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linting pt.1
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‎README.md‎

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```bash
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git clone https://github.com/fccoelho/PySUS.git
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```
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```
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then from within the PySUS directory build the container
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```bash
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Once you are done, you can stop the container with a simple `ctrl-c` from the terminal you started it or use the following command:
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```bash
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# to find the container ID
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docker ps
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docker ps
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docker stop <CONTAINER ID>
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```
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### Mounting your working directory in the container
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In Docker, just add an extra parameter `-e PYSUS_CACHEPATH="/home/me/desired/path/.pysus"` when starting the container:
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```bash
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docker run -p 8888:8888 -e PYSUS_CACHEPATH="/home/me/desired/path/.pysus" pysus:latest
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docker run -p 8888:8888 -e PYSUS_CACHEPATH="/home/me/desired/path/.pysus" pysus:latest
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```
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## Examples
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In[1]: from pysus.online_data.sinasc import download
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In[2]: df = download('SE', 2015)
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In[3]: df.head()
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Out[3]:
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NUMERODN CODINST ORIGEM ... TPROBSON PARIDADE KOTELCHUCK
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0 19533794 MSE2805100001 1 ... 11 1 9
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1 52927108 MSE2802700001 1 ... 11 1 9
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In[1]: from pysus.online_data.SIM import download
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In[2]: df = download('ba', 2007)
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In[3]: df.head()
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Out[3]:
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NUMERODO TIPOBITO DTOBITO ... UFINFORM CODINST CB_PRE
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0 01499664 2 30072007 ... 29 RBA2914800001 C229
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1 09798190 2 04072007 ... 29 RBA2914800001 R98
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In[1]: from pysus.online_data.CIHA import download
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In[2]: df = download('mg', 2009, 7)
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In[3]: df.head()
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ANO_CMPT MES_CMPT ESPEC CGC_HOSP ... CAR_INT HOMONIMO CNES FONTE
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0 2009 07 16505851000126 ... 2126796 1
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1 2009 07 16505851000126 ... 2126796 2
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In[1]: from pysus.online_data.SIA import download
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In[2]: bi, ps = download('AC', 2020, 3, group=["BI", "PS"])
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In[3]: bi.head()
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CODUNI GESTAO CONDIC UFMUN TPUPS ... VL_APROV UFDIF MNDIF ETNIA NAT_JUR
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0 2000733 120000 EP 120040 07 ... 24.2 0 0 1023
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1 2001063 120000 EP 120040 36 ... 7.3 0 0 1023

‎condarecipe/pysus/meta.yaml‎

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home: "https://github.com/fccoelho/PySUS"
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license: gpl-v3
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license_family: GPL3
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license_file:
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license_file:
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summary: "Tools for dealing with Brazil's Public health data"
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doc_url:
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dev_url:
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doc_url:
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dev_url:
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extra:
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recipe-maintainers:

‎docker/docker-compose.yaml‎

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version: '3.3'
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services:
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services:
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jupyter:
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build:
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context: ".."

‎docs/source/conf.py‎

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language = 'en'
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locale_dirs = ['locale']
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gettext_compact = False
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gettext_compact = False
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# There are two options for replacing |today|: either, you set today to some
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# non-false value, then it is used:

‎docs/source/rio.html‎

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<!DOCTYPE html>
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<head>
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<meta http-equiv="content-type" content="text/html; charset=UTF-8" />
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<script src="https://cdnjs.cloudflare.com/ajax/libs/leaflet/0.7.3/leaflet.js"></script>
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html, body {
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left:0;
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</style>
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<style> #map_309ce1ef971d4af68cd7a9bf39526cf5 {
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<script>
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layers: [],
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crs: L.CRS.EPSG3857
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var tile_layer_426a222503fd49d2b786a7b9b8b7fdf3 = L.tileLayer(
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'https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png',
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{
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).addTo(map_309ce1ef971d4af68cd7a9bf39526cf5);
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‎docs/source/tutorials/tutorials.rst‎

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PySUS includes some Jupyter notebooks in its distribution package to serve as tutorials.
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Preprocessing DATASUS data
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Preprocessing DATASUS data
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#. :doc:`Preprocessing SINAN`
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#. :doc:`Preprocessing SIM`

‎pysus/ftp/databases/cnes.py‎

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"long_name": "Cadastro Nacional de Estabelecimentos de Saúde",
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"source": "https://cnes.datasus.gov.br/",
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"description": (
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"O Cadastro Nacional de Estabelecimentos de Saúde (CNES) é o sistema "
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"de informação oficial de cadastramento de informações de todos os "
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"estabelecimentos de saúde no país, independentemente de sua natureza "
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"jurídica ou de integrarem o Sistema Único de Saúde (SUS). Trata-se do "
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"cadastro oficial do Ministério da Saúde (MS) no tocante à realidade da "
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"O Cadastro Nacional de Estabelecimentos de Saúde (CNES) é o "
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"de todos os estabelecimentos de saúde no país, independentemente "
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"de sua natureza jurídica ou de integrarem o Sistema Único de "
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"Saúde (SUS). Trata-se do cadastro oficial do Ministério da "
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"de saúde públicos ou privados, com convênio SUS ou não."
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),
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}
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groups = {

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