katiagithub-web
#api-covid-pandas
!pip install pandas
Requirement already satisfied: pandas in c:\users\katia\anaconda3\lib\site-packages (1.4.2)
Requirement already satisfied: pytz>=2020.1 in c:\users\katia\anaconda3\lib\site-packages (from pandas) (2021.3)
Requirement already satisfied: numpy>=1.18.5 in c:\users\katia\anaconda3\lib\site-packages (from pandas) (1.21.5)
Requirement already satisfied: python-dateutil>=2.8.1 in c:\users\katia\anaconda3\lib\site-packages (from pandas) (2.8.2)
Requirement already satisfied: six>=1.5 in c:\users\katia\anaconda3\lib\site-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)
pip install numpy
Requirement already satisfied: numpy in c:\users\katia\anaconda3\lib\site-packages (1.21.5)
Note: you may need to restart the kernel to use updated packages.
import pandas as pd
url = 'https://api.covid19api.com/countries'
url
'https://api.covid19api.com/countries'
df = pd.read_json(url)
df
| Country | Slug | ISO2 | |
|---|---|---|---|
| 0 | Gibraltar | gibraltar | GI |
| 1 | Oman | oman | OM |
| 2 | France | france | FR |
| 3 | Jersey | jersey | JE |
| 4 | Mali | mali | ML |
| ... | ... | ... | ... |
| 243 | Puerto Rico | puerto-rico | PR |
| 244 | Papua New Guinea | papua-new-guinea | PG |
| 245 | Saint Pierre and Miquelon | saint-pierre-and-miquelon | PM |
| 246 | Timor-Leste | timor-leste | TL |
| 247 | Montenegro | montenegro | ME |
248 rows × 3 columns
df[df['Country'] == 'Spain']
| Country | Slug | ISO2 | |
|---|---|---|---|
| 141 | Spain | spain | ES |
url_rt_es = 'https://api.covid19api.com/country/spain/status/confirmed/live'
df_rt_es = pd.read_json(url_rt_es)
df_rt_es
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Spain | ES | 40.46 | -3.75 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | Spain | ES | 40.46 | -3.75 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | Spain | ES | 40.46 | -3.75 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | Spain | ES | 40.46 | -3.75 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | Spain | ES | 40.46 | -3.75 | 0 | confirmed | 2020-01-26 00:00:00+00:00 | |||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 893 | Spain | ES | 40.46 | -3.75 | 12818184 | confirmed | 2022-07-03 00:00:00+00:00 | |||
| 894 | Spain | ES | 40.46 | -3.75 | 12818184 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | Spain | ES | 40.46 | -3.75 | 12890002 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | Spain | ES | 40.46 | -3.75 | 12890002 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | Spain | ES | 40.46 | -3.75 | 12890002 | confirmed | 2022-07-07 00:00:00+00:00 |
898 rows × 10 columns
df_rt_es.head()
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Spain | ES | 40.46 | -3.75 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | Spain | ES | 40.46 | -3.75 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | Spain | ES | 40.46 | -3.75 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | Spain | ES | 40.46 | -3.75 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | Spain | ES | 40.46 | -3.75 | 0 | confirmed | 2020-01-26 00:00:00+00:00 |
df_rt_es.tail()
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 893 | Spain | ES | 40.46 | -3.75 | 12818184 | confirmed | 2022-07-03 00:00:00+00:00 | |||
| 894 | Spain | ES | 40.46 | -3.75 | 12818184 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | Spain | ES | 40.46 | -3.75 | 12890002 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | Spain | ES | 40.46 | -3.75 | 12890002 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | Spain | ES | 40.46 | -3.75 | 12890002 | confirmed | 2022-07-07 00:00:00+00:00 |
df_rt_es.set_index('Date')['Cases'].plot(title="Casos de Covid19 en España desde 20/1/202 hasta 29/6/22")
<AxesSubplot:title={'center':'Casos de Covid19 en España desde 20/1/202 hasta 29/6/22'}, xlabel='Date'>
df[df['Country'] == 'Panama']
| Country | Slug | ISO2 | |
|---|---|---|---|
| 190 | Panama | panama | PA |
