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In [1]:



    


import pandas as pd

AlertaDengue API

A API AlertaDengue foi desenhada para atender às Secretarias de Saúde que necessitam dos dados do sistema para a integração em suas próprias rotinas.

A API disponibiliza a seguinte funcionalidade:

  • consulta de dados de alertas para a cidade do Rio de Janeiro.

Consulta de dados de alertas para a cidade do Rio de Janeiro

Esssa funcionalidade está disponível por meio da URL:

https://info.dengue.mat.br/api/alertcity?<PARAMETROS_DA_CONSULTA>

Onde <PARAMETROS_DA_CONSULTA> deve conter os parâmetros:

  • geocode: código IBGE da cidade
  • disease: tipo de doença a ser consultado (str:dengue|chikungunya|zika)
  • format: formato de saída dos dados (str:json|csv)
  • ew_start: semana epidemiológica de início da consulta (int:1-53)
  • ew_end: semana epidemiológica de final da consulta (int:1-53)
  • e_year: ano de referência da consulta (int:0-9999)

Todos os parâmetros acima mencionados são obrigatórios para a consulta.

Abaixo, segue exemplo de requisição de registros de dengue entre a semana 1 e 50 do ano de 2017, em formato CSV:

https://info.dengue.mat.br/api/alertcity?geocode=3304557&disease=dengue&format=csv&ew_start=1&ew_end=50&e_year=2017

A continuação, seguem exemplos de uso da API referente a funcionalidade descrita.

Consulta em formato CSV





In [2]:



    


# 3304557 = Rio de Janeiro city geocode
url = 'http://localhost:8000/api/alertcity'
search_filter = (
    'geocode=3304557&disease=dengue&format=csv&' +
    'ew_start=1&ew_end=50&e_year=2017'
)
df = pd.read_csv('%s?%s' % (url, search_filter))
print(url)
df.head()



    


















    






http://localhost:8000/api/alertcity










    
Out[2]:











  
    

      
      id
      aps
      se
      data
      tweets
      casos
      casos_est
      casos_estmin
      casos_estmax
      tmin
      rt
      prt1
      inc
      nivel
    

  
  
    

      0
      190034
      2.1
      201724
      2017-06-11
      12
      1
      1.0
      1.0
      1.0
      18.8571
      0.349526
      0.137641
      0.180933
      1
    

    

      1
      213390
      2.1
      201733
      2017-08-13
      13
      5
      5.0
      5.0
      5.0
      19.7143
      1.777530
      0.797493
      0.904665
      1
    

    

      2
      217372
      2.1
      201734
      2017-08-20
      15
      2
      2.0
      2.0
      2.0
      18.2857
      0.664763
      0.311178
      0.361866
      1
    

    

      3
      225358
      2.1
      201737
      2017-09-10
      12
      3
      3.0
      3.0
      3.0
      17.9714
      1.266840
      0.616171
      0.542799
      1
    

    

      4
      229380
      2.1
      201738
      2017-09-17
      22
      4
      4.0
      4.0
      4.0
      18.3429
      1.820440
      0.783039
      0.723732
      1
    

  




















In [3]:



    


# 4106902 = Curitiba city geocode
url = 'http://localhost:8000/api/alertcity'
search_filter = (
    'geocode=4106902&disease=dengue&format=csv&' +
    'ew_start=1&ew_end=50&e_year=2017'
)
df = pd.read_csv('%s?%s' % (url, search_filter))
print(url)
df.head()



    


















    






http://localhost:8000/api/alertcity










    
Out[3]:











  
    

      
      data_iniSE
      SE
      casos_est
      casos_est_min
      casos_est_max
      casos
      p_rt1
      p_inc100k
      Localidade_id
      nivel
      id
      versao_modelo
    

  
  
    

      0
      2017-10-08
      201741
      22.0
      22
      22
      22
      0.477252
      1.16156
      0
      1
      4106902020174117533
      2018-01-02
    

    

      1
      2017-11-26
      201748
      20.0
      18
      21
      18
      0.265967
      1.05597
      0
      1
      4106902020174817533
      2018-01-02
    

    

      2
      2017-01-01
      201701
      130.0
      130
      130
      130
      0.999967
      6.86379
      0
      1
      4106902020170117533
      2018-01-02
    

    

      3
      2017-01-08
      201702
      142.0
      142
      142
      142
      0.997440
      7.49737
      0
      1
      4106902020170217533
      2018-01-02
    

    

      4
      2017-01-15
      201703
      143.0
      143
      143
      143
      0.913890
      7.55017
      0
      1
      4106902020170317533
      2018-01-02

Consulta em formato JSON





In [4]:



    


# 4106902 = Curitiba city geocode
search_filter = (
    'geocode=4106902&disease=dengue&format=json&' +
    'ew_start=1&ew_end=50&e_year=2017'
)
search_url = '%s?%s' % (url, search_filter)

df = pd.read_json(search_url)

print(search_url)
df.head()



    


















    






http://localhost:8000/api/alertcity?geocode=4106902&disease=dengue&format=json&ew_start=1&ew_end=50&e_year=2017










    
Out[4]:











  
    

      
      Localidade_id
      SE
      casos
      casos_est
      casos_est_max
      casos_est_min
      data_iniSE
      id
      nivel
      p_inc100k
      p_rt1
      versao_modelo
    

  
  
    

