Library for data mining about covid-19 in brazilian cities
Project description
CovidBr
Library for data mining about covid-19 in brazilian cities 📈📊📚
Installation
$ pip install covidbr -U
Examples
Get data from cities
import covidbr as cb
cb.show_console(True)
place = 'Juazeiro BA'
data_pet = cb.city(place)
getting the light data and working with it
dataset = data_city.dados
dados
casos mortos mortes_diarias casos_diarios population
23/mar/2020 1 0 0 1 218162
24/mar/2020 2 0 0 1 218162
25/mar/2020 2 0 0 0 218162
26/mar/2020 2 0 0 0 218162
27/mar/2020 2 0 0 0 218162
... ... ... ... ... ...
26/dez/2021 18752 417 0 0 218162
27/dez/2021 18752 417 0 0 218162
28/dez/2021 18752 417 0 0 218162
29/dez/2021 18752 417 0 0 218162
30/dez/2021 18752 417 0 0 218162
[648 rows x 5 columns]
getting the data of death's:
mortos = dataset['mortos']
mortos
23/mar/2020 0
24/mar/2020 0
25/mar/2020 0
26/mar/2020 0
27/mar/2020 0
...
26/dez/2021 417
27/dez/2021 417
28/dez/2021 417
29/dez/2021 417
30/dez/2021 417
Name: mortos, Length: 648, dtype: int64
getting the data of case's:
casos = dataset['casos']
23/mar/2020 1
24/mar/2020 2
25/mar/2020 2
26/mar/2020 2
27/mar/2020 2
...
26/dez/2021 18752
27/dez/2021 18752
28/dez/2021 18752
29/dez/2021 18752
30/dez/2021 18752
Name: casos, Length: 648, dtype: int64
getting the mortality percent:
perc_m = (mortos/casos)*100
perc_m
23/mar/2020 0.000000
24/mar/2020 0.000000
25/mar/2020 0.000000
26/mar/2020 0.000000
27/mar/2020 0.000000
...
26/dez/2021 2.223763
27/dez/2021 2.223763
28/dez/2021 2.223763
29/dez/2021 2.223763
30/dez/2021 2.223763
Length: 648, dtype: float64
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