 92,1 47,7 188829383 4,4 2,3\n", "7 31.12.2022 Deutschland 43366919 514 3996995 92,2 47,4 189920514 4,4 2,3" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "t.data" ] }, { "cell_type": "markdown", "id": "1be153f2", "metadata": {}, "source": [ "You can also access the metadata as returned by the Catalogue endpoint." ] }, { "cell_type": "code", "execution_count": 11, "id": "f1f4957d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{'Copyright': '© Statistisches Bundesamt (Destatis), 2024',\n", " 'Ident': {'Method': 'table', 'Service': 'metadata'},\n", " 'Object': {'Code': '31231-0001',\n", " 'Content': 'Wohnungen in Wohn- und Nichtwohngebäuden, Wohnfläche, '\n", " 'Räume:\\n'\n", " 'Deutschland, Stichtag',\n", " 'Structure': {'Columns': [{'Code': 'WOH001',\n", " 'Content': 'Wohnungen in Wohn- und '\n", " 'Nichtwohngebäuden',\n", " 'Selected': None,\n", " 'Structure': None,\n", " 'Type': 'Merkmal',\n", " 'Updated': 'see parent',\n", " 'Values': None},\n", " {'Code': 'WOH004',\n", " 'Content': 'Wohnungen je 1000 Einwohner',\n", " 'Selected': None,\n", " 'Structure': None,\n", " 'Type': 'Merkmal',\n", " 'Updated': 'see parent',\n", " 'Values': None},\n", " {'Code': 'FLC001',\n", " 'Content': 'Wohnfläche',\n", " 'Selected': None,\n", " 'Structure': None,\n", " 'Type': 'Merkmal',\n", " 'Updated': 'see parent',\n", " 'Values': None},\n", " {'Code': 'FLC102',\n", " 'Content': 'Wohnfläche je Wohnung',\n", " 'Selected': None,\n", " 'Structure': None,\n", " 'Type': 'Merkmal',\n", " 'Updated': 'see parent',\n", " 'Values': None},\n", " {'Code': 'FLC103',\n", " 'Content': 'Wohnfläche je Einwohner',\n", " 'Selected': None,\n", " 'Structure': None,\n", " 'Type': 'Merkmal',\n", " 'Updated': 'see parent',\n", " 'Values': None},\n", " {'Code': 'RME001',\n", " 'Content': 'Räume',\n", " 'Selected': None,\n", " 'Structure': None,\n", " 'Type': 'Merkmal',\n", " 'Updated': 'see parent',\n", " 'Values': None},\n", " {'Code': 'RME002',\n", " 'Content': 'Räume je Wohnung',\n", " 'Selected': None,\n", " 'Structure': None,\n", " 'Type': 'Merkmal',\n", " 'Updated': 'see parent',\n", " 'Values': None},\n", " {'Code': 'RME003',\n", " 'Content': 'Räume je Einwohner',\n", " 'Selected': None,\n", " 'Structure': None,\n", " 'Type': 'Merkmal',\n", " 'Updated': 'see parent',\n", " 'Values': None}],\n", " 'Head': {'Code': '31231',\n", " 'Content': 'Fortschreibung Wohngebäude- und '\n", " 'Wohnungsbestand',\n", " 'Selected': None,\n", " 'Structure': [{'Code': 'DINSG',\n", " 'Content': 'Deutschland '\n", " 'insgesamt',\n", " 'Selected': '1',\n", " 'Structure': None,\n", " 'Type': 'Merkmal',\n", " 'Updated': 'see parent',\n", " 'Values': '1'}],\n", " 'Type': 'Statistik',\n", " 'Updated': 'see parent',\n", " 'Values': None},\n", " 'Rows': [{'Code': 'STAG',\n", " 'Content': 'Stichtag',\n", " 'Selected': None,\n", " 'Structure': None,\n", " 'Type': 'Merkmal',\n", " 'Updated': 'see parent',\n", " 'Values': None}],\n", " 'Subheading': None,\n", " 'Subtitel': None},\n", " 'Time': {'From': '31.12.2015', 'To': '31.12.2022'},\n", " 'Updated': '16.08.2023 16:38:39h',\n", " 'Valid': 'false'},\n", " 'Parameter': {'area': 'Alle',\n", " 'language': 'de',\n", " 'name': '31231-0001',\n", " 'password': '********************',\n", " 'username': '********************'},\n", " 'Status': {'Code': 0, 'Content': 'erfolgreich', 'Type': 'Information'}}\n" ] } ], "source": [ "pprint(t.metadata)" ] }, { "cell_type": "markdown", "id": "0d8805d9", "metadata": {}, "source": [ "You can use any EVAS number from the supported databases like GENESIS, Regionalstatistik or Zensus. The library identifies the database for you so you don't have to care about this." ] }, { "cell_type": "code", "execution_count": 12, "id": "533a7e96", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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JahrDeutschland insgesamtEnergieträgerElektrizitaetserzeugung_(brutto)Elektrizitaetserzeugung_(netto)NettowaermeerzeugungBrennstoffeinsatz
02022DeutschlandSteinkohlen60759486.055443585.019106288.05.712968e+08
12022DeutschlandSteinkohlenkoksNaNNaNNaNNaN
22022DeutschlandSteinkohlenbrikettsNaNNaNNaNNaN
32022DeutschlandKohlenwertstoffe aus SteinkohleNaNNaNNaNNaN
42022DeutschlandSonstige SteinkohlenNaNNaNNaNNaN
52022DeutschlandRohbraunkohlen113611255.0105943521.06558509.01.039784e+09
62022DeutschlandHartbraunkohlenNaNNaNNaNNaN
72022DeutschlandBraunkohlenbriketts43460.040444.0NaN4.102690e+05
82022DeutschlandBraunkohlenkoksNaNNaNNaNNaN
92022DeutschlandWirbelschichtkohleNaNNaNNaNNaN
102022DeutschlandStaub- und TrockenkohleNaNNaNNaNNaN
112022DeutschlandSonstige BraunkohlenNaNNaNNaNNaN
122022DeutschlandDieselkraftstoffNaNNaNNaNNaN
132022DeutschlandHeizöl, leicht829009.0773967.01386039.01.301587e+07
142022DeutschlandHeizöl, schwer237152.0214908.033706.02.366438e+06
152022DeutschlandFlüssiggasNaNNaNNaNNaN
162022DeutschlandRaffineriegasNaNNaNNaNNaN
172022DeutschlandPetrolkoksNaNNaNNaNNaN
182022DeutschlandSonstige MineralölprodukteNaNNaNNaN1.827200e+05
192022DeutschlandErdgas, Erdölgas46636174.045163692.041934364.04.312443e+08
202022DeutschlandGrubengas582597.0577321.0NaN5.708188e+06
212022DeutschlandKokereigasNaNNaNNaNNaN
222022DeutschlandHochofengasNaNNaNNaNNaN
232022DeutschlandSonstige hergestellte GaseNaNNaNNaNNaN
242022DeutschlandWasserstoffNaNNaNNaNNaN
252022DeutschlandLaufwasser13404202.013281638.0NaNNaN
262022DeutschlandSpeicherwasser614789.0611162.0NaNNaN
272022DeutschlandPumpspeicherwasserNaNNaNNaNNaN
282022DeutschlandPumpspeicher mit natürlichem Zufluss480142.0480142.0NaNNaN
292022DeutschlandPumpspeicher ohne natürlichen ZuflussNaNNaNNaNNaN
302022DeutschlandWindkraftNaNNaNNaNNaN
312022DeutschlandPhotovoltaikNaNNaNNaNNaN
322022DeutschlandGeothermieNaNNaNNaNNaN
332022DeutschlandWärmepumpen (Erd- und Umweltwärme)NaNNaNNaNNaN
342022DeutschlandSolarthermieNaNNaNNaNNaN
352022DeutschlandFeste biogene Stoffe5157301.04555379.05496277.07.738774e+07
362022DeutschlandFlüssige biogene StoffeNaNNaNNaNNaN
372022DeutschlandBiogas2781281.02662858.02238806.02.547129e+07
382022DeutschlandBiomethan (Bioerdgas)1031257.01007770.01172103.09.574762e+06
392022DeutschlandKlärgasNaNNaNNaNNaN
402022DeutschlandDeponiegas59864.056080.035286.06.237530e+05
412022DeutschlandSonstige erneuerbare EnergienNaNNaNNaNNaN
422022DeutschlandKlärschlamm206726.0181848.0107537.02.241021e+06
432022DeutschlandAbfall (Hausmüll, Industrie)NaNNaNNaNNaN
442022DeutschlandAbfall (Industrie)542529.0368799.01083604.01.036228e+07
452022DeutschlandAbfall (Hausmüll, Siedlungsabfälle)10494870.08248924.016865152.01.899352e+08
462022DeutschlandKernenergie34709262.032765409.0NaNNaN
472022DeutschlandWärme346035.0330543.01115125.08.318414e+06
482022DeutschlandStrom (Elektrokessel)NaNNaNNaNNaN
492022DeutschlandSonstige EnergieträgerNaNNaNNaNNaN
502022DeutschlandAndere SpeicherNaNNaNNaNNaN
512022DeutschlandInsgesamt293024354.0273144778.098388835.02.395591e+09
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" ], "text/plain": [ " Jahr Deutschland insgesamt Energieträger Elektrizitaetserzeugung_(brutto) Elektrizitaetserzeugung_(netto) Nettowaermeerzeugung Brennstoffeinsatz\n", "0 2022 Deutschland Steinkohlen 60759486.0 55443585.0 19106288.0 5.712968e+08\n", "1 2022 Deutschland Steinkohlenkoks NaN NaN NaN NaN\n", "2 2022 Deutschland Steinkohlenbriketts NaN NaN NaN NaN\n", "3 2022 Deutschland Kohlenwertstoffe aus Steinkohle NaN NaN NaN NaN\n", "4 2022 Deutschland Sonstige Steinkohlen NaN NaN NaN NaN\n", "5 2022 Deutschland Rohbraunkohlen 113611255.0 105943521.0 6558509.0 1.039784e+09\n", "6 2022 Deutschland Hartbraunkohlen NaN NaN NaN NaN\n", "7 2022 Deutschland Braunkohlenbriketts 43460.0 40444.0 NaN 4.102690e+05\n", "8 2022 Deutschland Braunkohlenkoks NaN NaN NaN NaN\n", "9 2022 Deutschland Wirbelschichtkohle NaN NaN NaN NaN\n", "10 2022 Deutschland Staub- und Trockenkohle NaN NaN NaN NaN\n", "11 2022 Deutschland Sonstige Braunkohlen NaN NaN NaN NaN\n", "12 2022 Deutschland Dieselkraftstoff NaN NaN NaN NaN\n", "13 2022 Deutschland Heizöl, leicht 829009.0 773967.0 1386039.0 1.301587e+07\n", "14 2022 Deutschland Heizöl, schwer 237152.0 214908.0 33706.0 2.366438e+06\n", "15 2022 Deutschland Flüssiggas NaN NaN NaN NaN\n", "16 2022 Deutschland Raffineriegas NaN NaN NaN NaN\n", "17 2022 Deutschland Petrolkoks NaN NaN NaN NaN\n", "18 2022 Deutschland Sonstige Mineralölprodukte NaN NaN NaN 1.827200e+05\n", "19 2022 Deutschland Erdgas, Erdölgas 46636174.0 45163692.0 41934364.0 4.312443e+08\n", "20 2022 Deutschland Grubengas 582597.0 577321.0 NaN 5.708188e+06\n", "21 2022 Deutschland Kokereigas NaN NaN NaN NaN\n", "22 2022 Deutschland Hochofengas NaN NaN NaN NaN\n", "23 2022 Deutschland Sonstige hergestellte Gase NaN NaN NaN NaN\n", "24 2022 Deutschland Wasserstoff NaN NaN NaN NaN\n", "25 2022 Deutschland Laufwasser 13404202.0 13281638.0 NaN NaN\n", "26 2022 Deutschland Speicherwasser 614789.0 611162.0 NaN NaN\n", "27 2022 Deutschland Pumpspeicherwasser NaN NaN NaN NaN\n", "28 2022 Deutschland Pumpspeicher mit natürlichem Zufluss 480142.0 480142.0 NaN NaN\n", "29 2022 Deutschland Pumpspeicher ohne natürlichen Zufluss NaN NaN NaN NaN\n", "30 2022 Deutschland Windkraft NaN NaN NaN NaN\n", "31 2022 Deutschland Photovoltaik NaN NaN NaN NaN\n", "32 2022 Deutschland Geothermie NaN NaN NaN NaN\n", "33 2022 Deutschland Wärmepumpen (Erd- und Umweltwärme) NaN NaN NaN NaN\n", "34 2022 Deutschland Solarthermie NaN NaN NaN NaN\n", "35 2022 Deutschland Feste biogene Stoffe 5157301.0 4555379.0 5496277.0 7.738774e+07\n", "36 2022 Deutschland Flüssige biogene Stoffe NaN NaN NaN NaN\n", "37 2022 Deutschland Biogas 2781281.0 2662858.0 2238806.0 2.547129e+07\n", "38 2022 Deutschland Biomethan (Bioerdgas) 1031257.0 1007770.0 1172103.0 9.574762e+06\n", "39 2022 Deutschland Klärgas NaN NaN NaN NaN\n", "40 2022 Deutschland Deponiegas 59864.0 56080.0 35286.0 6.237530e+05\n", "41 2022 Deutschland Sonstige erneuerbare Energien NaN NaN NaN NaN\n", "42 2022 Deutschland Klärschlamm 206726.0 181848.0 107537.0 2.241021e+06\n", "43 2022 Deutschland Abfall (Hausmüll, Industrie) NaN NaN NaN NaN\n", "44 2022 Deutschland Abfall (Industrie) 542529.0 368799.0 1083604.0 1.036228e+07\n", "45 2022 Deutschland Abfall (Hausmüll, Siedlungsabfälle) 10494870.0 8248924.0 16865152.0 1.899352e+08\n", "46 2022 Deutschland Kernenergie 34709262.0 32765409.0 NaN NaN\n", "47 2022 Deutschland Wärme 346035.0 330543.0 1115125.0 8.318414e+06\n", "48 2022 Deutschland Strom (Elektrokessel) NaN NaN NaN NaN\n", "49 2022 Deutschland Sonstige Energieträger NaN NaN NaN NaN\n", "50 2022 Deutschland Andere Speicher NaN NaN NaN NaN\n", "51 2022 Deutschland Insgesamt 293024354.0 273144778.0 98388835.0 2.395591e+09" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# GENESIS\n", "t = pystatis.Table(name=\"43311-0001\")\n", "t.get_data()\n", "t.data" ] }, { "cell_type": "code", "execution_count": 13, "id": "b00f1c76", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/miay/git/github/CorrelAid/pystatis/src/pystatis/table.py:48: DtypeWarning: Columns (7) have mixed types. Specify dtype option on import or set low_memory=False.\n", " self.data = pd.read_csv(\n" ] }, { "data": { "text/html": [ "