      0
      0
      201741
      22
      22
      22
      22
      1507420800000
      4106902020174117533
      1
      1.16156
      0.477252
      2018-01-02
    

    

      1
      0
      201748
      18
      20
      21
      18
      1511654400000
      4106902020174817533
      1
      1.05597
      0.265967
      2018-01-02
    

    

      2
      0
      201701
      130
      130
      130
      130
      1483228800000
      4106902020170117533
      1
      6.86379
      0.999967
      2018-01-02
    

    

      3
      0
      201702
      142
      142
      142
      142
      1483833600000
      4106902020170217533
      1
      7.49737
      0.997440
      2018-01-02
    

    

      4
      0
      201703
      143
      143
      143
      143
      1484438400000
      4106902020170317533
      1
      7.55017
      0.913890
      2018-01-02
    

  




















In [5]:



    


# 3304557 = Rio de Janeiro city geocode
search_filter = (
    'geocode=3304557&disease=dengue&format=json&' +
    'ew_start=1&ew_end=50&e_year=2017'
)
search_url = '%s?%s' % (url, search_filter)

df = pd.read_json(search_url)

print(search_url)
df.head()



    


















    






http://localhost:8000/api/alertcity?geocode=3304557&disease=dengue&format=json&ew_start=1&ew_end=50&e_year=2017










    
Out[5]:











  
    

      
      aps
      casos
      casos_est
      casos_estmax
      casos_estmin
      data
      id
      inc
      nivel
      prt1
      rt
      se
      tmin
      tweets
    

  
  
    

      0
      2.1
      1
      1
      1
      1
      1497139200000
      190034
      0.180933
      1
      0.137641
      0.349526
      201724
      18.8571
      12
    

    

      1
      2.1
      5
      5
      5
      5
      1502582400000
      213390
      0.904665
      1
      0.797493
      1.777530
      201733
      19.7143
      13
    

    

      2
      2.1
      2
      2
      2
      2
      1503187200000
      217372
      0.361866
      1
      0.311178
      0.664763
      201734
      18.2857
      15
    

    

      3
      2.1
      3
      3
      3
      3
      1505001600000
      225358
      0.542799
      1
      0.616171
      1.266840
      201737
      17.9714
      12
    

    

      4
      2.1
      4
      4
      4
      4
      1505606400000
      229380
      0.723732
      1
      0.783039
      1.820440
      201738
      18.3429
      22

Tratamento de Erros





In [6]:



    


params = [
    '',
    'disease=dengue',
    'geocode=3304557',
    'format=csv',
    'ew_start=1',
    'ew_end=50',
    'e_year=2017'
]

search_filter = ''
sep = ''
for param in params:
    print('-' * 80)
    
    search_filter += sep + param
    url_search = '%s?%s' % (url, search_filter)
    
    print(url_search)
    
    df = pd.read_csv(url_search)
    sep = '&'
    print(df.head())



    


















    






--------------------------------------------------------------------------------
http://localhost:8000/api/alertcity?
Empty DataFrame
Columns: [[EE] error_message: Disease sent is empty.]
Index: []
--------------------------------------------------------------------------------
http://localhost:8000/api/alertcity?&disease=dengue
Empty DataFrame
Columns: [[EE] error_message: GEO-Code sent is empty.]
Index: []
--------------------------------------------------------------------------------
http://localhost:8000/api/alertcity?&disease=dengue&geocode=3304557
Empty DataFrame
Columns: [[EE] error_message: Format sent is empty.]
Index: []
--------------------------------------------------------------------------------
http://localhost:8000/api/alertcity?&disease=dengue&geocode=3304557&format=csv
Empty DataFrame
Columns: [[EE] error_message: Epidemic start week sent is empty.]
Index: []
--------------------------------------------------------------------------------
http://localhost:8000/api/alertcity?&disease=dengue&geocode=3304557&format=csv&ew_start=1
Empty DataFrame
Columns: [[EE] error_message: Epidemic end week sent is empty.]
Index: []
--------------------------------------------------------------------------------
http://localhost:8000/api/alertcity?&disease=dengue&geocode=3304557&format=csv&ew_start=1&ew_end=50
Empty DataFrame
Columns: [[EE] error_message: Epidemic year sent is empty.]
Index: []
--------------------------------------------------------------------------------
http://localhost:8000/api/alertcity?&disease=dengue&geocode=3304557&format=csv&ew_start=1&ew_end=50&e_year=2017
       id  aps      se        data  tweets  casos  casos_est  casos_estmin  \
0  190034  2.1  201724  2017-06-11      12      1        1.0           1.0   
1  213390  2.1  201733  2017-08-13      13      5        5.0           5.0   
2  217372  2.1  201734  2017-08-20      15      2        2.0           2.0   
3  225358  2.1  201737  2017-09-10      12      3        3.0           3.0   
4  229380  2.1  201738  2017-09-17      22      4        4.0           4.0   

   casos_estmax     tmin        rt      prt1       inc  nivel  
0           1.0  18.8571  0.349526  0.137641  0.180933      1  
1           5.0  19.7143  1.777530  0.797493  0.904665      1  
2           2.0  18.2857  0.664763  0.311178  0.361866      1  
3           3.0  17.9714  1.266840  0.616171  0.542799      1  
4           4.0  18.3429  1.820440  0.783039  0.723732      1

Content source: AlertaDengue/AlertaDengue

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