url_rt_pa ='https://api.covid19api.com/country/panama/status/confirmed/live'
df_rt_pa = pd.read_json(url_rt_pa)
df_rt_pa
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Panama | PA | 8.54 | -80.78 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | Panama | PA | 8.54 | -80.78 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | Panama | PA | 8.54 | -80.78 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | Panama | PA | 8.54 | -80.78 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | Panama | PA | 8.54 | -80.78 | 0 | confirmed | 2020-01-26 00:00:00+00:00 | |||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 894 | Panama | PA | 8.54 | -80.78 | 925254 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | Panama | PA | 8.54 | -80.78 | 925254 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | Panama | PA | 8.54 | -80.78 | 925254 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | Panama | PA | 8.54 | -80.78 | 925254 | confirmed | 2022-07-07 00:00:00+00:00 | |||
| 898 | Panama | PA | 8.54 | -80.78 | 925254 | confirmed | 2022-07-09 00:00:00+00:00 |
899 rows × 10 columns
df_rt_pa.head()
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Panama | PA | 8.54 | -80.78 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | Panama | PA | 8.54 | -80.78 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | Panama | PA | 8.54 | -80.78 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | Panama | PA | 8.54 | -80.78 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | Panama | PA | 8.54 | -80.78 | 0 | confirmed | 2020-01-26 00:00:00+00:00 |
df_rt_pa.tail()
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 894 | Panama | PA | 8.54 | -80.78 | 925254 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | Panama | PA | 8.54 | -80.78 | 925254 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | Panama | PA | 8.54 | -80.78 | 925254 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | Panama | PA | 8.54 | -80.78 | 925254 | confirmed | 2022-07-07 00:00:00+00:00 | |||
| 898 | Panama | PA | 8.54 | -80.78 | 925254 | confirmed | 2022-07-09 00:00:00+00:00 |
df_rt_pa.set_index('Date')['Cases'].plot(title="Casos de Covid19 en Panama desde 20/1/202 hasta 29/6/22")
<AxesSubplot:title={'center':'Casos de Covid19 en Panama desde 20/1/202 hasta 29/6/22'}, xlabel='Date'>
df[df['Country'] == 'Peru']
| Country | Slug | ISO2 | |
|---|---|---|---|
| 49 | Peru | peru | PE |
url_rt_pe ='https://api.covid19api.com/country/peru/status/confirmed/live'
df_rt_pe = pd.read_json(url_rt_pe)
df_rt_pe
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Peru | PE | -9.19 | -75.02 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | Peru | PE | -9.19 | -75.02 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | Peru | PE | -9.19 | -75.02 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | Peru | PE | -9.19 | -75.02 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | Peru | PE | -9.19 | -75.02 | 0 | confirmed | 2020-01-26 00:00:00+00:00 | |||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 893 | Peru | PE | -9.19 | -75.02 | 3637529 | confirmed | 2022-07-03 00:00:00+00:00 | |||
| 894 | Peru | PE | -9.19 | -75.02 | 3640061 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | Peru | PE | -9.19 | -75.02 | 3644199 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | Peru | PE | -9.19 | -75.02 | 3650203 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | Peru | PE | -9.19 | -75.02 | 3656309 | confirmed | 2022-07-07 00:00:00+00:00 |
898 rows × 10 columns
df_rt_pe.head()
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Peru | PE | -9.19 | -75.02 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | Peru | PE | -9.19 | -75.02 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | Peru | PE | -9.19 | -75.02 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | Peru | PE | -9.19 | -75.02 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | Peru | PE | -9.19 | -75.02 | 0 | confirmed | 2020-01-26 00:00:00+00:00 |