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SemesterKreise und kreisfreie StädteGeschlechtNationalität (inkl. insgesamt)Fächergruppe (mit Insgesamt)Kreise und kreisfreie Städte_CodeGeschlecht_CodeNationalität (inkl. insgesamt)_CodeFächergruppe (mit Insgesamt)_CodeStudierende_(im_Kreisgebiet)
0WS 2021/22DeutschlandInsgesamtInsgesamtGeisteswissenschaftenDGINSGESAMTINSGESAMTHS-FG01316442.0
1WS 2021/22DeutschlandInsgesamtInsgesamtSportDGINSGESAMTINSGESAMTHS-FG0231157.0
2WS 2021/22DeutschlandInsgesamtInsgesamtRechts-, Wirtschafts- und SozialwissenschaftenDGINSGESAMTINSGESAMTHS-FG031138785.0
3WS 2021/22DeutschlandInsgesamtInsgesamtMathematik/NaturwissenschaftenDGINSGESAMTINSGESAMTHS-FG04314060.0
4WS 2021/22DeutschlandInsgesamtInsgesamtHumanmedizin/GesundheitswissenschaftenDGINSGESAMTINSGESAMTHS-FG05196239.0
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48415WS 2021/22Altenburger Land, LandkreisweiblichDeutscheAgrar-, Forst- und Ernährungswissensch., Veterinär16077GESWNATDHS-FG07NaN
48416WS 2021/22Altenburger Land, LandkreisweiblichDeutscheIngenieurwissenschaften16077GESWNATDHS-FG08NaN
48417WS 2021/22Altenburger Land, LandkreisweiblichDeutscheKunst, Kunstwissenschaft16077GESWNATDHS-FG09NaN
48418WS 2021/22Altenburger Land, LandkreisweiblichDeutscheAußerhalb der Studienbereichsgliederung16077GESWNATDHS-FG10NaN
48419WS 2021/22Altenburger Land, LandkreisweiblichDeutscheInsgesamt16077GESWNATDINSGESAMTNaN
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48420 rows × 10 columns

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" ], "text/plain": [ " Semester Kreise und kreisfreie Städte Geschlecht Nationalität (inkl. insgesamt) Fächergruppe (mit Insgesamt) Kreise und kreisfreie Städte_Code Geschlecht_Code Nationalität (inkl. insgesamt)_Code Fächergruppe (mit Insgesamt)_Code Studierende_(im_Kreisgebiet)\n", "0 WS 2021/22 Deutschland Insgesamt Insgesamt Geisteswissenschaften DG INSGESAMT INSGESAMT HS-FG01 316442.0\n", "1 WS 2021/22 Deutschland Insgesamt Insgesamt Sport DG INSGESAMT INSGESAMT HS-FG02 31157.0\n", "2 WS 2021/22 Deutschland Insgesamt Insgesamt Rechts-, Wirtschafts- und Sozialwissenschaften DG INSGESAMT INSGESAMT HS-FG03 1138785.0\n", "3 WS 2021/22 Deutschland Insgesamt Insgesamt Mathematik/Naturwissenschaften DG INSGESAMT INSGESAMT HS-FG04 314060.0\n", "4 WS 2021/22 Deutschland Insgesamt Insgesamt Humanmedizin/Gesundheitswissenschaften DG INSGESAMT INSGESAMT HS-FG05 196239.0\n", "... ... ... ... ... ... ... ... ... ... ...\n", "48415 WS 2021/22 Altenburger Land, Landkreis weiblich Deutsche Agrar-, Forst- und Ernährungswissensch., Veterinär 16077 GESW NATD HS-FG07 NaN\n", "48416 WS 2021/22 Altenburger Land, Landkreis weiblich Deutsche Ingenieurwissenschaften 16077 GESW NATD HS-FG08 NaN\n", "48417 WS 2021/22 Altenburger Land, Landkreis weiblich Deutsche Kunst, Kunstwissenschaft 16077 GESW NATD HS-FG09 NaN\n", "48418 WS 2021/22 Altenburger Land, Landkreis weiblich Deutsche Außerhalb der Studienbereichsgliederung 16077 GESW NATD HS-FG10 NaN\n", "48419 WS 2021/22 Altenburger Land, Landkreis weiblich Deutsche Insgesamt 16077 GESW NATD INSGESAMT NaN\n", "\n", "[48420 rows x 10 columns]" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Regionalstatistik\n", "t = pystatis.Table(name=\"21311-01-01-4\")\n", "t.get_data()\n", "t.data" ] }, { "cell_type": "code", "execution_count": 4, "id": "4ce4c9d5", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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StichtagDeutschlandHöchster SchulabschlussPersonen ab 15 Jahren
02011-05-09DeutschlandMittlerer Schulabschluss und gymnasiale Oberstufe1
12011-05-09DeutschlandHaupt-/ Volksschulabschluss2
22011-05-09DeutschlandOhne Abschluss4932710
32011-05-09DeutschlandInsgesamt6
42011-05-09DeutschlandAllg./fachgebundene Hochschulreife (Abitur)1
52011-05-09DeutschlandFachhochschulreife5531480
62011-05-09DeutschlandNoch in schulischer Ausbildung1691700
72011-05-09DeutschlandAllg./fachgebundene Hochschulreife (Abitur)1
82011-05-09DeutschlandSchüler/-innen der gymnasialen Oberstufe1339490
92011-05-09DeutschlandRealschul- oder gleichwertiger Abschluss1
102011-05-09DeutschlandHaupt-/ Volksschulabschluss2
112011-05-09DeutschlandFachhochschulreife5531480
122011-05-09DeutschlandOhne Schulabschluss3241010
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" ], "text/plain": [ " Stichtag Deutschland Höchster Schulabschluss Personen ab 15 Jahren\n", "0 2011-05-09 Deutschland Mittlerer Schulabschluss und gymnasiale Oberstufe 1\n", "1 2011-05-09 Deutschland Haupt-/ Volksschulabschluss 2\n", "2 2011-05-09 Deutschland Ohne Abschluss 4932710\n", "3 2011-05-09 Deutschland Insgesamt 6\n", "4 2011-05-09 Deutschland Allg./fachgebundene Hochschulreife (Abitur) 1\n", "5 2011-05-09 Deutschland Fachhochschulreife 5531480\n", "6 2011-05-09 Deutschland Noch in schulischer Ausbildung 1691700\n", "7 2011-05-09 Deutschland Allg./fachgebundene Hochschulreife (Abitur) 1\n", "8 2011-05-09 Deutschland Schüler/-innen der gymnasialen Oberstufe 1339490\n", "9 2011-05-09 Deutschland Realschul- oder gleichwertiger Abschluss 1\n", "10 2011-05-09 Deutschland Haupt-/ Volksschulabschluss 2\n", "11 2011-05-09 Deutschland Fachhochschulreife 5531480\n", "12 2011-05-09 Deutschland Ohne Schulabschluss 3241010" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Zensus\n", "t = pystatis.Table(name=\"2000S-1006\")\n", "t.get_data()\n", "t.data" ] }, { "cell_type": "markdown", "id": "4a869399", "metadata": {}, "source": [ "The `get_data()` method supports all parameters that you can pass to the API, like `startyear`, `endyear` or `timeslices`" ] }, { "cell_type": "code", "execution_count": 5, "id": "f912518e", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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JahrDeutschland insgesamtEnergieträgerElektrizitaetserzeugung_(brutto)Elektrizitaetserzeugung_(netto)NettowaermeerzeugungBrennstoffeinsatz
02002DeutschlandSteinkohlen121062371.0111426568.0NaN1.081030e+09
12002DeutschlandSteinkohlenkoksNaNNaNNaNNaN
22002DeutschlandSteinkohlenbrikettsNaNNaNNaNNaN
32002DeutschlandKohlenwertstoffe aus SteinkohleNaNNaNNaNNaN
42002DeutschlandSonstige SteinkohlenNaNNaNNaNNaN
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10872022DeutschlandWärme346035.0330543.01115125.08.318414e+06
10882022DeutschlandStrom (Elektrokessel)NaNNaNNaNNaN
10892022DeutschlandSonstige EnergieträgerNaNNaNNaNNaN
10902022DeutschlandAndere SpeicherNaNNaNNaNNaN
10912022DeutschlandInsgesamt293024354.0273144778.098388835.02.395591e+09
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1092 rows × 7 columns

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" ], "text/plain": [ " Jahr Deutschland insgesamt Energieträger Elektrizitaetserzeugung_(brutto) Elektrizitaetserzeugung_(netto) Nettowaermeerzeugung Brennstoffeinsatz\n", "0 2002 Deutschland Steinkohlen 121062371.0 111426568.0 NaN 1.081030e+09\n", "1 2002 Deutschland Steinkohlenkoks NaN NaN NaN NaN\n", "2 2002 Deutschland Steinkohlenbriketts NaN NaN NaN NaN\n", "3 2002 Deutschland Kohlenwertstoffe aus Steinkohle NaN NaN NaN NaN\n", "4 2002 Deutschland Sonstige Steinkohlen NaN NaN NaN NaN\n", "... ... ... ... ... ... ... ...\n", "1087 2022 Deutschland Wärme 346035.0 330543.0 1115125.0 8.318414e+06\n", "1088 2022 Deutschland Strom (Elektrokessel) NaN NaN NaN NaN\n", "1089 2022 Deutschland Sonstige Energieträger NaN NaN NaN NaN\n", "1090 2022 Deutschland Andere Speicher NaN NaN NaN NaN\n", "1091 2022 Deutschland Insgesamt 293024354.0 273144778.0 98388835.0 2.395591e+09\n", "\n", "[1092 rows x 7 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# GENESIS\n", "t = pystatis.Table(name=\"43311-0001\")\n", "t.get_data(startyear=2000)\n", "t.data" ] }, { "cell_type": "markdown", "id": "19ef667d", "metadata": {}, "source": [ "Advanced Features\n", "-----------------\n", "\n", "- Caching\n", "- Handling background jobs\n", "- Cubes\n", "\n", "Geo-Visualization\n", "-----------------\n", "\n", "Case study: international students in Germany\n", "- time evolution\n", "- regional differences (at the level of federal states)" ] }, { "cell_type": "code", "execution_count": 24, "id": "2f74a00f", "metadata": {}, "outputs": [], "source": [ "# !pip install geopandas\n", "# !pip install matplotlib" ] }, { "cell_type": "code", "execution_count": 55, "id": "01a68933", "metadata": {}, "outputs": [], "source": [ "import geopandas\n", "import pandas as pd\n", "from matplotlib import pyplot as plt" ] }, { "cell_type": "markdown", "id": "0a0c49e2", "metadata": {}, "source": [ "### Load Data from Regionalstatistik\n", "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" ] }, { "cell_type": "code", "execution_count": 56, "id": "e5e9b02c", "metadata": {}, "outputs": [], "source": [ "students = pystatis.Table(name=\"21311-01-01-4\")" ] }, { "cell_type": "code", "execution_count": 57, "id": "76a868f5", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/macbookpro/Git Repos/pystatis/src/pystatis/table.py:46: DtypeWarning: Columns (7) have mixed types. Specify dtype option on import or set low_memory=False.\n", " self.data = pd.read_csv(data_str, sep=\";\", na_values = [\"...\",\".