brazil-monthly-deaths 1.4.0

数据帧

这个包裹出口一些 pandas带有 以下列：

• city_id：州和市的唯一整数
• 年份：2015年至2020年
• 月份：1-12
• 地区：【北部、东北部、南部、东南部、中部西部】
• 州：巴西27个州之一，包括首都
• 城市：城市名称
• 死亡人数：死亡人数

frombrazil_monthly_deathsimport(data,# full datadata_2015,data_2016,data_2017,data_2018,data_2019,data_2020# always out of date, you need to update it)

巴西死亡

您可以使用此函数直接从Civil Registry Offices website中删除新数据。只是 确保您已经安装了chrome驱动程序，如上所述。在

关于法定期限的官方说明：

The family has up to 24 hours after the death to register the death in the Registry, which, in turn, has up to five days to perform the death registration, and then up to eight days to send the act done to the National Information Center of the Civil Registry ( CRC Nacional), which updates this platform.

{/str}最后13天总是在变化

frombrazil_monthly_deathsimportbrazil_deaths

由于它将访问外部网站，它将取决于 互联网连接和世界位置。考虑只选择 states您要处理。对于每个月，对于所有的州 一年的跑步时间最长为6分钟。在

df=brazil_deaths(years=[2015,2016,2017,2018,2019,2020],months=range(1,13,1),regions=_regions_names,states=_states,filename="data",return_df=True,save_csv=True,verbose=True,*args,**kwargs)

_regions_names是：

["North","Northeast","South","Southeast","Center_West"]

_states是：

["Acre","Amazonas","Amapá","Pará","Rondônia","Roraima","Tocantins","Paraná","Rio Grande do Sul","Santa Catarina","Espírito Santo","Minas Gerais","Rio de Janeiro","São Paulo","Distrito Federal","Goiás","Mato Grosso do Sul","Mato Grosso","Alagoas","Bahia","Ceará","Maranhão","Paraíba","Pernambuco","Piauí","Rio Grande do Norte","Sergipe"]

将*args和**kwargs传递给 df.to_csv(..., *args, **kwargs)

更新_df

从Civil中获取最新数据后使用此函数 注册处网站更新此包中提供的数据。在

frombrazil_monthly_deathsimportbrazil_deaths,data,update_dfnew_data=brazil_deaths(years=[2020],months=[5])current_data=update_df(data,new_data)

它基本上是把新数据放在数据帧中旧数据的下面，然后 删除重复项（不包括死亡），保留最新的 条目。在

获取城市编号

获取state和city组合的唯一id。在

frombrazil_monthly_deathsimportget_city_idsao_paulo_id=get_city_id(state='São Paulo',city='São Paulo')print(sao_paulo_id)# 89903871