PySUS

This package collects a set of utilities for handling with public databases published by Brazil's DATASUS The documentation of how to use PySUS can be found here

Features

Decode encoded patient age to any time unit (years, months, etc)
Convert .dbc files to DBF databases or read them into pandas dataframes. DBC files are basically DBFs compressed by a proprietary algorithm.
Read SINAN dbf files returning DataFrames with properly typed columns
Download SINASC data
Download SIH data
Download SIA data
Download SIM data
Download CIHA data

Instalation

There are some dependencies which can't be installed through pip, namely libffi. Therefore on an ubuntu system:

sudo apt install libffi-dev

Then you can proceed to

sudo pip install PySUS

Examples

Reading SINAN files:

>>> from pysus.preprocessing.sinan import read_sinan_dbf

>>> df = read_sinan_dbf('mytest.dbf', encoding='latin-1')
>>> df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 65535 entries, 0 to 65534
Data columns (total 10 columns):
DT_DIGITA     65469 non-null object
DT_NOTIFIC    65535 non-null object
DT_SIN_PRI    65535 non-null object
ID_AGRAVO     65535 non-null object
ID_BAIRRO     50675 non-null float64
ID_MUNICIP    65535 non-null int64
NM_BAIRRO     60599 non-null object
NU_ANO        65535 non-null int64
SEM_NOT       65535 non-null int64
SEM_PRI       65535 non-null int64
dtypes: float64(1), int64(4), object(5)
memory usage: 5.0+ MB

>>> df.DT_DIGITA[0]
datetime.date(2016, 4, 1)

Reading .dbc file:

>>> from pysus.utilities.readdbc import read_dbc

>>> df = read_dbc(filename, encoding='iso-8859-1')
>>> df.info()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1239 entries, 0 to 1238
Data columns (total 58 columns):
AP_MVM        1239 non-null object
AP_CONDIC     1239 non-null object
AP_GESTAO     1239 non-null object
AP_CODUNI     1239 non-null object
AP_AUTORIZ    1239 non-null object
AP_CMP        1239 non-null object
AP_PRIPAL     1239 non-null object
AP_VL_AP      1239 non-null float64
...

Downloading and reading SINASC data:

In[1]: from pysus.online_data.sinasc import download
In[2]: df = download('SE', 2015)
In[3]: df.head()
Out[3]: 
   NUMERODN        CODINST ORIGEM    ...     TPROBSON PARIDADE KOTELCHUCK
0  19533794  MSE2805100001      1    ...           11        1          9
1  52927108  MSE2802700001      1    ...           11        1          9
2  54673238  MSE2804400001      1    ...           11        1          5
3  54673239  MSE2804400001      1    ...           10        1          3
4  54695292  MBA2916500001      1    ...           03        1          2
[5 rows x 64 columns]

Dowloading and reading SIM data:

In[1]: from pysus.online_data.SIM import download
In[2]: df = download('ba', 2007)
In[3]: df.head()
Out[3]: 
   NUMERODO TIPOBITO   DTOBITO  ...   UFINFORM        CODINST CB_PRE
0  01499664        2  30072007  ...         29  RBA2914800001   C229
1  09798190        2  04072007  ...         29  RBA2914800001    R98
2  01499665        2  25082007  ...         29  RBA2914800001    I10
3  10595623        2  11092007  ...         29  RBA2914800001   G839
4  10599666        2  09082007  ...         29  EBA2927400001   I499
[5 rows x 56 columns]

Dowloading and reading CIHA data:

In[1]: from pysus.online_data.CIHA import download
In[2]: df = download('mg', 2009, 7)
In[3]: df.head()
Out[3]: 
  ANO_CMPT MES_CMPT ESPEC        CGC_HOSP  ...  CAR_INT HOMONIMO     CNES FONTE
0     2009       07        16505851000126  ...                    2126796     1
1     2009       07        16505851000126  ...                    2126796     2
2     2009       07        16505851000126  ...                    2126796     6
3     2009       07        16505851000126  ...                    2126796     6
4     2009       07        16505851000126  ...                    2126796     1
[5 rows x 27 columns]

fabianofilho/PySUS

PySUS

Features

Instalation

Examples