\",\"-\",\"/\",\"x\"])\n" ] } ], "source": [ "students.get_data(startyear=2015)" ] }, { "cell_type": "markdown", "id": "4de03a89", "metadata": {}, "source": [ "### Set Proper Column Types\n", "~~~~~~~~~~~~~~~~~~~~~~~~~~~" ] }, { "cell_type": "code", "execution_count": 61, "id": "87aa68c5", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 DG\n", "1 DG\n", "2 DG\n", "3 DG\n", "4 DG\n", " ... \n", "338935 16077\n", "338936 16077\n", "338937 16077\n", "338938 16077\n", "338939 16077\n", "Name: Kreise und kreisfreie Städte_Code, Length: 338940, dtype: object" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "students.data[\"Kreise und kreisfreie Städte_Code\"] = students.data[\n", " \"Kreise und kreisfreie Städte_Code\"\n", "].astype(str)\n", "students.data[\"Kreise und kreisfreie Städte_Code\"]" ] }, { "cell_type": "code", "execution_count": 59, "id": "37e7f2be", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 DG\n", "1 DG\n", "2 DG\n", "3 DG\n", "4 DG\n", " ... \n", "338935 16077\n", "338936 16077\n", "338937 16077\n", "338938 16077\n", "338939 16077\n", "Name: Kreise und kreisfreie Städte_Code, Length: 338940, dtype: object" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "students.data[\"Kreise und kreisfreie Städte_Code\"] = students.data[\n", " \"Kreise und kreisfreie Städte_Code\"\n", "].apply(lambda x: \"0\" + x if len(x) <= 1 else x)\n", "students.data[\"Kreise und kreisfreie Städte_Code\"]" ] }, { "cell_type": "markdown", "id": "62097373", "metadata": {}, "source": [ "### Inspect Dataframe\n", "~~~~~~~~~~~~~~~~~~~~~" ] }, { "cell_type": "code", "execution_count": 62, "id": "b7056a78", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SemesterKreise und kreisfreie StädteGeschlechtNationalität (inkl. insgesamt)Fächergruppe (mit Insgesamt)Kreise und kreisfreie Städte_CodeGeschlecht_CodeNationalität (inkl. insgesamt)_CodeFächergruppe (mit Insgesamt)_CodeStudierende_(im_Kreisgebiet)
0WS 2015/16DeutschlandInsgesamtInsgesamtGeisteswissenschaftenDGINSGESAMTINSGESAMTHS-FG01339730.0
1WS 2015/16DeutschlandInsgesamtInsgesamtSportDGINSGESAMTINSGESAMTHS-FG0227771.0
2WS 2015/16DeutschlandInsgesamtInsgesamtRechts-, Wirtschafts- und SozialwissenschaftenDGINSGESAMTINSGESAMTHS-FG031006645.0
3WS 2015/16DeutschlandInsgesamtInsgesamtMathematik/NaturwissenschaftenDGINSGESAMTINSGESAMTHS-FG04309194.0
4WS 2015/16DeutschlandInsgesamtInsgesamtHumanmedizin/GesundheitswissenschaftenDGINSGESAMTINSGESAMTHS-FG05166331.0
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338935WS 2021/22Altenburger Land, LandkreisweiblichDeutscheAgrar-, Forst- und Ernährungswissensch., Veterinär16077GESWNATDHS-FG07NaN
338936WS 2021/22Altenburger Land, LandkreisweiblichDeutscheIngenieurwissenschaften16077GESWNATDHS-FG08NaN
338937WS 2021/22Altenburger Land, LandkreisweiblichDeutscheKunst, Kunstwissenschaft16077GESWNATDHS-FG09NaN
338938WS 2021/22Altenburger Land, LandkreisweiblichDeutscheAußerhalb der Studienbereichsgliederung16077GESWNATDHS-FG10NaN
338939WS 2021/22Altenburger Land, LandkreisweiblichDeutscheInsgesamt16077GESWNATDINSGESAMTNaN
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338940 rows × 10 columns

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" ], "text/plain": [ " Semester Kreise und kreisfreie Städte Geschlecht Nationalität (inkl. insgesamt) Fächergruppe (mit Insgesamt) Kreise und kreisfreie Städte_Code Geschlecht_Code Nationalität (inkl. insgesamt)_Code Fächergruppe (mit Insgesamt)_Code Studierende_(im_Kreisgebiet)\n", "0 WS 2015/16 Deutschland Insgesamt Insgesamt Geisteswissenschaften DG INSGESAMT INSGESAMT HS-FG01 339730.0\n", "1 WS 2015/16 Deutschland Insgesamt Insgesamt Sport DG INSGESAMT INSGESAMT HS-FG02 27771.0\n", "2 WS 2015/16 Deutschland Insgesamt Insgesamt Rechts-, Wirtschafts- und Sozialwissenschaften DG INSGESAMT INSGESAMT HS-FG03 1006645.0\n", "3 WS 2015/16 Deutschland Insgesamt Insgesamt Mathematik/Naturwissenschaften DG INSGESAMT INSGESAMT HS-FG04 309194.0\n", "4 WS 2015/16 Deutschland Insgesamt Insgesamt Humanmedizin/Gesundheitswissenschaften DG INSGESAMT INSGESAMT HS-FG05 166331.0\n", "... ... ... ... ... ... ... ... ... ... ...\n", "338935 WS 2021/22 Altenburger Land, Landkreis weiblich Deutsche Agrar-, Forst- und Ernährungswissensch., Veterinär 16077 GESW NATD HS-FG07 NaN\n", "338936 WS 2021/22 Altenburger Land, Landkreis weiblich Deutsche Ingenieurwissenschaften 16077 GESW NATD HS-FG08 NaN\n", "338937 WS 2021/22 Altenburger Land, Landkreis weiblich Deutsche Kunst, Kunstwissenschaft 16077 GESW NATD HS-FG09 NaN\n", "338938 WS 2021/22 Altenburger Land, Landkreis weiblich Deutsche Außerhalb der Studienbereichsgliederung 16077 GESW NATD HS-FG10 NaN\n", "338939 WS 2021/22 Altenburger Land, Landkreis weiblich Deutsche Insgesamt 16077 GESW NATD INSGESAMT NaN\n", "\n", "[338940 rows x 10 columns]" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "students.data" ] }, { "cell_type": "markdown", "id": "2785f6e4", "metadata": {}, "source": [ "### Determine Ratio of International Students per Year and Region\n", "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" ] }, { "cell_type": "code", "execution_count": 63, "id": "427e1320", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ratio_internationalyear
Kreise und kreisfreie StädteKreise und kreisfreie Städte_CodeSemester
Aachen, Kreis05354WS 2015/16NaN2015
WS 2016/17NaN2016
WS 2018/19NaN2018
WS 2020/21NaN2020
5354WS 2017/18NaN2017
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DeutschlandDGWS 2017/180.1316652017
WS 2018/190.1375992018
WS 2019/200.1423712019
WS 2020/210.1414462020
WS 2021/220.1497542021
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3767 rows × 2 columns

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" ], "text/plain": [ " ratio_international year\n", "Kreise und kreisfreie Städte Kreise und kreisfreie Städte_Code Semester \n", " Aachen, Kreis 05354 WS 2015/16 NaN 2015\n", " WS 2016/17 NaN 2016\n", " WS 2018/19 NaN 2018\n", " WS 2020/21 NaN 2020\n", " 5354 WS 2017/18 NaN 2017\n", "... ... ...\n", "Deutschland DG WS 2017/18 0.131665 2017\n", " WS 2018/19 0.137599 2018\n", " WS 2019/20 0.142371 2019\n", " WS 2020/21 0.141446 2020\n", " WS 2021/22 0.149754 2021\n", "\n", "[3767 rows x 2 columns]" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ratio_international = (\n", " students.data[\n", " (students.data.Geschlecht == \"Insgesamt\")\n", " & (students.data[\"Fächergruppe (mit Insgesamt)\"] == \"Insgesamt\")\n", " ]\n", " .groupby(\n", " by=[\n", " \"Kreise und kreisfreie Städte\",\n", " \"Kreise und kreisfreie Städte_Code\",\n", " \"Semester\",\n", " ]\n", " )[\"Studierende_(im_Kreisgebiet)\"]\n", " .apply(lambda x: x.iloc[1] / x.iloc[0] if x.count() == 3 else None)\n", ")\n", "ratio_international.rename(\"ratio_international\", inplace=True)\n", "\n", "ratio_international = pd.DataFrame(ratio_international)\n", "ratio_international[\"year\"] = [\n", " int(semester[3:7]) for semester in ratio_international.index.get_level_values(2)\n", "]\n", "\n", "ratio_international" ] }, { "cell_type": "code", "execution_count": 64, "id": "cf4be61f", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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ratio_internationalyear
Kreise und kreisfreie StädteKreise und kreisfreie Städte_CodeSemester
Bayern09WS 2015/160.1142882015
WS 2016/170.1204342016
WS 2017/180.1289482017
WS 2018/190.1391242018
WS 2019/200.1471572019
WS 2020/210.1508182020
WS 2021/220.1676802021
\n", "
" ], "text/plain": [ " ratio_international year\n", "Kreise und kreisfreie Städte Kreise und kreisfreie Städte_Code Semester \n", " Bayern 09 WS 2015/16 0.114288 2015\n", " WS 2016/17 0.120434 2016\n", " WS 2017/18 0.128948 2017\n", " WS 2018/19 0.139124 2018\n", " WS 2019/20 0.147157 2019\n", " WS 2020/21 0.150818 2020\n", " WS 2021/22 0.167680 2021" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ratio_international[ratio_international.index.get_level_values(0) == \" Bayern\"]" ] }, { "cell_type": "markdown", "id": "ddb17d52", "metadata": {}, "source": [ "### Plot Evoluation of International Students over Time\n", "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" ] }, { "cell_type": "code", "execution_count": 65, "id": "10b60366", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for region in [\n", " \"Deutschland\",\n", " \" Baden-Württemberg\",\n", " \" Bayern\",\n", " \" Nordrhein-Westfalen\",\n", " \" Thüringen\",\n", " \" Sachsen\",\n", " \" Niedersachsen\",\n", " \" Schleswig-Holstein\",\n", " \" Berlin\",\n", "]:\n", " plt.plot(\n", " ratio_international[\n", " ratio_international.index.get_level_values(0) == region\n", " ].year,\n", " ratio_international[\n", " ratio_international.index.get_level_values(0) == region\n", " ].ratio_international,\n", " label=region,\n", " )\n", "plt.legend()" ] }, { "cell_type": "markdown", "id": "c816c0df", "metadata": {}, "source": [ "### Load Shape File for the Map of Germany\n", "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" ] }, { "cell_type": "code", "execution_count": 66, "id": "26590591", "metadata": { "lines_to_next_cell": 2 }, "outputs": [], "source": [ "path_to_data = \"./data/VG2500_LAN.shp\"\n", "gdf = geopandas.read_file(path_to_data)" ] }, { "cell_type": "code", "execution_count": 67, "id": "bb91abc6", "metadata": {}, "outputs": [], "source": [ "gdf.loc[:, \"area\"] = gdf.area" ] }, { "cell_type": "code", "execution_count": 