df_rt_pe.tail()
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 893 | Peru | PE | -9.19 | -75.02 | 3637529 | confirmed | 2022-07-03 00:00:00+00:00 | |||
| 894 | Peru | PE | -9.19 | -75.02 | 3640061 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | Peru | PE | -9.19 | -75.02 | 3644199 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | Peru | PE | -9.19 | -75.02 | 3650203 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | Peru | PE | -9.19 | -75.02 | 3656309 | confirmed | 2022-07-07 00:00:00+00:00 |
df_rt_pe.set_index('Date')['Cases'].plot(title="Casos de Covid19 en Peru desde 20/1/202 hasta 29/6/22")
<AxesSubplot:title={'center':'Casos de Covid19 en Peru desde 20/1/202 hasta 29/6/22'}, xlabel='Date'>
casos_pa = df_rt_pa.set_index('Date')['Cases']
casos_pa.plot(title="Casos de Covid 19 en Panamá")
<AxesSubplot:title={'center':'Casos de Covid 19 en Panamá'}, xlabel='Date'>
pa_vs_es = pd.concat([casos_es,casos_pa],axis=1)
pa_vs_es
| Cases | Cases | |
|---|---|---|
| Date | ||
| 2020-01-22 00:00:00+00:00 | 0.0 | 0 |
| 2020-01-23 00:00:00+00:00 | 0.0 | 0 |
| 2020-01-24 00:00:00+00:00 | 0.0 | 0 |
| 2020-01-25 00:00:00+00:00 | 0.0 | 0 |
| 2020-01-26 00:00:00+00:00 | 0.0 | 0 |
| ... | ... | ... |
| 2022-07-04 00:00:00+00:00 | 12818184.0 | 925254 |
| 2022-07-05 00:00:00+00:00 | 12890002.0 | 925254 |
| 2022-07-06 00:00:00+00:00 | 12890002.0 | 925254 |
| 2022-07-07 00:00:00+00:00 | 12890002.0 | 925254 |
| 2022-07-09 00:00:00+00:00 | NaN | 925254 |
899 rows × 2 columns
pa_vs_es.columns = ['España', 'Panamá']
pa_vs_es
| España | Panamá | |
|---|---|---|
| Date | ||
| 2020-01-22 00:00:00+00:00 | 0.0 | 0 |
| 2020-01-23 00:00:00+00:00 | 0.0 | 0 |
| 2020-01-24 00:00:00+00:00 | 0.0 | 0 |
| 2020-01-25 00:00:00+00:00 | 0.0 | 0 |
| 2020-01-26 00:00:00+00:00 | 0.0 | 0 |
| ... | ... | ... |
| 2022-07-04 00:00:00+00:00 | 12818184.0 | 925254 |
| 2022-07-05 00:00:00+00:00 | 12890002.0 | 925254 |
| 2022-07-06 00:00:00+00:00 | 12890002.0 | 925254 |
| 2022-07-07 00:00:00+00:00 | 12890002.0 | 925254 |
| 2022-07-09 00:00:00+00:00 | NaN | 925254 |
899 rows × 2 columns
pa_vs_es.plot(title="Comparativa Covid19 España-Panamá")
<AxesSubplot:title={'center':'Comparativa Covid19 España-Panamá'}, xlabel='Date'>
df[df['Country'] == 'Costa Rica']
| Country | Slug | ISO2 | |
|---|---|---|---|
| 242 | Costa Rica | costa-rica | CR |
url_casos_cr = 'https://api.covid19api.com/country/costa-rica/status/confirmed/live'
df_rt_cr = pd.read_json(url_casos_cr)
df_rt_cr
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Costa Rica | CR | 9.75 | -83.75 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | Costa Rica | CR | 9.75 | -83.75 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | Costa Rica | CR | 9.75 | -83.75 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | Costa Rica | CR | 9.75 | -83.75 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | Costa Rica | CR | 9.75 | -83.75 | 0 | confirmed | 2020-01-26 00:00:00+00:00 | |||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 894 | Costa Rica | CR | 9.75 | -83.75 | 904934 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | Costa Rica | CR | 9.75 | -83.75 | 904934 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | Costa Rica | CR | 9.75 | -83.75 | 904934 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | Costa Rica | CR | 9.75 | -83.75 | 904934 | confirmed | 2022-07-07 00:00:00+00:00 | |||
| 898 | Costa Rica | CR | 9.75 | -83.75 | 904934 | confirmed | 2022-07-09 00:00:00+00:00 |
899 rows × 10 columns
url_casos_cr = 'https://api.covid19api.com/country/costa-rica/status/confirmed/live'
df_rt_cr = pd.read_json(url_casos_cr)
casos_cr = df_rt_cr.set_index('Date')['Cases']
casos_cr.plot(title="Casos de Covid19 en Costa Rica")
<AxesSubplot:title={'center':'Casos de Covid19 en Costa Rica'}, xlabel='Date'>
df[df['Country'] == 'El Salvador']
| Country | Slug | ISO2 | |
|---|---|---|---|