68, "id": "5d2bb0f2", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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ia1eFJJ9MbCMrgTgnLTNh2mtq9jaSvSSTtFwdlTvrT52fvyIPAJVWRV/bIAgC6dkJ1Fd3otGoMOaasDs9k4waGfyTNLt57Nf/Yd2WMvIKU6MqT6R466WD/OqB5wNz7E+DOOKhv3mA5PwkBloGWZieBi6RrmwNluN2NCYNqlwzHgEqbaejv5p10++u9r1fi8ftRT2HI7WCQXYMy0SdnPzkaU1CXq8ff4eNs6PPulsHqDnUQuXuBjpbB7APO2moGTUou91e8tVaEqNcSkCjnDic1e3ysvUbT8+K/ge1Fa389Ov/CIsCAPAmaVGplXQmK6koUVOpcCBqFaR7VOgzTbRUdnDstRqUfWN/d1lMbxIasbmoPBBcZNFcRvYJyEQdhULBlksWT3tdb5eVox+c3gUoFMK0Tr+Gmi4SohgtBKCaIkHpeE0nd338tzz/5K4xZS+CwW5z8p+XD/PkH97h599/gZ98+9lpS3GHm/K9DWEby5xowFnbz1CfnRaHHQSBPrebbpWPcr+dHaKV5EwLAG77CaUjipwrmjn+amD2/t0B9KuQiV/kPd4s4Kob1vCvp4NrF6k3aslekomr207z8dEwTUGAM60x2fnJ1EfZLzBd7+POtgG2/fQVHt/2NlfesJrrbtpAarpl0uub63uor+uiu2OQ7s4hKg400VDXNeaa/7x8mPlLcrju5g1suXgR6gn8EuHk2NGZhWxOhClRT3t9D0qVgg2iGVunFUephUrb6b+be2ESpSlGhjqsLChIJdWnpOb1wB2+u7dX8ZlvXCWXFA8Af4gtImXHsMyMKC7LZPHKfCoPBr6itQ87qdvZiEqtZNHaQnrcbhL0Go7takRv0FAwP4OetsGof0JUbn9A19ltTp5+bAfP/3UXl394FR//1LnjlMFbrxzhZ995Dp937JgqtZK8lbkoBAGdQsFwj42aijZ+/M1neOqR9/jN3z6HKoAs65lim6Don0qlRKEUgg7nNCYbobGP0s3FVGlcLEgxcrbB7KjdiilBTUG7iPJQD0JhcD0EOpr7Gei1kZxmDuq+uYg/xLIRfgki82QlMEu4+qNrg1ICJylelMWBttGdQHp+OgCOETfVB1tYtKmYtsYuksw6ipITONDUNdVQIbMgN5WqvcHZnz0eHy/9Yy+vPHuARcvzKChNx2Z1MNBn59Ce+gnvKVuRx4HW00lqiCIL1xfQsr+FpuPdfPojv+L7v/wE+UVpofw4EzI0YOfgzvEROUUXliLYPNR+MLHMZ3JyRZ47Lx33Cb+CX6uk1Ghmh6sXr238g8Tm9ZBSmkp7eQfWpODbSzrsLpCVwKxEVgKzhHMuWsRvk14NOrmnoaqDhStyUSoU1B04HTqasSKHA42jD/0Cg4GjO+vJXZZFa691sqFmjFGnZkF6MlV7G06ZoyyJBgQBhgZGAhrD6/VxZH8jR/Y3TnutXTjrISmM1jNatiib2iOtdLQOcN+nHuWBn9/EouV5Qf40U/P2S4fG7UwA6kQHXUoHaZfkYVapSUeN1gsuFTgFET8iDtFPm3OEFYMqBAQGc3T0vVwHQMPbxyi8qJTlpkT22yau/9Rg8KHakMHh4QHOPacEa9sQfR1DuAOIAHM6wuPEnu2E6tz1TWMOjQSyY3iWoNGouPy64DtEedw+GvY0cWxXA+4zCr853KMPBp1WxbGK9hPnZpZ5OhUrs1LRdjnobeln4dpCSjcUYlyQRrceBswqFqwMf+0al8dDcWYSRt3YFXGX14P2xLmhATv3ffpP/PPxHdP6KQKlpb6bP//f6+POZ+Ql0+VyjlZbdTpJFdR4jg2gNKoxeMDsgUS7SEafj+X9SuxZOnaanTh93lOyeT0+jr1aQ+u/a1hlSpx4fscIDSOjzuN3FcMcylNgvKAgINOXK8qhwvFKaIlio0e0kZXALOLKG9aEzXk3UtdHgaDG3O8mvzSdhEUZ9FkDW5UHNY8ScpZl0YqH/c3dVDT3jM4jCLi9Prza0x9RjUYVFru0v9NO95F2FqSPtspUKUc94l2DNkpWnV75+7x+/vDz13noG0+HvBJ2Otw89OUnJwwL1S0dNTsJiJyjT6Lp3zV4XF6G3G5aD7TibrfRtLeZuj2NKDMMHLYN4QeO24aZd9l8ChZlkZxhoWxDEUVLc9D7AvsMaBUKWp0jFF1QMr38YQpnne34RCHkI9rI5qBZRGZ2Euu2zGP3u7Uhj+X1+OhqGyQ9O5F6x8iMGs4EQk3r1D0M1AoFBqOWouW5VHf20e70kLUkg2S/kuMzrCnU3TEaOeMZ8VCalYQFJS113WQVJnO2pQjg3dcr6Wwb5Ee/vWVGLRgbajp4/Jdv0Fg33qcy/5wSsHpZPzCasCfMNzJ/SylVOhcJfh8JG3Lo9XspSM6j+UArrYozVuSCwPuOAc7NTkQsNPOebRA0gGNic1CGVsd8jxZXj52eln7sVifZxan0z5/eGS/vBGYvshKIM4atDlobe3E5PegMGiwJBtIyLafCGq++Ye2MlEBuUSqWVBNuJQw53FhHXGQlmWjuGcQ5wwJk4aB7eISC5TnsbzxdWqGj30aHKLJ0YyG2Vuup5jTTkVechkKpoKmuC4VCwKtXoh/xcrR81Bk9fKR10ntrK9t44Mt/44e/+WTAfQ6OVbbx5La32PmfoxO+rzNocJtVNLwyGq5pStDznmbUXIMLejidC9GqVKBdn4J1ZAKfj9uPTzP1pr7EYIKdHdScEZkkCALm7ATMHgV90/wssk8gMEJvKiNHB8lMgN/vZ/urFbz41G6qysc/qNRqJcvWFHLVDWvZcN58MnOS6GwLrjmMkKKnuneAkTMe+EN2abNz9Ro1zoYBGrMmWIUKAuVNoxE+SfNTKE5OoKmyHZt1vMwqtZJ5aws42NCJTqumaH0BHQOjzXja6gPvpnZkfyP/94MXue/7H57S7FZT3sKTv3mLPdurpxyvYGUu/hOL8PkXldGq8YJ94iZBLr8fl3/iFXunUSSxYRhSxVEFchZ5egOK3Z1YzwpNTctJRNSrwD79Kv/91ypYuamUxGTpqszGA35RgT8Ex/BkZVMiiSCGy+sVQaxWKwkJCQwNDWGxTJ4YNBvp67by0Df+ScXBwEInl60ppLgsk+ef3BXQ9RqNisy8JLrbh0hckEZj12AI0oaXvDQL6QY9+wMMTTXpNaS5hXE7g/kbizl81hgKAQzdTrwBtOc8mw3nzcegVmAbcuAYcTNic+Kwuxixj/4/kDEVSgUlF82jdUcDKrWKgTXJ9LlnuNoWRRYfc5NSkorPqGLHCXNQjk6PRqFAe6CXge7hSW/PyE+mq3n63ZTRrOMTd13EdbdujqvEsWg8P07O8acDKzGYZ55jMjLs445VB6P6rJN3AjFMX88w997xp6BW9Uf2NXIsiJr0JUtzaLbZIc8cUwoAYMjumrCq6GTYHG5SMxLR92lwjLhP7wAaxysRvzjaZa2rbTAomRQKgZFBO3v3NMw4akihVFB8yTyUIz4S0y1UFahwzVQBAAgCHYvMJKpUqDwiW9xGfEka6BqhP0NN3/JEkg+KDE7SijQQBQCjCYa///HLrL9gAdkFs6OQX7iRzUEyYcPv97P1G08HbdYBgqqrI2iU9A2Pz2CNBawjLqwjwdUIauwaJLUgAZXbi88nTqgATpKQYgpKCaRnWNCrFFTsnj6hazKyilKxLrCwwz7AElMCeq2KQr2RGvvkK/VA6Pe42eEZVSQZZh3FgGPAQXqynkS1gT5fYA/6QDi8u15WApPgh5AifALLlw8vcohojPLu65WUR6F6Y29jH9kpo2GXi/JSWZ2fzvLCDFbnZ4wtJBRH9A6NYHO4T+U6TIZaH2DmrCiyZGkOw11DtBzvnrFc88+fR0W+kvoTdv8K2xAVWQJ2f3gb5nS5nOy0D2BMNlDzZi0Nr9RgDWOHsCN7Z64EZcJPW1sb//Vf/0VKSgoGg4EVK1awf//+gO+XdwIxyot/3xOVebo7hlD1DLNsUTaNB9vGJIxp8i24Z2lHLwCmqFh6EpNZS25WIkdDrPxZuCSbd/3ji/E5fD5aHeHPvwCoSwadTo1SpWDENvGOSqtTU7A8h/bqLlI25+M+2ktH49SxQkd21yOKYlz5BaJFqAlfwd47MDDA5s2bueCCC3jllVdIT0/n+PHjJCYmBjxG0NLOROu88847rF69Gp1OR3FxMb/97W+DnXZOYR92cvRwy/QXhgmv10/tkdYxCkClVuL2SBcaGg2mS9EvmZeBxi9SeyT0v4Utf/oOcOGm2+Uk8cJCWlYlkleWMe59g0mL5vx8ai1+MotT2WMbQL9gejNPf88wbY2BR1XNJaLdT+DHP/4xeXl5PProo6xbt47CwkIuuugiSkqmTwA8SVA7gZlonYaGBq688kruvPNOnnjiCXbs2MFdd91FWloa119/fTDTzxnamvvCVqpgpuQVp1E1HJqdOl5RqRQsXJhF5QxX/wqFQP6iLLSJegStkkEtHLYNhlfIADlyoqS0rzQRarvIKUnDlJuAx6Ck3GXDNjL6NzZnmtmkMrFnqJ/Vi7NprJw6Ee/I3gZyI1BgT2YUq3VsjS6tVotWO763x4svvshll13GRz/6Ud555x1ycnK46667uPPOOwOeKyglcKbWOUlhYeGU9/z2t78lPz+fX/ziFwAsXLiQffv28bOf/UxWApPgCiA5KzXDwmCfDe8ExcjCgZiggVmqAwREVhVkUrVn/EM+KzsRld8/rQJQa1QkpJpQKhV0nQhJNScayF6Ty1Ec7Ha7gGHwMHpIzMHhAUoTDdQXahn0WOEsF8Ex+zC9ag1rUlM5ouxntamQ2t2Nk45XvqeeK29cF1mh45Bw9RPIyxtbuPC73/0uDzzwwLjr6+vr2bZtG/feey/f/OY32bNnD/fccw9arZZbbrkloDmDUgIz0To7d+7k0ksvHXPusssu45FHHsHj8aBWj3fOuVwuXK7TNsyzteJsZ7p2kTDaKUwZgE17pthmaZmAJLOOTNRjei0Do87f5XkcO9w8bU1/vVGD/5xsKk/Y8i3zsklUa2l0jHDMPRghyUNEEDBuysGMwEHPxOGog24XDreXEZ+P97QjrLmyDMOISFdFx7jw0iN7ZL/ARIReRXT03paWljF5AhPtAmA0inDNmjU89NBDAKxcuZLKykq2bdsWsBIIStqTWmfevHm89tprfO5zn+Oee+7h8ccfn/Sezs5OMjLG2iMzMjLwer309k5sV9y6dSsJCQmnjrO14mzEPmTn7z95Aa/HS05+MgbT9G0dfb7IBZRlGKLbWzgaJJp06HpdNNR0jjlvSdBTNi+do3vqp1UAgiCQfF4hzWc4c61eL80OO14JYryD4bBtiINTmKXyzSZqbEOsNCWSpNHgrxmgcVcjmnVZ5M0f+x2W/QITczJPIJQDwGKxjDkmUwJZWVksWrRozLmFCxfS3Bx4b5GglIDf72fVqlU89NBDrFy5ks9+9rPceeedbNu2bcr7zl4tnLR3T7aKuP/++xkaGjp1tLREz0kqFf2dg/zxG0/w5l/eRalSsvmChZLKU7W3kZVZqZSodRRnJUkqSzhQCJCj0jDQN3ZFW1yajsLl4VjF9C0fS1fnU7wily7vzPobxzIqQaBYa2SNJgHrjhb8ooh+XjIupwffgS4cJWZKV48t630kjL2SZWbG5s2bqakZ2yq0traWgoKCgMcISgnMROtkZmbS2Tl25dXd3Y1KpSIlJWXCe7Ra7ThNONvxnojMeeIH/8Tj9vDRWzejiKC5Zzr8PpGq/U20NfWRqIzfSOL5uamsLshgWXoyx4+OzaTOykmis74b6+D0IZqCIODJ0NNc2cFsDJr1iiJ9Lhfd+1sxJehZOqymb387yRkW+jqtJPV62WFwMP+islP31E1Qx2qu4xeFkI9g+MpXvsKuXbt46KGHOHbsGE8++SS///3vufvuuwMeI6inzEy0zsaNG3njjTfGnHv99ddZs2bNhP6AuYrnhBLoaurhtUe3U1CSzo23bY6qDOYE/YTna/Y3U5CeEFVZwkFZTgot+5up3FlP9cGxu0mzWYfX5gi4Tr4oinRtb6D43GI6nbGZYR0q5bYhji02YslJoP5AM8cXGVGvHjUD+T2+0WY0nkHmXTqqCHQGjZTixiT+EE1BweYJrF27lueee46//e1vLFmyhB/84Af84he/4BOf+ETAYwQ1YyBa5/777x/jkPjc5z5HU1MT9957L1VVVfzpT3/ikUce4b777gtm6lnPmUXHnvzhM7idbj7xmfMpXZAVlfktiQYMZ9XKV2uUqNRKfD4/qZPYJGMZncuP3zfeTq9SKUhN1NPXNX3AgUKpoHBJNjklaeSfU8hOz+wOUvAD76lslG4sYq0+AYOowHVRLqqk05+N9x0DlF42n6QMuedwLHD11VdTXl6O0+mkqqoqqPBQCDI66KTWuf/++/n+979PUVHROK3T0dExxjxUVFTEv//9b77yla/w61//muzsbH75y1/K4aFn4XV7MVj0LFg/j4Xr5zE8YCclK4kHfnET//2ZP9PWfDqL02TSkpudgCAICIAIo4FlAihEEZ/DgSCCKJw4f+ICQalE0GpBEPD6/NQd7z3lXLYOjowxixSWZdDoceJxe1mYl8bx/vh7+PkME3y8RZH58zLoahtg/rmloBJAIeDtc3D8rN3CvHWF1CX42eNysCwhmfeGgq/jFJcIAu+KVrYMGqk0ehjyeHgX95j3P3AO8NUrPySdjDFK6KWko28ClktJxwgetwelSolCMf5DYB0a4VcPvkRfWz9u6wgNlW34p4gMWrIyn4rX9+F1jQ/zXHH1eioOjdpyLUlG8hfl0N5jo7dvbOC4QimQtCiDtr44ThYQRVYXZoJfxDHkpL66g+Ur8nBaVOx0Doyx7efrjZiP9NPbcbq0g/6yIrIEDQOCj16Pi1737HMIT8YiowVN1QBt8wz0uCb+uf/6rZtZmD8+EznWiGYp6R/suRCdaeY+NKfNy/9b95ZcSnouotaM9Y8MD46w962j1Bxqoqd9gIo99QwH4MAEqDjYTNaahfj7B2irGru6PfSv3Sy7egNHD7VgHbBTsaMWQRAoW5YHOi11x7oRGXUMJ6Nk+piZGEYQTvUiWJCbysKlObQlCVTZx6/omx12SpanwBlKILVhBFHrJsEvUpsyu0tonEmh3ohzRyupa/I45Br9fWTr9FiUagQBTCjRekUGOq0QB0pAZmpkJSAxDruL3W9WUL77OK3Hu3GcKAPdUN2O1z3zOJSOpj5UaiXLr1zH4X+fLkY3f10pVW/up+yCldSWjz7iRVHk2OFRE15qZgLKFAudnVaOV7aTOj+V3qHIFDiLJjWtPRRsyKWqdfIqoF0uJ/PnpWPMT8SqBf2Ah9qdDeSVZUhS4lcqSnRG9q1Nodlr5VxNIs1KD9r9PQycSBg7WZT6XzY/m9bNk07QGCQezUGyEogSHU291B5uprdziOHBEZRKBb2dg7z/78OMDEemjaPX46PySBtlF6+ht6qB/rY+Wqra8Dg9dB45RkFZIU1nNT/v6xxicWEanZ3g94sUWEyzQgmIgoByxE9hRhKNXRPb9m0+L/uzAM8geEChhk2XltEkuCFClT5jkX68rElJxXGsn76OLhwdQ0wUD3Xwg2Mc2nWcFRsCL1Y22/EBvhDKRkgRfiwrgQhiGxrhP8/s5fV/7Kb+6NQFuSJJfXUHRksii+bncPStIygUApkFaXicEz/Y6g41kZCdwtCQg6p9jcxflUdN23StyGOXzLxEuvQ+VGYNmklKJkyEH3jfORgxuWKVgwP9aAQF83tcY3wkE/HYz1/l50/dJZePiGNkJRAiPp+f2sPNVO6tP2XO8Xl9dLcO0FTbiXsC56wU2Ied1A47WXjZOrRqAY/DyeDxTkBF4cpstOuMHP9TPV6PD7fTg6+5m3mLctBaDPS2DLK6MAMXfmp6+3GPeBEQEE+USRBCWPlEEpVKSenqHKr6+rCNuNnXJJ0ijjfcop+jRWo2LJ5P/eu1+P0Tx4/UHGmlYl8jS9cWRVnC2EQ2B80hfD4/rzz5AU//5j90z6AFpFTUVZ529c5fVkhWgZZd17aA0EdRYSbW73bhcXvxef0cP6OOvt7vpf0uNw7D6bILAgJahYoSchjZLtByILbCSOetzWFPS+D9lmXG4gN2jAxQdGkR+S4lvTU99LYPnno/f0Em3mILKVmzM2JvJoSrgFw0kZVAkNiGRmis6eSJ/32Fwx/USS1OSLQ19zH4WQWc2Mo3pPey4FvZOH4zwEDX6dBQvUmLoBdI6zfSd4YSEBFx+j1U0ojyPAXzU0qofSN8vWxDJuaDn+ODhhEbDQAlakqWFZMmjEaylTuH0bhHGBwYITt34hIwcw0xxFLSogS7alkJBIAoiux+o5Jn//g2FSda680G8i7Mpl03tv5LdW4XPChicSdgcmpBhE7LEF3KqX0CPtFP6/I2EiqSGOqIjKM7WFqre1CYBfyz5O8lOYLA8REbx0+81CuVFBx3Ik5iKpKJD2QlMA12q4P/ufev7Hy9QlI5dEYNfq8ft8tLekEyKVuSwS7S+EYrjkn6x06HbdEkse8KAavOiVUX3MPc6h1h+Q1ZDP0qNpTA8KCDxCwL/cOzs9aP1Dh8Pg7nCTxfUcvi5fnT3zAHkM1Bs4wRm5P7b/oNdeXRK2WtN2kxJuhRqBSMDDmwDTooua+EnkwbSq+Cov9oOf5OC0PPDKM1aNAaNDNWAi2Zg+EVHqhSN2HJSMfaJX12rUqlZNAWGwpptiIi0NYbW74gKZlJJdCz7482shKYghcefTcqCsCSYsScamCw04b9IQ2Fu1IR+/2k6JJpeKWZrkc6sA2MhnOedEF78eFyzDzyKLssjWp9+L+8br+Xgg8bKf9teJTAaAzSzL4YXq+P1Xm57G2Wo4IiSWNHPwM2B0mmiavQysQ2shKYgtIluWEdL7ssDeEmA1azE7VXic6pIuGoBmeDA32pAcfbLjKfsFC189jYG88qd6xSK0kvSkalU+Kyuulvt54qRR0opksTgcis4Mr19ZRdVkztazN3EheYdSQooPv9o1jOWUTt0MxW9FUfNLFmcwFH2rtQKhQ4YiRkdzbROTDMdx97jV9+4TqpRZGcM7uDzfT+aCMrgSlYtrEUrU6Nawb9dnUGDUk5FozpBpQmJd2Hehlot5LyDwXqQQfDfSP0u72MpJtxDDtx7R2do7/z9INZoVRQtDYH5Vot+MBr8lNZ0oFH6aNfOOM6n5Il29JpPBjYitdo0VG+JHKrY6/o4+jCOlZml1H+6MySzJIGh6n6Tzm5i3I5bp25SUcAanY0oVOMZjOUbsihvLlruttkgsQ2Ir35LxaQzUGzDK1Ow/JN89jz1tGA70nJSSBtWQqix4+r381go5X+Tuupqp+tVV0kpJkouLuA2nk9NGtdIAoIohYRkYL+FDIPG3Fl+zle1MtB3US1bsZ+UPxK8IwErqhSChLpUEc+t+FgQi25CwvorLJNf/EJVli0CEN2eupG4/vNi/LwWUN/wIj+0dQ2HcqQx5IZj0ol/17jFVkJTMPaCxcFpQRSlyaDRqDmlcYJ3y9cnUPzbSO0GM4IzRQExBMNAZpS+2m6KHgzirnMgr7NGpCT2OOIXkXMtE3agJTAcosOlwCDhxroqDud4FX1z52svH4jB4fDs9IUQyjKN1dIMusZCDKiyu+fSyX2Jsc/g+5gZ98fbaRrYhsnrLtoMYXzJ+7ulZRpYcE1JZTcV0LpOaMhcnVvNFH9wvEJr593fgEVn+1l0BD+YmQHrm7HuVWPwayb9tqOY70U9CSHXYaJcCZObMrRq05/9DIMGmqf3UnD0x+MUQAnqXlhDyZ1eFaa/aLsE5iOnIJENEH+vg/UtdHaMxgZgeIInyiEfEQbWQlMQ3pOEtve+G8e2/H/+Pz3r6d4Ufap95z/rWHfNa1oWgXEE20MJ2v2kr88i/KbevBHaNfsVfkZMjgouHasM3v+pUUUfLOI3EVj677n7jBQ0GEBUSS/wwwRSqiq9rWw+MaUU3WGTjJv2I5JrUSnUmCsap60Ng3A/PMXY/OEZwXv9MydvgAzRUAgtzSZsvy0oO676xfPYnPIvoF4Q1YCAZKRl8KHbtvCj566m9XnLQAg8dew6h9ZVD11jOM7pw4lHb4Z3KrImyKaV1pRKEZXE4Wrs9l7YxvlJe0MfEpEoz3D+tc0wsBnKim8e4Tkv7lOlY4INyIih7Nrmf9VM4k5o32KlQLU7agm/Xg7Rd0DtNVM7qQuWlXESFJovWxzi1PIKkyiZFkWg3Y5cWw6yiva0SqUjOiD+7y29g5xvD1+q82Gg5OO4VCOaCMrgSAxJxr5weOfJSMvmY5jvdS+2RjQfYZHfaQNR74xd0fiEGVXjlZ01C8ynnq4dyQOYf5uOmUXFKBQCFRXdbP4nIV01/fAuZGX66iviZGP97H0UyksOTeZhOWptFW3Ub9vYtPZSXTFmdQMhfbgVutU1HptHOrvZUQOEZ2UpUuysRSZKFyQyoGeThqtg6xYmBPUGOX1c7tgn3iiiuhMD1GCjGFZCcwAQRD41cv3sXzT9F2VijfkUvTfxZhyDah80fl1uxeO/utNGmtiacjoY99/dTKyTY/hh2noyxJG33gvOn2ER3wuDppr2b+yDu3WwsBuGgg8smgytBZtyGPMZjRqJUuWZLOnp52uERtVA70ggMfvZ/9QB3npiZTlp7F0XhbJFgNKhUDe/BSWzstiWVkWxTmni8ftrm6W8CeRHh9CyEe0kZXADDEnGrjnRzdOm1DWXz/E4Xmt7L2pg47EqRt0hIQogiiSYjOiPjTql/DtcbL2H9msqBq7mnOrfLQk9+PUj9pvW3e1QJSLgBlGAgtMa9hVywqLdsY+i7TsBGr646fUtxQsLM5gb8/EJjm3z0+tMMhhVw97rB2YsvTkliVTO9jHHmsHu4c6sCSeDkbYW93CgE02ucUTshIIgezCNH7x0r1867e3M39lwYTXZF2RETF7+5noPRqKv2vA95UBat5oBKB+Vys1rzWg7RvvjV7z1wSOPV6FOdVE4WcWgiK6K5BqfReJy6YvP+y0u6j6505WiMHZp0Vg/ppcek1+rCNy/aCJ0GtULF+cQ7Uj8JDkmsE+qgfOsvufEQvh9vp4/v3yMEkYf/jFUP0C0ZdZVgIholQqOOfK5fziha/wp/e+zZarVox5v39edB5ADrUbQcGEUTbi2TpAFOk/V6DnL2l0PZHKvhnkJYSKR/SRcd/8Cd/Tpukxz0scc67qzSOsMqqnHVetUbFgfT4LNxewr7NLVgBTkGDSs6u3jUHXzH9HKkGgs2ts+ZE39sd3n41QCMUfEGpXspkiK4EwklWQym3/fdWYc41pUYqWEAR8dxso+GYRpZvHlvW1ZbvHXVufPzReOUSZA6ltLNi2gfkPrmb+A6tPnc+5oRjHw1mYisZ2rKp8bjer9VPvWAoXZbC3rYO9civJaUnJMoU8xtqUbDr7x/qUtAY1LX2DIY8tEx3kjOEwMzJ8elWl0amxqqKXSdmY1gdpYM7RklRnZrB7mLzFGVTmdXB2qYlYYX9BB9oiNbkkUXjbfDRFJqrXW3H43GQ9vBDvp8pxdo4m1y349XoqSwfJVSaQOGLm6O8G8XvG7nxUOrl8QaDU20LzlaxMzeTQGe1KM5JMJGYb2dXbRvPAEHkpiSFKGH/4Q+wsFsq9M0VWAmGmeHEOGq0at8tD9uJ0eumNugzDOhe5d2WQeTCd+gsHom7vDxaX38NxuuFGAOcpG3O10Enm46UUVutBCfuLOsEHNp8TVF3kfSUN/a4E6t8dlFD66VmxOIeGxj6G7E5y0hJITjRw9HgXPglLLSgVAjqlGpiZKWhBUgp1VafrWqUnmdBl6DjUO1qc74XDR1mem4lJN7cis0LN+pUiY1hWAmFGoVCQnG6hs6UPXaZ0X4CqvC7Ik2z6sNHpHaKzdOKoqhZ3D6zqoWx9LsZeA4OH3Ih5PlaXJY2+f9BN94A9muKOoygrmYaRIYw5ehxOkWOuIbAOsWFeNgODIwwMOxiOcgXOouxkzMl6dve0TX/xJCT4tVhKMnC6vPQN2knPsYyJMHrpcDWf2bKO0jmmBOIRWQlEgG/8+hZ++LlHadzeyvLFudgtbkTFqNliROuhz2SLSvbwXKHW0woJwHljz+dvzmHwNSXuEyUnEk06CjarUPUZKD/Uh9sb+b+BXq+m0z7e8b5rcPSBaUxWs7woh4qqjojtDJYvyEFUwcigC9uIi6PefugJbczdQ2f4XPTQ1jO2HtYVS8ooTZ97zedDde5K4RiWlUAEmL+igD9s/yYvPPIurzy5k972AbIKUjAlGFD1u9B51HT+PwUOjZy9GkmadW2UXJqHbZ8Jh8tD6jluanWNYIalLGf/vsj2FUgw6hD1AkyxGbF7POzqbWPtomwqKsLjzFYIAgadGpvDzYrFOezsHV3xpxuM5GZbaOiJbHJgmtnIN688P6JzxCp+QuwnIPsEZg9anYYb776Y6z97AW6XF71xdFv8r7+8z5vv7qdBI0evRINGfQviOaBEQZNweqXdmduE8oAhIqvvxSWZqPRKjg71cKC3M6B79va0s3FhDiN2N4JZgVpQ4rZ6MJg0jNjc1DYHtnRPTTBCqopehw2DX02f97TNv3vETvdI5M1j1y5fSKrJGPF5ZMKDrAQijFKlRH9Gw43UzEQUGfKvPZoIAvgZ+7DvVw2yfGU+B/ZP1LRnZiwpzUSlUbKrrw1xBtUudvafsNGf6SJwwbKUDBYVZ+DzidQ0TS1vWrKJA7bRHU5Srp76oejngAhRSI6MVcQQo4Nm2k87FOSnUZRJLUikZXkEy0fIBExrXj36iqSg+w4rFQILF2XROmJFr1KToTLgHPGgVClGTS9h/h4f6Rt9qK9JG+1rMS8vFZfbh8/vJy3dhNPuoa17iJyipFPXArTbQq+7NBP+uvsQX7xwI2rl3AvXldtLykxLRlEK7U3SKgHBB0q/Aq96bneDGlbZWLglh4P/GQqqNFHpwrG1duo5EW/vIKLpGPu6O0gu0HPE0UuiTodGoaBvuI9Mj4HEPBMHAzQ9RRq1UjEnFQDEp2NYzhiOMma1ngxdoqQypA8Zyf+qnWUHU1i5KyXqxeNiiarEGhZeoSE/KwGlYvqvgyBAVX/4TEhBIUC/0wECDLqcdDtGGHA5qfL3UzsYO3X8c5MSpBZBJghkJRBlel1WkjWhp+uHQleyHf3nc+j75XFqHtjPil/qyO8wkzagj1iHsVimwdBMz+YaVm6cPqRRFCHfkhh5oeKYZbkTt2OdC8RjUxnZHBRlHqz4B1XW1ukvjDCVC/vR/jaFheUlDPyxkd7bR1eSq7+xioESH8NmNz2Jc6wksE8gPyuB5o7T5jqdRkVhdjIej4/jbX2olAra7NHpvxCPaFVKPr52mdRiSIZcNkJmWqpjQAGcxKX1cWhNH6tHCul5aFQJVP3oAAAavYaUx4qxGlws/7uZyhvsOHSzO8GtMvcIYg5s6FiJtcuP2+XDmKBlV28biFA8LxEfIk1W2bE/EQpB4GcfvZKyjFSpRZEJAlkJRJlrctbxZNM7Uosxhqp1Q6jUSrxnNHN3O9wY7mwiVaeijV5yzinmWOHsf/gJAgylD3Dg+In4+pOlnwSotw5KJVbMo1YqeOjDl3HxwlKpRZGUeIwOkn0CMozovMy7dsH481YHQ93DaI3aOaEATtKoamTjytHVrFGjZsPSdDauTEU5h+Pfp2JtYS7/+OzNXL1s/GdorhGPPgFZCUQZvXL6xihSUHOzh/lXT/wl7m7oJWF4bhUCqzFVsHaDifR1VmoTj1BjqmDVOiMLclLQqVVk6I1Y1BqpxZScj6xazKO3Xc+CzDSpRZmTPPDAAwiCMObIzMwMagzZHBRlkjRmqUWYEJvBjSonEUOCHqVayXDv2ESjwjojh1dFt9ql1BxXHxv7WnMMimFBVjadL7vRFaixetyT3D032FJaGFBo7VxBCnPQ4sWLefPNN0+9VgaZoyErgSiTqDFILcKkVFxpw3x+ETqHirw3RJpfq8fWb6dgdT4N86XJPo0lFKKCkv2LaDg+gNPtpnDYRHF6IvsGOwDwzsHw2gPN7Vy+pExqMWIGKZSASqUKevU/5v4Z3ykzIxrtEiUaBYBD68Wh9UISNN0Kyk+kU9KUwLH8ITzqub3iBchxZVBVdbqQW2NbPzneREr8JnQ6NUeUfZLUfpGSt6qP843Lz0MR442L4g2rdWzfZq1Wi1Y7sUm2rq6O7OxstFot69ev56GHHqK4uDjgueR9XJR5v6dKahECxqcSqS0ZxKOeeyvcidC7dePOtXUN0tFjpaGlj2KriU2GuZUopVQIyP7y04iczhWYyXHym5aXl0dCQsKpY+vWrRPOt379eh5//HFee+01/vCHP9DZ2cmmTZvo6ws8g1zeCUSRTsdATOUJyATOvOEiXEd0wMik1/T020gsME11yazjvkvPndNVQ88mXOaglpYWLBbLqfOT7QKuuOKKU/9funQpGzdupKSkhD//+c/ce++9Ac0pK4Eo8qvaf0ktgswJFKKCbFc6Gp+GIY2VPvXgpNcu6V7IkdcH8IvTP93tbQ42Z+fQ7R+hYXgQryiSoNFidTsRENAqlTh8syfp7o2jdfTbR8hLTmBTSYHU4khOuJSAxWIZowQCxWg0snTpUurq6gK+R1YCUeLtrnK2d1dILYbMCcqGiqh4yQa4KJuXQ5ouj4EeJ5YkLSNLe2jVdJHpTiWxMpNDlYH3YmzvHqK9ezSnIj/JSGZWAlXVHaSpVORkJXJMMcwSUzIiIpVDvdOMFvu8dKSal45UA/D9ay/mo6uXSizR3MblclFVVcWWLVsCvkdWAlHA6hnhf6ufl1oMmRMoRAWeGh0wGvFUW3f6YdzWCVRBWkoxHf0jtIkzb8bbO2Cn90Sje5/by/GmXrLTLDTXdaNWKUgt1dPrnD31mb7zwpsc6+7jkxtWztlKotGODrrvvvu45ppryM/Pp7u7mwcffBCr1cqtt94a8BiyEogCvz/2Gv1uOcRSCkQRSuz5aLxaVG4VPrUP7zENVbVTP9x7+iLThrGjZzTqw+P1s1SXTK+zLSLzSMXjOw/y+M6DfHLDyjkZNRRtJdDa2spNN91Eb28vaWlpbNiwgV27dlFQELhpTlYCUeC4LTaafcxFlKKCY8+78Yuxl+jmG/FKLULE+Muug6iVCr522blSizKreeqpp0IeQw4RjTBdzkGODDZKLcacJdFnxh+DSVxlxensds/uxcGfduznL7sOSi1GVBFFIeQj2shKIMLEcnLYXMDskbaBz2RoLZo5kVi29ZXtvF1TL7UYUSOUHIFQexHMFFkJRJh+l9yAREoa9W0UFyRLLcacRRThnr+9xA9ffpue4cj4WWRCQ1YCEaZPVgKSIgiQWBp7H/ORAafUIrDakkyG0Rjxebx+P0/sPsTFP3+EH/zrLYadseefCRdyKWmZcfS5ZSUgNS3pLaw8J11qMcZwvKmXNUkzL/oVLEUJCcxLTASg0GJhQWISjj/tx/iz3WhVwVWdnClur48n9xzmi397Ca/PH5U5o43sE5AZR5/LOv1FMhFlQGWloqCC9NTY8g9ovdH5+q0zJZO+o5Pk99rZpEnE/Nej2L/xOsPHesm6dgkub3QzmHc3tPBWzfGozikzOXKIaIjYvU5GvG7SdBZsHgdGlW5MLRU5PyA2EBUihvPtaF9U4XLHSGhmhBfgCkHAqFHT/eB/8DlP/MwvV465xtU8yOoFxZTbh3BHqZxFpsXERQtKojJXtInH9pKyEgiB3b01fO3QY/hEPxqFCrffy5rkUpYmFtDvGubSrJVydFAM0arvZNmmJRzYPvMs4HCQlWbBlaFgx0AbkSzBuV6XiP25StxpZuwtAxNe07W9DrbXsfzi+exdE3ytmpmQbjbN2kY0oZp0pDAHyUogBPb2H8Mnjto23f7Rlda+/mPs6x/tSPVC2x7JZJOZmNqcWhYuLEOfLnDgHWkUdHffMFYTEVUAAAq3j4FDgWUkd75ZwzmrL6Ta6KV3JLKlLI60dfL4zgPcsnFVROeRAjHEnYDsE4gztIrY7BcsMzlOhZuuFY3013skkyE9JfItRhN1Opp++J+g7mn68VssaIpO86DMhNhsszoXkZVACNxefBHLE4ukFkMmSLLs6TROYh6JBsm5ZnwRTmL2iyK5378UhSa4zX5jceTbn24ozuOShaURn0cKREZzI2Z8SCCzbA6aIU837+CJxu30ytE/cUeLqR2DLpURpzS7Ac+gB0SRFUkZWL1u6m2DYZ/D6nIh6Az4g3CCq806cgb8FKrM1Bn9dNnDn9x1yaJSHrz2klnbiMaPgBBC1q+cMRxHrE4umT0KQAI7pJSMKJ2UXhj5Fe9k1DZ0s9mcg7fbTRYG1iWFvyVlttlE6/ffCOoez7CTxp9tp+lHb6H9/ruc4w1/Itk5pQVY9OPbdMpIh6wEZkg8ZwIbBSM5Qg6CKFDqX4DYUMQ8z2KpxYoqbQkdzCtJkWz+8oo2mtsHKK9oo6U6/M1lHF4vauPELQkDQfT4cSTP/P7J6LLO7pBpOVlsDrEyqZhPFV+CUpj4VzjZeamxYKGvJpX9h704j+XzfsUAXTY771X1kiJMXWNHEAWK7Mso9S1CiyZKEoefDFcK9mcs1B0PvBl3JEkw68M+ZqnKgHvYiVKnovCLW8i9cQWWBRkYcxPRZ46GgmY9eBkFd59D4qLMcbbovI+vYr+1P+xyPX+oKuxjxhLxWDZC9gnMEJVCyR0lF3Nj/maGPCP0u4f5w/HXOdBfz+rkEjakzOfhupdnNLYWDYrWIjKTtNhMHfSE0N3qbBJJotY5WrdmwDG2fs10TqkS3yLeP96FAGxcWkC9EHgf01jCq/CiUikgOoEw05KcY4KB8JoW23BTctc5dOXreW9wEG2ZDm9JARqVErNGQ9pfqhhQ+TluceP/UB6Lb1lOr8dFkV9Dxw/fwrM0DYbDrwTaB63UdvVSlpEa9rFlZoasBELEpNZjUuvJMaTwy9Wfods5iE6pwSf62XbslVN5BMGQ5y/i/f5BGvqhICkJ8mauBNKFdNQDGejNXvApqW+fPAZcx+S22hQhhX21gwCsLUynXiifsUxS06ceYt6lydS+5MUXAzVsBF/4V3/twzbaLcDgaLG2k6UhHB4vDo+X/huK8A4Onrq+cnD0gd+FnXNuX8c+Z+T8XU/uOcwD11wUsfGl5GSUTyj3R5ugbBYPPPAAgiCMOTIzpy6C9de//pXly5djMBjIysri9ttvp68vNrbhkSBdl4hFbSBJY+Lq7LUzGqNb0XHq/00DQxiFmTvousVu2gbsvF/Zz/vVPbRPYZNVTlLHQCUqcben4fSeSIhr6iFNSJuxTLFAnbmBhVcaUSmlN9v53dGt3QOjlT0nY0eSB6cncqU1qjt6EGOw0U84mBM+gcWLF9PR0XHqKC+ffEX4/vvvc8stt/CpT32KyspKnn76afbu3cunP/3pkISOF76+6CPMM2cHfV+qOLbipbGniHQyZiSDKEJxhhGTZnobvtZnRC2qKaKUZCEZHToKKSalfyF1Pafj6mOxU9dMqE48RsF1Alnp0iYuCQpBmiXgJERaksOtHdzx2DP87PX32HGsCb8/dn72uUjQ5iCVSjXt6v8ku3btorCwkHvuuQeAoqIiPvvZz/KTn/wk2GnjljxDCnXD7QFda8JEpquI9p6xxuoj7T0oOwTWFi1DpfcwNKAgMUHguPoofqY2ZwgC1BvKscxXsNK7iB3VvZM+xN+vGECtSKXFPwyogQQasQNj48WX56TRJVYE9DPFOo36dhZnL6WjW7poL4/LF/ESErHGroYWdjW08Mj7+7jv0i186pw1UosUFuKxdlDQO4G6ujqys7MpKiri4x//OPX1k7eO27RpE62trfz73/9GFEW6urr45z//yVVXXTXlHC6XC6vVOuaIR7qcg+zsrQno2jwhj/66VN6v6aa+f3Dc+z5RZFd9F+9X9lPe3st7VT0UisUBy+IX/NSpK9g4b2ozjmcKM4FSENCrVHhSA1Nqsc6S3gUYnsvnyCFpi/x16CJbqyfWaeiVLns73MRjdFBQSmD9+vU8/vjjvPbaa/zhD3+gs7OTTZs2TWrj37RpE3/961/52Mc+hkajITMzk8TERH71q19NOc/WrVtJSEg4deTl5QUjZszwXMsuHL6pQ1DUoppSz2IOlXvpdwT3MPAMG4K2Ivh1M8sCVSsULF+mIHNRH/1i+KNGpKAitZqSxYmSylCYm0KrPX5zTsKBJkpNbaJBSCUjQnQqz5SglMAVV1zB9ddfz9KlS7n44ot5+eXREMg///nPE15/9OhR7rnnHr7zne+wf/9+Xn31VRoaGvjc5z435Tz3338/Q0NDp46WlpZgxIwZXunYP+X7alGNtzGf96t6p1yBT4RJo0FrdAedou5hZqUSStOSaBfbcSB9W8RwIYow1CVtnKg5Uc6eNWrkQoxSElKIqNFoZOnSpdTVTRwvvnXrVjZv3szXvvY1AJYtW4bRaGTLli08+OCDZGVNnC6v1WrRasOfrRhtUjRmel1WLFhIFlPxKTw4ceLHR6Ijh/KmIayumWVQurxeRlTWoJcOXmFmSiA1RWD2bNpHEQQwLHdDk3QydHdaWZ2Xwf6BLumEkJib1i2XWoSwMbqaD8UnEEZhAiQkJeByuaiqqmLLli0Tvj8yMoJKNXYKpXJ06zdbQ8TO5AulV/OLA29x9JibWsdJM4zixBGaHVoQBGxi8ApkQOwHkoK+z+9VoFVpcMVKhlWYqEmoZ+WGZRzcJdFDWGQa1/7sR6eePelKs94xfN999/HOO+/Q0NDA7t27ueGGG7Bardx6663AqBnnlltuOXX9Nddcw7PPPsu2bduor69nx44d3HPPPaxbt47s7OBDJ+OFyq5u/uvpp/nai9vZUW4dl5kbDlYXpmIleId5CjPL1NxR201fdQYlrqWxFM0YMmavEczStZtMKDBxcA7vAgB+8tq71HaFv36STGAEpYJbW1u56aab6O3tJS0tjQ0bNrBr1y4KCgoA6OjooLm5+dT1t912G8PDwzz88MN89atfJTExkQsvvJAf//jH4f0pYow/7tvHzubI+jGcpp4ZBXRrbKnAzB46NrcbhcI/q6IZze/lcrBVmuRFpULg6JD88HvhUBX/Lq/ln5+7Oe7LSYiElmcR8/0EnnrqqSnff+yxx8ad++IXv8gXv/jFoISKV16vO8bjhw5GXAEAmDxJiMqOoB/INnM764uy2d0QnCIwaTRkJ5gYVs+ubO+URUpEMZGWtsGoz+3zi6wyZfD+UGAtIGczHp+Pbqst/pXAbDcHyUzOiMfDl15+OSoKAOC9o310l2cweDSHFCHwksg9/l7U+uDNHza3m/R0gU46g743ljmSfhSdXroQxerKDrINJsnmjxU0KiULsuK7FEm8Mns8MhIw7HJR0dWFWqnk3cZG3L7o1oARgaKUBPrEiVeSgiiMbi+F0U1mHvk01St53z6z1fxAn0B+egHttGEWTAyIgzMaJ2bwCyxvWsKBY9Ili7m9PjIGlCSnp1ExFL5qsfHG7ZtWk2oKfxObqBOH9iBZCYTArpYWPvfCi5LNr1OpSDKrJgzdTBISsTenkZWsBxFsljZcvRa67TN/0FR29kInKIRURFFk3jLLjJzTscDCgTKshxUcaJE2WxigpWMQw4AaU64am1ealpdSY3PNkqizUIvAyf0E4gO/KPLvmlr+uG+fJPPnJ1rIzRNooYF6YfwuQIcWa0MqbVYrzYMnH9IqIDwrTb8oolYq0ApaaTxZYaDD1Am22LE/jzg9zPelUae2YvXMkgdiEChmSbRBPJaSlpXADKjq7uFLL8+sYUw4GHF7aRPa8OAZrRIqlCLiY5B+0vzZtHeINFojm9rl8fkZakpEzOuJm2ghUYQF1mK0w6P9hY/aYyv9ra6hB4tJx8J52ai90K9wcXTotOnOpFKjUigZdM+erO2TGOSsYcmQlcAMmJ+WylufuoNf7PiAF6uroz5/78gI+QNlkNyPajiFnQ2jJg2loKc6inV9slP0NMaoAsh0paHenUJvzwhOtweFQoEAVLrHV0WNJaw2J9aDo7s7g07NOfOyef9EFdoVhnSaG/pYXJJDtaOPPtfsUQZLcwKrTBzrxGN0kKwEZoBKoaAgMZH/vfIKlmVm8tA770S9xv6Blh5ogTMzj31RlqG9z4HKoMQrRL8pylRYvCbSWjM52HSmvT/+8nJHnB4qK9spTjCgUAgcaWwFYPBQK0qFwJrlmahRsG+wE88MOtjFCh9avpAt8wqlFiM8iEJodn1ZCcQXgiBw++pVtAwN8eeDB6UWJ+p0DdvJVxgYFmOnCmaprYDq55z0h1iWI1bw+UV6B8bvXHx+kdqDox3oSpen0TpiZbEplYrhnrhyLl++eB5bP3wZCkWMbinnAHKeQIhUdfdwoH121NcPlnnpSbj8TvKEPBRibHyUjpmaWLUlHbUqNuSJBm2He9A0eDh6sI1l6lT0SmVMdSqbjEyLia0fuXxWKYBZX0paZjxPV1RQ3jU3a79UdvSi7ypl72E3OYocqcU5RW1+DUWFyVKLEVU83lFzUEVVO+rjXjYkj/49CkwWlDH6jJ2XkTqriscBp/MEQjmizJxVAhVdXfzonXcZDKKRi8/v593GRr7/1tu4vF7+duQIfzl0KHJCxjgiUNM96oj2ETt+AYNPT1/fiNRiSIpn0M06VTqaDj9FpuCrxkaD94818tC/t9M+GJ+5JrOFWaaGA2deSgrvNjaiV6u4c+1a2qxWSpOTEQQBj8+HSqFAOBH72DgwwKP7D/Dv2tpT3b/+XVtLjz12o0yiTV21kgzzApzZx/AiXVVOgH71ELkXG+h7WlIxJKWuYTQnJCPFTP1wbIXCnkQU4S+7DiKKIt+66gKpxQkLcnRQjOPz+3mpuhq/CMsyM7ht1Uruf/0NfrlzFwAXl5TwsysuZ2dzCz/cvp3Pr19H78gID+/cNa7zl6wAxjLscjPscrMoxxIT7SeT21NpnCXO4VDo6htmU25uTBepq+qYZX+n2HfHjGFOKIEum40vvvQvrC4XdWf0Q1YrxlrD3jx+nMsee4y71q+n1WrlW2+8GW1R4xq9SkWyNwmLMpF2sQX3DLuYhYRfYNHRpRw4ODf9NBNxrKYbMkRiNavvWE8f3cM20s1yIT0pmBM+gVSDAaNGM0YBABP29e2y2fnuf96KlmizCofXy/uVA+w6Yieht0wSGYyijiOyAhhDcVFqzCoAgCGHizsee4bK9vj/u500B4VyhMLWrVsRBIEvf/nLAd8zJ5SAUqHgU6tXSy3GnMLtkyZ5SZLdR4zT32cfDRuNYY739PPR3z1JdWecV1KVMDpo7969/P73v2fZsmVB3TcnlIDN7ebv5eVSizGncHulUQIehZcEs06SuWOV9u4hVhtjvyyDKMLjOw9ILUaICGE4gsdms/GJT3yCP/zhDyQlBRcNNieUAMC1Cxdyzok2mDKRxaBWY84dlGz+nAsVKJVz5qM9LUqFQLs/PgIZ9jfFrgM7mlit1jGHy+Wa8vq7776bq666iosvvjjouebEN8Wk0XBxaQkPXHQhJo1GanFmPfMX+umeYR/jcFBraWD5ObFTJjrSFGZNnhiXYNKRtyyNettg9AQKgV7bCF6JTIlhIUzmoLy8PBISEk4dW7dunXTKp556igMHDkx5zVTMieigk7QODWFzz71a7dFGi1ZqEajKrSI1KX/CujvxTn5mEm6Pl86+YVbMy6aivI1589Koa+klPzOJ/nYrGXmJaI1qqhikZTA+7Oy5ehPfvu4iVPG8iwtTZ7GWlhYsFsup01rtxN+plpYWvvSlL/H666+j083MDBrHv+3gWZeby7fPP58lGRlSizKr8Q1JH+rnUXjJWzgL2hWehUIQGO6x09NqpTg1ifIjbSBCfW0PmQYjbQ39OF1eHIMuVH6BIffUZgQp2WzOZhPpoy9EkSWKZM5dUCStUDGCxWIZc0ymBPbv3093dzerV69GpVKhUql45513+OUvf4lKpcIXQMvbObUT0KpU3L56FecWFnLpY49JLc6sRauPjWwZb/LsqbdfmpuKCCTotBwpb0UAmlv6T7kRBaC3z3bqdXfvMN29w2xZmoOgFNjj7cIZ5R7YZyMgstCcirbTj8/ro6a6Db8osrogBeuwkz3VjdTUd7OgJI4XaVEuJX3RRRdRflbQy+23386CBQv47//+b5QBRIXNKSVwksfnYNnnaGLT9JLnz8UyYKQ9oYMBlTS1YRrNzWycvwT3sAdBoUBUQvvQMB2DNknkCYasFAsZiSZQCIhePzW1naO28iD1a2V5G0qlAstSA05f5OsprbNkovGPGhg8Cj+dnhGaRoYoMibiqbTR6RxvmmpoOp2/86XvP82apflcsmUhm1cVo1bHdmjr2US7vaTZbGbJkiVjzhmNRlJSUsadn4w5qQRW52Tz5JEjUW8EMxcwKdVQl4jepubQ0XZWXZiHJXEQELH0pFCeH51Q3TRnEpY30jjY0DTmvEIhsGZZLjaPm+r23qjIEih6rZqFeen4fCJNTb1UtA6FZVyFIJCnNdPtiqwSWGhK5tju8WXVV+Wn0NlgxemaPofDNuJi++46tu+uozgvlY2rijAZtVxz4VKSEgyREHvOMyeVwIcWLsTu8fBtuSxE2FnQb6Gh+fRq78BbZz5ou8m/IZ0ObfhqxQh+Aa2oxqkc6/BPtSVS1zC+hpHfL+J3+TBoY6enrU6rpjQnBbwiR8pbwz6+x+ujYU8Hq9dlsd8auaitNI92wpiwxua+Cc5OT31LL/Uto5+f9/ce5/cP3RyCdFEiTI7hUNi+fXtQ188px/CZ3LRsGVeWSVPaYDajypw8BDcl0YChPJ0UT0JY5rJ4DFgezUb5h2RWHl6C8oQZomA4ixGtk8XrJrYtK7VKDjR1hEWGULEYdeQlWKiu7KC6pjNi84giqAciF3qpQmC4L/Cy7MFSWdfBoDUOyoOf9AmEckSZObkTOMl3LryAdxsb5bDRMJGm1tN9dPKyxT6fSM+KRqyK8IRtZthTabCPPhjK3+lkoXUhSrVA7YEefH4/ncLEoZHVle0sKEuNCXNQaXYKR46Ef/U/ERqDCiIULLTEnEZTVeSUGMRFs7S4ZM7uBADSjEYuLi2RWoxZw2JfMkO2ySNycvJNWFU2UITn26yrNI95XX2wi8o9nXi8Pvx+Ed8kSUcejw+/NTZqDLX1Rc9p7vdEbidg8Ud+PTkwFPs7AUEM/Yg2c1oJAORZwmOamO1kqY2s1k8SuifCRn0WVRWTm1iy0s10Lmma9P2gEGFV9WKq9s/cvt3aNkBhmrQdt5QKgTRT9HIZBP3pSBu1IHCOOZv13lQ2CxlYVDPPpJ9vSuJYeeQzxA9Xx0FJiThsLzmnzUEA/njrABFl1hoyETq9HG/qpRE7i1LMJJWY2eEYjQJRIbDenU71FAoAoKN7mKX2dKwJwzOSQ+tVU2TNwY+I8qCBI5WhPXT8fhH/gLSJVIuLMjlaMT6aJlJ4h72nln2rPCkc3XPaDGVQK1lWlkmzzk7zyOR/IxUCWpUKu8fNpoRsRBG8vW56Aoj8CZX39hzjw5cuj/g8IRHlPIFwMOeVQGXXLOtqFGZOKoCTdPUN4y0e/dikqvUUqROoLg/MFuxv0MOKmcmx+HgZR147+eAPj0/BPuIGtXTNVlp6BlmyJIeKiuiscGtqOtmyLAe/10/NsbF/M7fHx9HKdhYuzibfZGZY8NDqGsaoUiOK0OYYJlGjY4kimbqjnWRodVRHeWW++3Ajf3p6J3d8dGNU553tzGklIIoi5V3x38gikvSne1G2CPj8p3dMWU4DSXotqgGR6rrAnYF9XcFl8Jo8elJcCfRph2jbF/4EL7vdxYrlOXQN28mxmGkbGqZjcGY7lZkwYHWQk2CZ/sIwUnlk6gd3VeXYncnJ33oiACNUMGqXd7mk6SP9yD8+YF5hGlvWlkoy/7TEQIhosMxpJQCjFUb7RmLf4SQVx5yDnLsqh8p9px8eFeUzWwF29g6T4UmgX306CUrjU6MQBEr7SnDqHRwzNQKwomUBR1/oo83vBYw4w7T6P5va8nb8fpEBBgFYuzwPBPC6fKi0SvxePwqVgr1NkTHbqHVz/isYNDX1XbISCCNz+hMoCAIrsjJpGhyUWpSYQi8ocfp9CAIU6xJReEM3l6xcn0FrQSP96tPRMLnOLHpfUVOyKJGD+7pISTSgulzF0iMLKH8vsuGGJ/H7x37ryg+3jLtGECA/1YI+TU9NR3jDSpu6Jg+plZmYjNTo7p5mO3NWCXj9fv5y6BD/qq6RWpSYIFmlY746CY1d4OjRDkpSLej0ahrK+06tkmeKQhCoKT6KRzFqQhD8Aks7F1OxYwCX20V3i4MEsw6f20fWc/mUt0dHAQSKKEJ3j5XF6WaUirGmsVDJSrFg7Zp95a4jybIFOVKLMDnyTiB+eP5oFQ++vV1qMWKCVfoMBo8OUWs7HeHT0RO++HW1WokKFR5OKAEEuqvduNyjr9u7RudKMGjpaJem2FwgVFa2MX9JJkfbwlOfPzPFTPXRjhk2FJy7ZKSap79IKuIwOmhO5gk4PR5+vWuX1GLEBFt02TTt6ZoyyStUXG4vzqeTWdq5GFEEv8KPeE4/y68Ym6MxNOJi/vzY7oXbeLSLZXnhkbGzb5j5pXFcNlkCkhIM6GKo7tNsYM7tBERRZOs779I8FJ4KjfFMiS6R2gPRMb24vT4O/KeXBFMBuQVmxBI7dI5vlDFEbGTyToYoitim6fcaDFqD/EALhgSzXmoRpiTUrF8pMobnnBJ4cPt2njh8WGoxYoKUbhWDJ0orWEyjremsEdwRAAzZnAxVOqESYHxUVkPvIIuWZKJXq/AMe6g7FlshvEuW5rG3JXyRQgfr2jDr1Tgcsa38YgX7SOx2SgPi0icwp8xBHp+PPx+QG8qcRJWhQaNWsnR5DrYygZRFiVKLBMDRjh72N3egMsXOKtls0lK6NIvDHeHfOaWlSN+OM16I9Z1APDKnlIBScfrH1QTQdm2284Gjnd4Ffrb72+jxOLCKsbXKGnA6sZhn1jw73Hg8frRKFctyMlCHuRG60RQbP2M8ML84XWoRZh1zSgkoBIGLS0vYeuklfGjBAqnFiQk8Z+w/ax0DJMbQSquhZ4AutRtzkYWFK3IxGSduth0NnC4PlYdaqDjUyoqc8DqvlUo5PihQLtoU299bgRCriEog85zzCfz22msZ8Xio6ZW+lnzMIUBObiKDVZFrDhI0gkC31U631U56uoEMu5aubmnDSKuPtqNJVOD2hqc0s6BQoFIp8IZpvNmKRq1kSVmW1GJMjRwiGtuIosjDu3ax7jfbeEz2DYzDotQw0BebJTR0KiXZFovkCgBgwcKssCkAgIPH2igsSA3beLHIj75+LWuW5p96vaAkg7XLCoIaY/2KQowG6XaDs5U5sxNw+3x87623eOpIdBqdxxvJKh3pTSra+2MvdHZtfjZtDX0xU/bb7xNBFNFqVCzLSscvgFcU6bXZaeufWQE6pVbBymV5CA4fCAIHakfrM2nUStweXzjFjzpZaRbOWVPClrWltHQMcOhoK1ectwiHy0NtfTfv7KnjmVcPTTvOeevnRV7YUInD6KA5oQR2NDVx90v/YjiM8d2zDZ1ChUKiksrTsbepjXX52bgc0lSuPJvKyjayEg14R3yUHz5dk99s0oJqZqWpKxu6WJuXxZHyVjQaJWXZKTgcbgwGDY19g7jc8asINq0uRjjxO8nLSiIva7SZj1mlZPXSfFYvzSfBrOdPT++ccpz5RXGQWCcrgdjh70fK2dPays+uuJyv/PsVWQGcgUZQsFGVhWvAjUqjRKlW4OhzU98fu36Swf4RWlr7pRbjFAOD481mwzYXK+Zn0edz0dI3hEohUJiWROeQDZtz6j7WSoVA9dHRsh1ut4/6xtOlKUqL02OiH/JM2XWwkfKaNpbOn7zmj9k4dYRUQU4yRXkp4RZNhlmsBPa1t/F8VRV9jhG5VPRZFGoTqC/vZsQZHwlKBq0mphTAVFTXjD7IC9It2GxOWqt7MJt0zCvN4mBj+6S7BL/fjzdFjcWhwWod65jv6rayal4OB+rioL3iBLR1DfK1rc/zxVvPY9mCHDJSzWjUpx89Xp+fV96pxKjXoFAoGLaPT1j8wifPO7WbiGXiMWN41jqGLy4ZbSD/XmOY+trOImqdA3GVdDPi9pBWlhzzdYXOpKvbOtq5DBi2Oak61Mry9PRJv3AiArnJCeMUwMn7KypbWV6axdLizNGypnHGsN3JQ795jY/f8yeefW1sxr7b7WXL2lKe/vWnWbYge9y9H796NZtWF0dL1NCIwx7Ds1oJbM7PJ8diYXlmJqkGg9QixRRJKbH/+zBpNQgnvhXNfUMMiPGxc5mMmtpOVuePPuR0KuXow1wU0aoUmHQa3H2Tl+zw+0UqK9qoOtpORkr81tNPTTKxanHemHMGvYY7ProRt8fHBwfqx7ynUSv57M3nRFPEOcesNQcpFQoe/+gNp15f9Kc/0SubhYDR0tGNdX1SizElJenJtFf1kKRTU1Kajl+tYLAzeq0fI0XDsW7y9Hp6emwUZSaQkmpCFMHq99BSFVi/66xkM10zjEKSgi/ffgH5OckIwOol+Sgnybg+WNkybpNjNurGmI5iHtkxHLuc3UFqrpKpNtJ5qO9ULf9YpWfYjtmkZdjmiloj9mhgs7uw2UeDFDo6h+joHA3JzcxImOq2MbS3DaBWKfF4Yz9iKCPVzIcuXoZWM/2j5sJN8zGbdLy39xiVtR0ca+qhICc5ClKGj3j0CcwZJfDyrbfw75pavvOfN3HFwZdnHOLMQg/PpnDAQJ07tjtZqRQCVoeL0tIsqg61Tn/DLKCza/L8DLVaybySDJRqJQKjXfG6j3dMen0ssGZpPjdds4aVi3IDUgAAKqWCjSuL2LiyCICO7qF4dH/EHXNGCRjUaowadVwqgHM02VjrhzGUmNjlmvmX36BQ0dYxGD7BIkCSQUdhSiIqLzTUBmYemc0Y9BqMKXqONMZWy82z0ahVuD2ju8sHvnQlF29eEHI0T1Z64LujmCEOy0bMGSUAUJoSh3HGokj9vk48Xh+lJTMvOawXlCwbTqbOGdsP1oERJwMjnZh1WtITDKcibOYqhYWpHGmIbQVQVpTOL7/7UVraB0hLMZOWPIdLY8s+gdjlFzs+oH5gQGoxgkcQSLTo6em3oXMrWKhNpso1fcy8AlikT6XCMZpktF7IpLw+fmzrw04X8/OTaY/xnUukyCtOxWp30jEY2w7gb3/hctYsycds1LFoXowXd4sCsk8ghvnbkSNxGR0kiCJO12hoZMX+VtQqJZYVGoZ9LsTJttsibBGzqT3QxflLcsAPNZWxvZo8m6LURI4fja2uYpEmOzMBnU6D3qTh8LHYtvmfREAgLSWGG7/LTMusVwLNg4P89L3341IBZKmNFPUaqLOfNuF4vD6SKhQY3AL+tXq6PWOTixTAOf5sKo6OtkAsPxQ/q/+TZCeZEQQBhSL2M0TDSWqamabuQfo6Yzd812zUkZJkpKmtj4LsZBbHemnnaCObg2KP/MRE8hLiz8GUotIh7HdQ57WNe+9kuQfVBLl+WzQ5VOyPvwf/SXKTLPQdi0OzXRhoaeknLcNC31BsLVi+9pmLUQgCep2atcsKSLQYaO0YIP2s8g8yQIjmIFkJRIgvbtzAv2pqaLNKX4s+UPo8DuYbDfRP8kBISTJS7baNCRvdos2h6kD4mqBLQayUi442Br2GXqeDnqbJs4ajyRXnLebTH9sEQGba+Azl3BOVQGXin1lbNuJM9Go1JcnxkXSSrzGzvj+FlZ2JkyoAgEGrg0W6sY1IRpRefHGeFJdtnpuRJSMON5kmIwatWmpRAKg63klmmmVCBSAzBXFYO2hO7AQAfnzZpejVat44dpyvvfqq1OKMY742ibReNQqVgqrG6Z2CPp+fwb0DLF6bQqVr1Ia8f6SLlTlJNLfFrzklznVYSAiC4lQQgNRkpsrO3hkRhz6BObETAEg3mTBrtVy3aCFlqdLnC2zQZnKuM5Pz1DlssqbRv7OfmrouqqoCjwrxeH0IdWf0SRBhJM7j6hXeuasFunusZJpNrJw3vpJmpDl3bSlGvQYAk0HLjVetjroMMtIwZ3YCJ1EIAl/etIm7XnxJUjn0HiUVR0MviWCzu7jAn43oE/GbFFQOxLFTONlCTXV8hEZGCrvdSfeQMqpzpiWb+MjlKzhnbQm/+vN2vnjr+axfURhVGWYLcp5AnLA2JxeNUonbJ2EJiTBNbXe4qTjURnZ6Au21sZ1YNCWiiM4OA36RxUtyEFUCSlGg/HCL1JKFFb1ejU6rPtWZTKVSkJ5qoaNrkHklGTj9Purbo9NAZ9n8bI7UtPOHrZ84leV7+bmLJq3yKTM7mZNKINmg528fu5GGgQGeP1rF+02RbTyzSJuMXfTS5LaSpNSyTEilsaJn+huDwOfzI/r9QHzG1iuVCtraR6tjdrsdNHcMgSiysCCFxqbYjZsPlnmlmYiieEoJLFqYQ3P3IJn5yRxtDe9nYipWLMzl4e/dyItvlp8yAwGyApiDBPUXf+CBBxAEYcyRmTl1tyeXy8W3vvUtCgoK0Gq1lJSU8Kc//SkkocPBiqwsNufnc7A9/CGVagQQRdQIaAUFlg4BdaWLZa1mtPtdHN3Tim0kvD2Pu/qGWVQYP523zsbn81OyNIuypdm4TxT5y01JxGieuvdsvCAIsGxpLhWNnbT1na4Y6hP9KBTQ0jUYVXnKitMRBIFrL1mG4QwlIBMiUY4O2rZtG8uWLcNisWCxWNi4cSOvvPJKUGMEvRNYvHgxb7755qnXSuXU9ssbb7yRrq4uHnnkEUpLS+nu7sbrlbaWvSiK/O1IOT997z3snvBGY6gRWN2fjDZdy3DbCFarg+PDo/V7hoYjGwMu+CM6fGQRBCraxxa3yzIZqTg4O8xBgiBQ29qL2+MjLdFEf8cwecWpuDw+bBI485fOj77zeS4QbZ9Abm4uP/rRjygtLQXgz3/+M9deey0HDx5k8eLFAY0RtBJQqVTTrv5P8uqrr/LOO+9QX19P8ok4/cLCwmCnDDs1vb38vzMUWTjI1ZgY9rlZ6UyhsrEdGsM6fEDMtjIL/c7YSJwKlbycJLwq4dRqv6qhi6QMEw1tfWHpETHt/FlJtHQMUJSXwrIFObR1DrJ5dUnE552zRNG5e80114x5/cMf/pBt27axa9euyCmBuro6srOz0Wq1rF+/noceeoji4ombQL/44ousWbOGn/zkJ/zlL3/BaDTyoQ99iB/84Afo9ZM3One5XLhcp80l1jBn+hYnJ5NmNNJjD09zlVyNCeGAA43bSyXRzdjNzUjENuJicNiB2xfPW4Hx2F1uVCoFX719kH+9m8uiEhf/esuPwxkbsfSB4vX6cYtg1GmwO934YbQ0RBQUAMB/f/YS5hWmYzRoQq7xLxMdzn7mabVatFrtlPf4fD6efvpp7HY7GzduDHiuoJTA+vXrefzxxykrK6Orq4sHH3yQTZs2UVlZScoEtfrr6+t5//330el0PPfcc/T29nLXXXfR398/pV9g69atfO973wtGtKDQKJX87toP8diBg7h9Pg51dNBpG1+jJ1CS6wU6JGjXWJCdTNuglfREE4W5KRw81kq8OoYnIj/BzDWfbuKS1U9z6RpQKKAk70Z+9Lvo14IyGTU89OUjeLxqXv1gBW+8F3gkVseJrmHFhWnUdfYiRvlvlJJkxGSc+gEiEybClCyWl5c35vR3v/tdHnjggQlvKS8vZ+PGjTidTkwmE8899xyLFi0KeEpBFGfewM1ut1NSUsLXv/517r333nHvX3rppbz33nt0dnaScKKI27PPPssNN9yA3W6fdDcw0U4gLy+PoaEhLJbwp7E7PR7O++MjAVcaVSOwSJfKYedoNMc5mmxqdkU/Pr8gL5mGzvjNDp6O//10P5tK/zHmnM+v4InXP8Ozr6uwDofXuT4Z6akGrr9smBvPH124/PKf9/Dca45p7hqPVqNCadZgtYffzGUx6fjUjZvYfaiRDw7UnzqvUat49dG70MZIOQopsFqtJCQkROz5ceYc877+EErtzIMZfC4ndT/5Ji0tLWNknWon4Ha7aW5uZnBwkGeeeYY//vGPvPPOOwErgpBCRI1GI0uXLqWurm7C97OyssjJyTmlAAAWLlyIKIq0trYyb968Ce8LZOsTTnRqNecVFfFMZWVA1290ZFB1oIMlm9KocPSgdkuz+u4fDv5BFE8sKagdd06p8HPr5b/lpou0vFt+DT/cFtlCZpefZ+Lrn/j5GMtNU5sGCO53P39eJi7Rx7HW8Ie73nDFSu782GZMRi3XX76C9/cd56e/f5NB6whfuv38Oa0A4pWT0T6BoNFoTjmG16xZw969e/m///s/fve73wV0f0hBwS6Xi6qqKrKyJq4pvnnzZtrb27GdYWqpra1FoVCQm5sbytRh5yeXX4Y5UMVjGf219ezsZWVnIhUHpGmGXpIlffmLSPHAfw1iUR+a9H2N2sXGRW9gNEY2vPHdPS6c7rFF7dYsGUSnC279pBD8eHzh8WWU5Kdy0ab5XH3hEjauLOKeW88/Ze4RBIEta0v5x8Of4pltn+G6S5aHZU6ZAImBAnKiKI6xpExHUJ/k++67j2uuuYb8/Hy6u7t58MEHsVqt3HrrrQDcf//9tLW18fjjjwNw880384Mf/IDbb7+d733ve/T29vK1r32NO+64Y0rHsBS0W60MB/iL2+vtIj/RSP+gnVYJ2x86whzeGit8/Dw3ly35+7TXGXVDbP3yEb7+P0twOiPjkxlxeOgcKKYo88ipczdd9Eduugi++sv7OFA+NO4ei1nLR69wU5LTwvd/U0hykpYf370NEQWf/79baW6fmf/p7k+ey+bVxeRnJ0/r4NVpRzOTZaJLtENEv/nNb3LFFVeQl5fH8PAwTz31FNu3b+fVIIpkBqUEWltbuemmm+jt7SUtLY0NGzawa9cuCgoKAOjo6KC5ufnU9SaTiTfeeIMvfvGLrFmzhpSUFG688UYefPDBYKaNCj//4AOKtQn0eB0M+86I2xZFlIIwpsqDTqHCHuZkr2BJSzJR0xzbTeOn4+r1Hu66opxfvbyMV/aqAJGtt/dz/vwXEQJcEi3Ofw9YgkqlwOuNTHRU71AGRRNERV9/cRUHyrP55IdV5KT3UV6XzYalx1lb9iZazai56H++tomSrIOnXt/7sUN8+eelQctQmJvCTdeskaN7ZMbQ1dXFJz/5STo6OkhISGDZsmW8+uqrXHLJJQGPEZJjOFpEw7Hzm9272f92PT3tw3QUe7H53WxSZDHQMozZoqM2aRi714Nd9CKIIqu6pS/ZbDJoKcpP4fDx+Cy6ds0GD9+67hFEjPSMLCdB34lWqJ/+xrPYU3MpqZZu7vvfLQwMTu50NRk13PLhESzGEQREUhL6qKwv5dF/Tq08brxKx+ev+9WE7w2PJGM2BF7rp7JlE//vj+vo6Q/cp7CoNJMf3HuNXNt/hkTTMVz21dAdw7X/882Iyno2c7J20ER8ft06ft3n5YnyXSSWJbJ4IIHK6lFbf4bXz2JDEn6PH59ZgTDgo31oUFqBAduIi6N1nRRmJ9PYGZ2iY+HkgmWDAAjYSTd8MONx1s1/HYBvfzaZ7/xqIW6PD49nbIW+/7pORVl+M1uWjq0euyh/Dx7vJ5lf0Mwjz5bxrU9v552D63ni+dPmpaKcyXdcwSgAgMV5H/DUt/fz7K7/oq3XzMvvulCplIiiiNM13qS1ZW0J3/vy1Wg18lc1LojDfgJz/pNltTv5+6sHuPmK1bgGXRh0aoZ3DlJ9xjVdvcN09cZmhU6fz0+iIT7r6xRnhNectar0LZ756U7srkR+9Pgn2HvotL3+ui0vkWIZ78DXa4f51FW/QRRh06LRXITizAPsPPRVjjeOJuxsXPRWWOXUqF18fMsjAHzphstQp/4ffYMjXPuZ8dEcH7tqtawAZCLKnC8Z+PdX9vPIszu55ou/5+mXD55q4h5P1Lf0sqggQ2oxgqa2I/wyazUOks0d/OjzPxtz/sUdV+OfwuojCKMKAGBX9VWnFACAy2MIu5wnUfleA89BUpNMKM8q+3H1BUtYuThvkjtlYpGTjuFQjmgzZ5WA3y+yr7KZF94uB2DEGb8duWwjLsQ4KxmhVooszWuM2PgjrrH5A48/6+Prv76Ptt750967pGA3JQVmbvqQhpQkPdaRCIbiGu8G9WiNl20P3kRORuKpt264cmXk5pWJDDEQIhosc3KfWdvYzf/79cs0Ral5RyTJTrMgAj5fzPv3T3HZai9fuuYISdp9EZujZ2j8Cnr/kSFuqTiP1cuu4Sd3/2yCu0axGHv59de3AfCJSzToNePDQMOGaAdfO6iKWTwvi9s/uoFH/v4BWo2K0oK0yM0rExlkn0B88O2H/0Vzx+wot2BO0NPVP4zXGR9K4Or1Hr714T8jENlaS/lplZiMW7DZR3d4W9ZZsJh89A6oSDBP39btZEinNsjM4KAZeQxx5DFI/BWC7jKuOG8xVpuTqmOdcjioTFSYk0rgqi2L2faP96UWIyRSk0xo1Urswy4GbQ78MaoDbr7AzflLexga0fK1P6Zwx8XHIq4AAJRKH1+6pYshm5EPDqah1fi576ZfRHzemSIOfg1SyxBURbS0D/D+3uNSiyQzA+Qew3HAP18/yP6j8duoRKtRMa8onYr6DhBGywTEqgIAONqs4ouX/QsBkZ0/UiMQPcf7xav+CcB15yjoGoj1+vlOxJG/IVi+yZduu4AbrpD9AXGJbA6Kferb+thTEdmewpFkfnEGh46f6FkgAjGe61fXJpzK/o2mAjgTpcJPdsrERQ5jCUE3muWpVispzJ29daFkYos5pwRiNd4/UARGQ7riJRZIL5exl5lDyOagGKejx8qOQ8GXJYgVDDo1h6vbWL4wh4PHotvBbDL+584eFuS00m1N4YOqNLYf0dHUJeL2jkYf9w6BiCoqfoB4R7R+H8zfQNBulloUmZkim4Nim3hWAEa9BpfgJy83GZdn+uiWSLCixM9lq+0szO0n0WjjL2/PY3PJMwCk6GBhOnzqPKjrvYxP/qzoxF0CNs8izOojkw8sM4q3BnHgdkj+K4JmrdTSyMwR5pQSaI3jLlwpiUYaewdp6pLmZ9BqRH5z57Mo6D117r6rD094bUnqLpYXF7BpkYsVRQPo1T3REnNWIA7eh6hehJD4GzlMNN6QdwKxzfWXrOCpVw9ILUbQLF+YQ0VDp6QyLCkQxygAAAHrhNcqGOJ3n/l9NMSanfg7wNWBOPglMH8VQVUgtUQyASIQWpdvKVT+nCobkZeZRF5mZNsRRgKvx48/wCggpUKISMTQDecMYPMuDfu4MlPgehWx93L8A59HtP8Z0T+zZjQyMlMxp5QAgNkYf+Eqlcc6KE5PJsk0cTc2BbC4MINFueng9pOo1bF0oi4oIXD/oync8r+bwjqmTCD4wPUfxOEfIg7dJ7UwMtMRh7WD5pwSuPrcJVKLMCOOt/RSlJk85lySSc/qeTmkGA1U1XVS3dCFKI6Wx64+3kXhWdeHSlFWvASmzk4Ew+1SiyAzDXIV0TjgQ+cv4YVf3kmSJbZ6HAdCT98wK0tzWFWaw5L8DGxDDg4ebaVv0D7uWp/PT2/PMNkp4etOdPW6wbCNJRM84tDX8Q/+N6K3QWpRZCYjDncCc8oxDKBSKclIsZCVmsCANcLFwcJMW/cQbd2BV7QccbrJ0ycSroyCAVv8mdJmFf4OcD4H2k2gKpr+ehmZAJhzO4GTlBWmSy1CVGhqH0CtDM+fub5TVgKSoywA3ZVSSyEzFXG0C4A5rATuveUCPnb5KqnFiDhutxeDThOWsSoalWEZR2bmCMY7EAS11GLITILsE4gjNGoVX/nkBdx364WkJBqlFidiZKSaGbI7wzJWdYuAj/hrYzlrMNwKumullkJmljFnlcBJbrh0JS/88jNcf/FyqUWJCB09VlaVZIdlLI1KRERehUqFoEhGUESu37FMGJAdw/GJSqngK5+8gEUlWei0Kg5WtfLPNw5JLVbY6B0YHz00E9xeBd3DJWSbW8MynkwwqEf9ATIxTTxWEZ3zO4GTqFRKrjp3MRetn8/NV62RWpywMjjsmDTRLFg+8sMFuPyx3qBllqEqRUh9EUEvO4Rlwo+sBCbAI1GVzkhhG3FRkB6uchkCj23fQkXH1QFdPSwuRcR06vWAfzUicpRRUAhJoCyWWgqZQJDNQbODV94/KrUIYaextY+VJdkMO90ca+ud/oYpePR1LbeeXzPuvJt83u1Zj9cPTx9PYFmKl20VGl6+Kh23T81PDuUx4oW/n7c/pPnnHJ694HgWDNdLLYnMNMSjOUhWAhMwNBxfSWSBYLU7aWjpQ6kLR5inwJcfuYBtd3YicLpT27/aN/G1HRZO1kLc3jY616UvlZ665s7F7jDMP/cQrd9BdP0HQXsu6D+CIIQn7FdGRjYHncXbe+v49yzcCaQlmcjJTqTPOhKW8cx6cYwCAPhw9tOUf/RdfrZ5iC8tnzgstdjiQkTPu30fAeDdvo9QYbsiLDLNbjzgehPR+h1wyzupmCUOzUGyEjiDZ988zP2/eBGXe3a1Qly6IIeuYRuVjV1hGe+KtV4evPntcecFfOhp4srs3XysuHbCe/udKrq9K/j0Wyl0ejZx+1tpXPtKHnYWhkW2OYEgh4nGLLISiG/cntn18D9Jn9UOYexQ9aH1PWgVxyZ8T8CBlgaePFY24fs/Pahn03PL8KFg8/Oj/QlMKtAL4VFQcwHR+RKid+Lfv4y0yBnDcYzX6+OFt8uDvk8JrNPq2KDUUmTQs06ri0hTl1BITzRNf1EQPPbmxHWXerzraXWfi4siFiUHbnayeaHbsyBc4s1+Rh5HtP9JailkZgmyYxgYsI7wvW2v0NDWF9R9a/R67AdbqT3WiUIh4PeLDABrb1jDXqdjVBnEQI/Yvn7bpLKIiGQXJeF2eunrmL5zlUkn8uAndo873+ndxObnTnYeC9a0I3Duc4upurEOpSj3Iw4IX5vUEshMRKgmHXknIA1P/Gsvu440Bnz9Oq2eNb0ujj29j45jo71//f7Tf72mlw+zsmOE/F3NWNTS69mWzkFWzcsdd75oWRr+zXqOJA+QsjAhoLFyUkUM6vGmG59fLi4XVTxHEL0tUkshcxaCKIZ8RBtZCQAXLS2kzKCnyKBHOcnC3aBUMt+oZ6NXSe0z+zi2a3KbrNvhoWF/A9Y+G4XH+lmjN7BRIW1IX1vfEIkXJjH/3JxT51qq+nB4R/0gzrbAiszVtCr4+avX0u45hx7fOjxCDk2u87nh9dAcu19a6aLJsVSOFAoU0Y44eBf+4V9KLYlMnCP9MjUG+Nv3nqX7jVF/wLzidAxrChAa+/EWJqP3+OjZ00Bf2wBdQLDuy+byFihvITkzEdbkTHt9pDBl66kY6qaOfjZvzKF2Zztej59iUzKVgz1oEwIvDHdgIJNtz5/UlitDlm1hksgdpTu57Z3zSdSK/G7D6ffEEzkHglTF1mMZbw2ILjDfI7UkMieJQ3OQrAQYbcV4ks76bqjvHn2x53jY5rBN0AIymnTUDqBaocDr93OEXlITdag1SoZ9o8lbg2YvSpWAzzv1p1AQYGTIRW6BhVabNSyyVQ0ILHn6QgDWpI/tY/zrulu4qfgoKcq9YZlr1iHoEEU/giBv6mOBeMwYlj85gCnBgFqjQq2JnE5UKBSSRg05RzwsTkgDYNjtYmgxdJZ4aB4ebVd5dLAHcaOe4ouzKVufhVqjIDnDiCCAQiVQtDQNjU5J6QU51GfaSVbrIiJnnvm0EhARcPsEXm0twy8kRmS+uMdbDe6dUkshE8fIOwHgk9+8jo/fdzX2oRH+964/0dEY/ggVt9PNar2R/c7wZOzOBH03nGwH0O8cXxqja8RO18jojiV5rZ4ul50FaguJ88zssLaStsbILmsbflHkyEB3RGS0uwXaPefgFxXs7M7h1+VaQMt1+VkYhcGIzBnviI5/AgrQrJd3BFIjm4Pik7yyrFP///3eH/LKY+/w6Pf+icPmCsv4giAw/4plVPmkrZvjsnogJbBri3qNqPUJHGvtRL1gtAx1jyPyJq3XW5S83rJ4zLlzs/0YhKaIzx23OF9GdL4M2ksh4Sdy4xkJkc1BswC1RsWHPnMRy7aEr4yBKIr0GNUMSpyRrFQLnGPIJVk3fW8BfbKW44e6SEwxMOwLjzKcKR122Dd0saQyxAWu18H1ltRSyMQZshKYhLJVhViSw5dpO/DsQQr0kbGjB0rL0T6Ovd2KT/RPed2ypHR6GqwkpRpwLFZy3DoQJQknpm5IwU2vZ+KiSFI54gHR+QLiCd+T6B9CdL2D6GuXWKo5hFw7aPbwia9/iDt/+LGwjefz+si2eTAqpf2Vq7RKhlxTr+ztPg9p8xIYXqSgzT485bXR4vaFHno90oXYxg2udxB7L8Lf/2lE60OIA3ci9pyPf+AeRL+0ynwuEO3aQVu3bmXt2rWYzWbS09O57rrrqKkZ3+tjKmQlMAnNNe08sfWFsI5Z9coRkt45zpoeJ4US7Qp8Hh9qxdR/9uPWAd4faaUjRhSAgMg3l/yZHPX7UosSH/hawf0uOJ87fc71KmLvhxD9sfE3nbVEeSfwzjvvcPfdd7Nr1y7eeOMNvF4vl156KXZ74P472TE8CfnzsylemkdXc2hduM7GNjjCsd3HMeWtCuu4gVK6JYcOZ3zVnTGpQZJ98mzD3wX+IVCYpZZEJky8+uqrY14/+uijpKens3//fs4999yAxpB3AlPwlYdvZ+NVoWfEnk1KThKtzug7W4tWpPNenCkAgGGPwPfLb5N7E4cB0fptRF+n1GLMasJhCrJarWMO1zQm3JMMDY3m/SQnJwcsr6wEpsCSbOI7f/0C130+vJEpaQuzwzpeoDSVd7PZMr6QXDxQ0a8C5NaUIeP+AHHg84iiR2pJZieiGPoB5OXlkZCQcOrYunVrAFOL3HvvvZxzzjksWbIkYJFlc9A0CILATV+7hpcf2Y4nDB3HFly7ij1eaUIuM4uSqPcNSjJ3qBzsFrCJSzALwfd8kDkLbyWi7WEwfRkhBkqdy4ynpaUFi8Vy6rVWO/0u+Atf+AJHjhzh/feD853JSiAAElLMaA3akJSAQqkg/frV7B0ZwS/B9y5/SSpHk4aw2+NzBfjjTcOyAggn9m2Ivhaw/D8ERZLU0swawpUsZrFYxiiB6fjiF7/Iiy++yLvvvktubnC7fdkcFCD/+/r9JKSedqhlF6fzuR/dxO3fvZ7UnCSUqmnq6YsiHW4XvgjLORFJmSaqkqzYPfGpAACStbIpKOw4/wUjf5VaitlFlKODRFHkC1/4As8++yxvvfUWRUXB59LISiBA7FYHQ72nw+vScpK57vOX8LF7r+LRQz/m/976NqaEydP1/X6RRV5pft1DvXYM6sBLRcci9cMG2TEcAUTXu4i+0QLpoigr2njj7rvv5oknnuDJJ5/EbDbT2dlJZ2cnDsf42mCTISuBAClbVcTnf3Izn/vRTeSUZFC4+PSWS61RUbq8gCvvOH/KMWr+fZhlRgO3XrueH3/lQzz0pWsozU+LsORQuimb7hFpS1mHykP7DFzy2i20e86RWpTZhecQYs9F+HuvQ+xaiWjbhjhNRrnM5Aj+0I9g2LZtG0NDQ5x//vlkZWWdOv7+978HPIbsEwgQpVLBtZ8djRK6+tMXTGj+KVtZCMA1d17IS38YX8NFpVFhaRni8zeefpDNL0zn+q88EhmhTzBo9MyKwJoGq4Itzy/mu2sL+GTh0wiz4YeKCdzgPQqAaPs5eOsh4SEEIb53j5IQ5SqiYhjK08tKYAaoJukbvHB9KYs3zuOun36CpZvK6O0YJDUrkZ72AV76/X+444EbOPcj68bc43ZH3kvgl7CPQST4yQEj1xUswCIckVqU2YnzBUR/PyRtQxCkbYsqE3lkJRBGUjIT+Z9X7wcY97D/8F2XjDaWOYui3BQu3jCfN3cFV+8jUESgzTGbSgWIvHPtQVkBRBr3e+A5BJp1014qcxq5lLTMpEykAE5y/6cu4Zrzl3DR+jLU00UZBUneghQGXYE1kY8XHqldzJB/udRizH48kVmYzGrClCwWTWQlEAMYDVq+dedl/PCea/jY5aM1hVQnqo2WFaazcsFpJ7RSqTj13nSYk/Q0ZgYeJRAfCPyuQkuVtVBqQWY9oq/llJNY9NsQfeHvuDfbiHYV0XAgm4NijLs/voUPX7QMk0HL4eo2lszLxqBX84u/bKcwO5m0ZBP5Wcl84+cv0NY9NOVYGWtSODbcGh3Bo8y7HUkouJYliTUYqJZanNnJyGOInkpI+CGi7VfgfAlRewFCwo/kBLNZhCCGw70cYaxWKwkJCQwNDQWVRTebsY24eP6tIzzxr70MDk+82k+7PI2Kwdm/evvHZe2strwktRizGC0oEsB/oq+0Mh8h5TmEOKlGGo3nx8k51l/9A1TqmZeJ93qc7P7X/4vqs042B8UpJoOW/7p6Lf/7tY9QnDu+cXBqjplqa58EkkWfm17LpMcnOzAjh+u0AgDwNcPIk9KJE8PI5iCZqLOoJJMnf3wbQ8MOqhu76Oy18u+aWvYqu/A650bSjw8F39+/jP9bX4tCHJRanDmBaP8dKBJBUIPuKgRBzuaOV+SdwCwhwaxn9eJ8/tJXyeueJgacsysiaDr+3aTkG/uvR5Q/0tFBtCFa/x/i0DcQrd+XWprYQY4OkpGSxw4fYH/H3G0q/sxxFW4KpRZj7uF4HtH5mtRSxATxaA6SlcAsocdu5xe7P5BaDMnxE948C5lA8CAOfgnRvV9qQWRmgKwEZgm/PbAnrktFhwuFJMW6ZcAP3uqw1LKJa6JcSjocyEpgFuDz+3m+ukpqMWIChSAXlZMK0foDEAekFkNSZr056IEHHkAQhDFHZmZmQPfu2LEDlUrFihUrZiKnzBRU9nTT75xtmcEzQ0l8l8yOa7TnIigCb3AuExsEHSK6ePFi3nzzzVOvlcrpbbBDQ0PccsstXHTRRXR1dQU7pcw0PFNdKbUIMUG6XkQQp86ilokcgu5yqUWQHr84eoRyf5QJWgmoVKqAV/8n+exnP8vNN9+MUqnk+eefD3ZKmUl4rvoor9cf49XjdVKLEhPcXOZCYG7kRsQiouMFBP1HpBZDWkK168e6OQigrq6O7OxsioqK+PjHP059ff2U1z/66KMcP36c7373uwHP4XK5sFqtYw6Z0ww4HLxUW83De3fJCuAMbik9LLUIcxtv7Zx3DAuE6BOQQOaglMD69et5/PHHee211/jDH/5AZ2cnmzZtoq9v4vIEdXV1fOMb3+Cvf/0rKlXgm46tW7eSkJBw6sjLywtGzFnP3o427nntZeoH57YT7mzu37sGn5AhtRhzF38f+JqklkImSIJSAldccQXXX389S5cu5eKLL+bll18G4M9//vO4a30+HzfffDPf+973KCsrC0qo+++/n6GhoVNHS0tLUPfPZkRR5PkaORIIQDhr7/xas5LP7LhGbkgvJf5eqSWQljjMGA6pdpDRaGTp0qXU1Y03SQwPD7Nv3z4OHjzIF77wBQD8fj+iKKJSqXj99de58MILJxxXq9Wi1cpf5In41d5dvHKsVmoxJGdTlp/fbN7Jvr75fGdPCh+b5+JD+U1c8GIZNrEMs1AutYhzEDWoF0sthKTEY2exkJSAy+WiqqqKLVu2jHvPYrFQXj72i/ib3/yGt956i3/+858UFRWFMvWc5OW6Gn4uZwUDsCrVjVmo4ILUCr68/CY2ZzTRaEtjz0cOygogUhg/DY6XwD9RhJ8AuisQBH3UxZIJjaCUwH333cc111xDfn4+3d3dPPjgg1itVm699VZg1IzT1tbG448/jkKhYMmSJWPuT09PR6fTjTsvMzVun48vv/5veQdwBr+r1HJb2UqSFAe5PudvAGQmSivTrEW1CBQWBOPnwXArOF8FcQTR8Tz4GgAQEn8L2s3SyhkLxGF0UFBKoLW1lZtuuone3l7S0tLYsGEDu3btoqCgAICOjg6am5sjIuhcZldbi6wAzsLjFzj/hbW8d51PbjofaVRFKBJ/fuKFGYyjiz70H0Icuh/cu0CRjCBoJBMxVhBEESEEu34o94YwZ+zHdM3lzmIen48P/f2vVPfN/g5hwVJiEXnl8mdRinPcGRlxNAgZhxCEideMorcRQVUYXZGCIJqdxbac/11UqhA6i3mdvLf9e3JnMZnT9DpGZAUwCcetAr2eeVKLMftR5kyqAICYVgBRxx+GI8rIncVinDSDUWoRYppuZyIZJqmlmOXoLpZagrghHs1B8k5AJm4xqESSNHLBuEgjCAapRZCJIPJOIIYRRZEXa6ulFiMmeffao2Rr3h+XMCYTfkRPhSTlDOKS2R4dJBNdWqxDfPWNV6QWI6ZYmCTyu/OOkq0+JCuAKCFoNkgtQvwQatZvvGUMy0SWLrtNahEk56YyDx8q6GVN0nZe67yMizL2oEGuTxM9VKAdnwwqMzFzLmNYJrLIpiD41PxGinRvgQhXZDwttThzDAEh4acIqmKpBZGJILISiFHsbjcvzPFCcWWJIvn6I5LYSWVAsDyIoL9KajHiC9kcJBMuKnq6GXbP3X65CRqRpy/eISeCSYFgQrB8D0F/jdSSxB2Cf/QI5f5oIyuBGCVZP7cLca1J96MQfFKLMUdQgO7qE2YfEfQfRlBmSy2UTJSQlUCMUpyYhFmjmbO7gf+0Knmyfi2fLpb9IhFDdwWC9gJQL0VQlUgtzexANgfJhAOn18MzVUcZ8XikFkVStu7Xc2PRUixyaejwIhgQkv6IoFkjtSSzjzjME5AzhmOQPx7cz7e3v4kv9mv7RRiB7+xbhyinKoUVwfwNWQHInEJWAjFIbZ/sDD3JS40qOj2bpBYj/lHmgfY8BPO3EQwfl1qaWcvJ2kGhHNFGNgfFGKIosqe9TWoxYoo+l4UstdRSxDGqJShSn5VairlBHPoE5J1AjHGgs13OFD6L48MJUosQ1wiGm6UWQSaGkZVADNFls3HHS89JLUbM8b+HLIjIXauCR4mQ9Cjor5dakLmDSGi9BGTH8Nzme++9jdXlklqMmKPVJtDvWy61GHGGFsF8H4J2M4IgO9ajRbR9Au+++y7XXHMN2dnZCILA888/H7TMshKIEXa1yn2Ep+KDHrl+TVCoShCMn5JairmHyGm/wIyO4Kaz2+0sX76chx9+eMYiy47hGOHRwwekFiGmeazKwjWZUksRR3hrEb3NCKp8qSWRiSBXXHEFV1xxRUhjyDuBGKFpaFBqEWKaQ70KdgxcJ7UYcYQXsf9mRPdhqQWZW4S0CzgdWWS1WsccrgiaiWUlEAMMOh3U9fdJLUbM8/djqVKLEF/4u0cVgeMFqSWZO4Sp0XxeXh4JCQmnjq1bt0ZMZNkcFAP0ORz453x28PR0jMgOzuDxIA59AzSbEZSyEo0XWlpasFgsp15rtdqIzSUrgRhArVCgEARZEUzDhwodUosQp/jA/QHoPyS1ILOeULN+T95rsVjGKIFIIpuDYoD8hET+e5Pcwm86MvRy+OxMEYd/gn/o24h+ORExooTJJxBNZCUQI3x65RryLHJm7FScn75XahHiF383OP6BaP2B1JLIhBGbzcahQ4c4dOgQAA0NDRw6dIjm5uaAx5CVQIwgAJYI2v3inf/ZPISaDqnFiH+czyG6dkotxewlyjuBffv2sXLlSlauXAnAvffey8qVK/nOd74T8BiyTyBG+P3BfVT2dEstRsyiU/oQkM1B4UC0/Qw0/5QziSNBlAvInX/++YghmpDknUCM8MjB/VKLENPc/W4SorxmCQ+ecnD8Q2opZGIE+VsVA/SM2LG55VXuVKTpQcArtRizB9EptQSzEz+E1ANJbjQ/N3ngnbdweOUH3FR8ebldahFmD8oCMNwktRSzknCFiEYTWQnEALlRigeOZ9rscleZ8KBASNiKIMiluSOC3FRGJlhEUWRXa4vUYsQ8vynX0uI+V2ox4h9FCqiXSC2FTAwhKwGJKe/u4kh3V9TnXZiaRrbZHNQ9Sr/Ile+5MHmjH1WyKcuPSSUnOoWM9jwEQSe1FLMXvxj6EWVkJSAx77c0RX3OdKORH190GW/91x2UJiXzlfWBNXL3KQTc2UaW/F8ta/qimdMg8uiWl0lSzMFy24IeVOFbuQu60bLDoq8bv/VBRJ9cuDCsyBnDMsGyKjM7anPlWiy88Ynb/n979x4V1XXvAfy753UYYJjwHgZ8odQHD6WSi8+g8VmBJrVNClWjNelqbjBK2kaT1d6ltYnYJm1jem9sYu9t6rJBl9XEmtqIpqk2AaWFmIzGiFaMgiAgMOCDYYbzu39MPDryEJhheMzvs9aslZnzO2fv2ZGzZz8PPlz+PSRGREKnViMjbixyUlLxwynTERkQeM9rHB7tgOY78VD//iQWnhQIcnjjn5BAZkEGrlG8F9IaSASE4XnAg/331PA45OqxoNoZwI3tzl1GZavHrs8GH64E+llcaKhX0tGqVNiW/jDGhIRCq1YDAIQQWJM6DWqVCulxY6HXOgdfTfeoDD6MasXnuWMhawXGbD6JKTV9P8hY1ihgJx9aUa0ZDxH2F8AvE7CfAKRZQMD3AU08EJDjfLU/CdAmAf5LAL+vAdqJgHpUB3F3/NpsKwfavN8aHbrcbQXw7CCf0trWhtyDB7yS1ncnfRXjwsI7PHbTbkdFkxUXGhvwTOo0LB43ATl/fRef1lR3ej2rRkbBWGDR9Fi0FdYADxmBPl6Berx2NBZG+kiXUFsFIIIhVAFA+N8g1F+2GA0/BACQowJ0YztAzcopIvRPENoJynsiGdTwPeeNvgt0/X8h7tvi+e/gi3h2EOsJe1ubV8YE9BoNclKmdHr854X/wLmGeixNnIj/+ddxfFZXi42z5iAuxLWVYtBJkNSuvxssUwNRfrQMi4ockNo8nXPCw7EOxIc4V9Bs+TTY0wkMXNQMuvZrALhdAdxBaGK+vHHrAM0EwC/DpQIAACFUEP7ZgOoez+VU8/ObfRm3BPpRgE6H8WHhOF1X2+fp3Lm/yPmGenxwoRzDgoIwf3QcNqQ9qBxbkZSM8IAA3LDblVXMeo0Ga6fNxJKEiVCrVDjfUI/f/PMY/nquDHqHCpFfMaFsVwm+ejwM2kfHoyyMENugwvlgGdVSdxfBEU4+8gFqbdF46h9fwekGgT/MrcWM4LdBMGDTyW9hdfy/PFksA1/LX0BBGyBEx3+mQpoBhL0HqM0QouPfc8JvLqi1GLjxZsdpqEdABD7loQwz5+weN37N98PsIEHu7j7kBU1NTTAajbBarV570IK3XG5uwsr9b+PM1bo+TcccaEDenPnQazTYcrwIH1VcxJToYXhp7sJOF6udrb+K4soKzB89BuH+Ae2ON7bcRG15HVStbfALkPBB/kc4sO0waiucM060khYx94+EPdWEvw+3d5m/7XOvYHrwOwAAggYOEQUNVSlbRThEJDTk/am0fUY9GvCbD6GdBGhGAI6zgDoakJsAx+kv+/JtgDTHrYVd5Pg3qK6LB5HrvwmVse8eXTgQeOP+cSuNucOfgkbV+7Erh2zD4YuvefVex5XAAHCq9goyd+5we0hIq1JhclQ0rly/hvLGhnbHBYDc1Gl4YPhIrD/yPrITkpAVn+Rmqq7aHG0o/uvH2Pnzd/BZ4RlnviQtLuSl4Kb6zm9IuLXJyp0VwNChAqR5QGsRoE0EVPcB0AF0DaBrEMH/ByHUfZ4Lkq+B6hYBcifjO34PQXXfS32ej/7ElUDXuDtoAIgPj8TskbFwyDKabDacuHJ733xJrYEpMBB2uQ2Xm5s7PN9fq8V3EpLw+KTJMAU6F4C9UfpP5H101CXup2lzsCxpEgDg4bETkNwH01PVGjWmZqZg8rwk/PRbL6P4wMew2+xIOw28lwAAhFdnNmKRaQ8qW6dDUrcgXGoEMA5wfO6BHEiAZiTgOOOBa/WeCFw9ILpZhCoQCHsHdP0PwPXfAXBtkQlpVr/ka8gahAPDXAkMEC/NXYCrN2/iTF0tnj74F+XznPtT8fT9U0BEWPrOn1BY4frEIH+tFkeXP4FQvb/L51nxSfj0SjVO1tbAamuBo01GWX0dqq41IyrQgO9O+mqffh+dnw7r9zyLn37zJRQf+BjnthVhelwkpmVEYOHi3RAgxOiOAqowiND3AWhAVzywDkD3HxD+2aDGO27AfhnOufb2zwHHZ+6n0R1+872TTjcIVQiE4RmQ9CCo8T8B+XbXI9k+gNCn92PuhphBOCbAlcAAEaL3R3ljA9b9rQCSWoP7zdF4eOx4PDR2PADnnP4Fo8dgkikK02OGw1J7BfdJfkiMiGxXAQDOp5T999cyvf01XOgkLdbveRZbc3+PfxV8grDIYLz9awuO7ZuN6RmBiEtqQtq34qASehC1AqpIQL6z31+gx39Qrf9wPlBdOwlwXADUYVDd9yvlMF3fAWotBGxHANidM2e0Y7987ylaAANvgzahmwiEvg26thWw/xNwfAGh695qcdZNg7AlwGMCA0xzqw06lRqSZujVz/VXGnGm+BxOHytDWcl5xMRFYcXGTAQGRwAASK4HHP8G5HoAapD1eYB6uJpVMwaqsHuvvSDHOecgrHYSABuo7iGg7UJPvxIAQAQ+C2iGAW2VzopMlwqh7nhNxkBBJANtlyA0I/o7K33Oq2MC5u+7PyZw+XUeE/BlBt3QXRUbEnkfpmamYGpmSofHhSoE0IUo78n+CXD99Z4loorqVpjQjFH+W276hfMG3hvSAiDg8U6naA5UQqics5KYZxHcbAl4LCfdNrj+5TKfIgKfggh6EcLwX90/qfUjyNb1PUznhxARhYCu8wV1nXKcck7vZAwYlBvIcUuADVhC6AH/R5xvqBF07TfdOEsGWj/qWTqqL/dKCn4DVL8CsHe0NYVwrqyV6wFqAPy+AWH8GUB2QPADb9jgxS0BNjgEfB8Q3Xz+gSqsV0kI4Qehf/TuiwH+KyDC3ndu6KYZBWjiIIw/gxA6CFUAP6WL3SbL7r+8jFsCbFCga1tcNkvrlAiECP5d7xMSfs4dOKEChAFCEwsRsMKZh7Y6CP03nQO/fONnHRmEs4O4EmCDgtCMUcbMhPEXAAhkfQ7tRtL8l9/u3ulNOvpFEPpFHR9Th93unmJsiOBKgA0O0iwI468A4Q9IM4HWUrSrAPRZEIGr+yV7jAHglgBjfUWoggF9hvJebv65a4A0FyJoA0QfP9OAsS4NwhXDPDDMBifV7fUE0EyACPqvQTdXn7GBgFsCbNChG28BrccBaAH/LAjDWggxdBfZscGDSHauxnbjfG/jSoANPqpwiOCtgHaCc5UxYwMFkXtdOjwmwNi9Cb95/Z0Fxjrm7sPi+RnDjDHGvIlbAowx5imyDAg3+vV5TIAxxgYx7g5ijDE2mHBLgDHGPIRkGeRGdxBPEWWMscGMu4MYY4wNJtwSYIwxT5EJEEO4JbBhg3ODrjtfJpOp0/i9e/di3rx5CA8PR1BQEKZOnYqDBw+6nWnGGBuQiJzTPHv9GuCVAADEx8ejqqpKeVkslk5jjx49innz5uHAgQMoKSnB7NmzkZmZiY8//titTDPGGPOMHncHaTSaLn/93+mVV15xeb9p0ybs27cP+/fvR3Jyck+TZoyxAY1kArnRHUSDoSVw9uxZmM1mjBo1CllZWTh//ny3z5VlGc3NzQgJ6XrTL5vNhqamJpcXY4wNeG51Bcn9smK4R5VAamoqtm/fjoMHD2Lbtm2orq7GtGnTcPXq1W6d/8tf/hLXr1/Ho4/e/TBvV3l5eTAajcpr2LBhPckmY4z1C5LJ7Ze3CXKj/XH9+nWMHj0aa9euxQ9+8IMuY/Pz8/HEE09g3759mDt3bpexNpsNNptNed/U1IRhw4bBarUiKCiot9lljPmgpqYmGI3GPr1/3EpjlvgGNELb6+s4yI6/09tevde5NUU0ICAAiYmJOHv2bJdxu3btwuOPP47du3ffswIAAEmSIEm3HxJyq57ibiHGWE/dum94o7/dQTa3unQcsHswN93jViVgs9lw+vRpzJw5s9OY/Px8rFy5Evn5+UhPT+9VOs3NzQDA3UKMsV5rbm6G0Wjsk2vrdDqYTCZ8WH3A7WuZTCbodDoP5Kp7etQd9KMf/QiZmZkYPnw4ampq8MILL+DIkSOwWCwYMWIEnn/+eVRWVmL79u0AnBXAY489hi1btmDx4sXKdfR6fY/+Z8iyjMuXL8NgMAzpB4nf6va6dOkSd3v1AJdbz/lSmRERmpubYTaboVL13SYJLS0taG1tdfs6Op0Ofn5+HshR9/SoJVBRUYHs7GzU1dUhPDwcU6ZMwbFjxzBixAgAQFVVFS5evKjEv/7663A4HMjJyUFOTo7y+fLly/Hmm292O12VSoWYmJieZHVQCwoKGvJ/mH2By63nfKXM+qoFcCc/Pz+v3rw9xa2BYeZZ3hjAGoq43HqOy4zdwhvIMcaYD+NKYACRJAnr1693mRnF7o3Lree4zNgt3B3EGGM+jFsCjDHmw7gSYIwxH8aVAGOM+TCuBBhjzIdxJdBLeXl5EEIgNzdX+YyIsGHDBpjNZuj1esyaNQunTp1yOc9ms+Hpp59GWFgYAgIC8PWvfx0VFRUuMQ0NDVi2bJmyi+qyZcvQ2NjoEnPx4kVkZmYiICAAYWFhWL16dbvVihaLBWlpadDr9YiOjsbGjRv7Zb/yyspKLF26FKGhofD398ekSZNQUlKiHOdyc+VwOPCTn/wEo0aNgl6vR2xsLDZu3AhZvr0nDZcZ8xhiPVZcXEwjR46kpKQkWrNmjfL55s2byWAw0J49e8hisdC3v/1tioqKoqamJiXmySefpOjoaDp06BCVlpbS7NmzaeLEieRwOJSYhQsXUkJCAhUWFlJhYSElJCRQRkaGctzhcFBCQgLNnj2bSktL6dChQ2Q2m2nVqlVKjNVqpcjISMrKyiKLxUJ79uwhg8FAL7/8ct8Wzl3q6+tpxIgRtGLFCjp+/DiVl5fT4cOH6dy5c0oMl5urF154gUJDQ+ndd9+l8vJy2r17NwUGBtIrr7yixHCZMU/hSqCHmpubKS4ujg4dOkRpaWlKJSDLMplMJtq8ebMS29LSQkajkX77298SEVFjYyNptVrauXOnElNZWUkqlYree+89IiL67LPPCAAdO3ZMiSkqKiIA9PnnnxMR0YEDB0ilUlFlZaUSk5+fT5IkkdVqJSKi1157jYxGI7W0tCgxeXl5ZDabSZZlD5dK59atW0czZszo9DiXW3vp6em0cuVKl88WL15MS5cuJSIuM+ZZ3B3UQzk5OUhPT2+3JXZ5eTmqq6sxf/585TNJkpCWlobCwkIAQElJCex2u0uM2WxGQkKCElNUVASj0YjU1FQlZsqUKTAajS4xCQkJMJvNSsyCBQtgs9mUbpaioiKkpaW5LAZasGABLl++jAsXLnioNO7tz3/+M1JSUvDII48gIiICycnJ2LZtm3Kcy629GTNm4P3330dZWRkA4JNPPsGHH36IRYsWAeAyY57FlUAP7Ny5E6WlpcjLy2t3rLq6GgAQGRnp8nlkZKRyrLq6GjqdDsHBwV3GREREtLt+RESES8zd6QQHB0On03UZc+v9rRhvOH/+PLZu3Yq4uDgcPHgQTz75JFavXq3sNMvl1t66deuQnZ2NcePGQavVIjk5Gbm5ucjOznbJB5cZ8wS3nifgSy5duoQ1a9agoKCgy50C797qmojuuf313TEdxXsihr4cqPPmdtyyLCMlJQWbNm0CACQnJ+PUqVPYunUrHnvssS7z6qvltmvXLuzYsQNvvfUW4uPjceLECeTm5sJsNmP58uVd5tNXy4z1HrcEuqmkpAQ1NTWYPHkyNBoNNBoNjhw5gldffRUajabTXz41NTXKMZPJhNbWVjQ0NHQZc+XKlXbp19bWusTcnU5DQwPsdnuXMTU1NQDa/4LsS1FRUZgwYYLLZ+PHj1e2HDeZTAC43O707LPP4rnnnkNWVhYSExOxbNkyPPPMM0oLlMuMeRJXAt00Z84cWCwWnDhxQnmlpKRgyZIlOHHiBGJjY2EymXDo0CHlnNbWVhw5cgTTpk0DAEyePBlardYlpqqqCidPnlRipk6dCqvViuLiYiXm+PHjsFqtLjEnT55EVVWVElNQUABJkjB58mQl5ujRoy5T+QoKCmA2mzFy5EjPF1Anpk+fjjNnzrh8VlZWpjyDYtSoUVxud7lx40a7h5+o1WpliiiXGfOofhiMHjLunB1E5Jy2ZzQaae/evWSxWCg7O7vDaXsxMTF0+PBhKi0tpQcffLDDaXtJSUlUVFRERUVFlJiY2OG0vTlz5lBpaSkdPnyYYmJiXKbtNTY2UmRkJGVnZ5PFYqG9e/dSUFCQ16ftFRcXk0ajoRdffJHOnj1Lf/zjH8nf35927NihxHC5uVq+fDlFR0crU0T37t1LYWFhtHbtWiWGy4x5ClcCbri7EpBlmdavX08mk4kkSaIHHniALBaLyzk3b96kVatWUUhICOn1esrIyKCLFy+6xFy9epWWLFlCBoOBDAYDLVmyhBoaGlxivvjiC0pPTye9Xk8hISG0atUqlyl6RESffvopzZw5kyRJIpPJRBs2bOiXKXv79++nhIQEkiSJxo0bR2+88YbLcS43V01NTbRmzRoaPnw4+fn5UWxsLP34xz8mm82mxHCZMU/hraQZY8yH8ZgAY4z5MK4EGGPMh3ElwBhjPowrAcYY82FcCTDGmA/jSoAxxnwYVwKMMebDuBJgjDEfxpUAY4z5MK4EGGPMh3ElwBhjPowrAcYY82H/D90zHtM8wT3HAAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "gdf.plot(\"area\", legend=True)" ] }, { "cell_type": "code", "execution_count": 69, "id": "27c5cf8e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 Schleswig-Holstein\n", "1 Hamburg\n", "2 Niedersachsen\n", "3 Bremen\n", "4 Nordrhein-Westfalen\n", "5 Hessen\n", "6 Rheinland-Pfalz\n", "7 Baden-Württemberg\n", "8 Bayern\n", "9 Saarland\n", "10 Berlin\n", "11 Brandenburg\n", "12 Mecklenburg-Vorpommern\n", "13 Sachsen\n", "14 Sachsen-Anhalt\n", "15 Thüringen\n", "16 Schleswig-Holstein\n", "17 Hamburg\n", "18 Niedersachsen\n", "19 Niedersachsen\n", "20 Bremen\n", "21 Mecklenburg-Vorpommern\n", "22 Baden-Württemberg (Bodensee)\n", "23 Bayern (Bodensee)\n", "Name: GEN, dtype: object" ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ "gdf.GEN" ] }, { "cell_type": "code", "execution_count": 70, "id": "53069624", "metadata": {}, "outputs": [], "source": [ "gdf.AGS = gdf.AGS.astype(str)" ] }, { "cell_type": "markdown", "id": "fce92e3e", "metadata": {}, "source": [ "### Merge `GeoDataFrame` with Data and Visualize on the Map\n", "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~" ] }, { "cell_type": "code", "execution_count": 102, "id": "877c61cc", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 102, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(10, 5))\n", "\n", "ax1 = fig.add_subplot(131)\n", "year = 2015\n", "plt.title(str(year))\n", "gdf_merged = pd.merge(\n", " left=gdf,\n", " right=ratio_international[ratio_international.year == year],\n", " left_on=\"AGS\",\n", " right_on=\"Kreise und kreisfreie Städte_Code\",\n", ")\n", "gdf_merged.ratio_international\n", "gdf_merged.plot(\n", " \"ratio_international\",\n", " ax=ax1,\n", " legend=True,\n", " missing_kwds={\"color\": \"lightgrey\"},\n", " legend_kwds={\n", " \"label\": \"ratio of int. students\",\n", " \"orientation\": \"horizontal\",\n", " },\n", " vmin=0.08,\n", " vmax=0.23,\n", ")\n", "\n", "ax2 = fig.add_subplot(132)\n", "year = 2018\n", "plt.title(str(year))\n", "gdf_merged = pd.merge(\n", " left=gdf,\n", " right=ratio_international[ratio_international.year == year],\n", " left_on=\"AGS\",\n", " right_on=\"Kreise und kreisfreie Städte_Code\",\n", ")\n", "gdf_merged.ratio_international\n", "gdf_merged.plot(\n", " \"ratio_international\",\n", " ax=ax2,\n", " legend=True,\n", " missing_kwds={\"color\": \"lightgrey\"},\n", " legend_kwds={\n", " \"label\": \"ratio of int. students\",\n", " \"orientation\": \"horizontal\",\n", " },\n", " vmin=0.08,\n", " vmax=0.23,\n", ")\n", "\n", "ax3 = fig.add_subplot(133)\n", "year = 2021\n", "plt.title(str(year))\n", "gdf_merged = pd.merge(\n", " left=gdf,\n", " right=ratio_international[ratio_international.year == year],\n", " left_on=\"AGS\",\n", " right_on=\"Kreise und kreisfreie Städte_Code\",\n", ")\n", "gdf_merged.ratio_international\n", "gdf_merged.plot(\n", " \"ratio_international\",\n", " ax=ax3,\n", " legend=True,\n", " missing_kwds={\"color\": \"lightgrey\"},\n", " legend_kwds={\n", " \"label\": \"ratio of int. students\",\n", " \"orientation\": \"horizontal\",\n", " },\n", " vmin=0.08,\n", " vmax=0.23,\n", ")" ] }, { "cell_type": "markdown", "id": "7d7fffc9", "metadata": {}, "source": [ "Outlook\n", "-------\n", "\n", "- `quality=on` -> handle the different quality identifiers\n", "- `Find` to work across all databases -> search for and find results over all supported databases with a single query\n", "- `LLM`? -> ideation: provide some kind of interface that allows to talk with GENESIS via a LLM like ChatGPT" ] }, { "cell_type": "markdown", "id": "d8b9d035", "metadata": {}, "source": [] } ], "metadata": { "jupytext": { "formats": "ipynb,py:percent" }, "kernelspec": { "display_name": "pystatis", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.6" } }, "nbformat": 4, "nbformat_minor": 5 }