| 139 | El Salvador | el-salvador | SV |
url_casos_sv = 'https://api.covid19api.com/country/el-salvador/status/confirmed/live'
df_rt_sv = pd.read_json(url_casos_sv)
df_rt_sv
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | El Salvador | SV | 13.79 | -88.9 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | El Salvador | SV | 13.79 | -88.9 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | El Salvador | SV | 13.79 | -88.9 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | El Salvador | SV | 13.79 | -88.9 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | El Salvador | SV | 13.79 | -88.9 | 0 | confirmed | 2020-01-26 00:00:00+00:00 | |||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 894 | El Salvador | SV | 13.79 | -88.9 | 169646 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | El Salvador | SV | 13.79 | -88.9 | 169646 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | El Salvador | SV | 13.79 | -88.9 | 169646 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | El Salvador | SV | 13.79 | -88.9 | 169646 | confirmed | 2022-07-07 00:00:00+00:00 | |||
| 898 | El Salvador | SV | 13.79 | -88.9 | 169646 | confirmed | 2022-07-09 00:00:00+00:00 |
899 rows × 10 columns
casos_sv = df_rt_sv.set_index('Date')['Cases']
casos_sv.plot(title="Casos de Covid-19 en El Salvador")
<AxesSubplot:title={'center':'Casos de Covid-19 en El Salvador'}, xlabel='Date'>
df[df['Country'] == 'Nicaragua']
| Country | Slug | ISO2 | |
|---|---|---|---|
| 36 | Nicaragua | nicaragua | NI |
url_casos_ni = 'https://api.covid19api.com/country/nicaragua/status/confirmed/live'
df_rt_ni = pd.read_json(url_casos_ni)
df_rt_ni
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Nicaragua | NI | 12.87 | -85.21 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | Nicaragua | NI | 12.87 | -85.21 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | Nicaragua | NI | 12.87 | -85.21 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | Nicaragua | NI | 12.87 | -85.21 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | Nicaragua | NI | 12.87 | -85.21 | 0 | confirmed | 2020-01-26 00:00:00+00:00 | |||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 894 | Nicaragua | NI | 12.87 | -85.21 | 14690 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | Nicaragua | NI | 12.87 | -85.21 | 14690 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | Nicaragua | NI | 12.87 | -85.21 | 14721 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | Nicaragua | NI | 12.87 | -85.21 | 14721 | confirmed | 2022-07-07 00:00:00+00:00 | |||
| 898 | Nicaragua | NI | 12.87 | -85.21 | 14721 | confirmed | 2022-07-09 00:00:00+00:00 |
899 rows × 10 columns
url_casos_ni = 'https://api.covid19api.com/country/nicaragua/status/confirmed/live'
df_rt_ni = pd.read_json(url_casos_ni)
casos_ni = df_rt_ni.set_index('Date')['Cases']
casos_ni.plot(title="Casos de Covid19 en Nicaragua")
<AxesSubplot:title={'center':'Casos de Covid19 en Nicaragua'}, xlabel='Date'>
df[df['Country'] == 'Honduras']
| Country | Slug | ISO2 | |
|---|---|---|---|
| 91 | Honduras | honduras | HN |
url_casos_hn = 'https://api.covid19api.com/country/honduras/status/confirmed/live'
df_rt_hn = pd.read_json(url_casos_hn)
df_rt_hn
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Honduras | HN | 15.2 | -86.24 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | Honduras | HN | 15.2 | -86.24 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | Honduras | HN | 15.2 | -86.24 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | Honduras | HN | 15.2 | -86.24 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | Honduras | HN | 15.2 | -86.24 | 0 | confirmed | 2020-01-26 00:00:00+00:00 | |||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 894 | Honduras | HN | 15.2 | -86.24 | 427718 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | Honduras | HN | 15.2 | -86.24 | 427718 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | Honduras | HN | 15.2 | -86.24 | 427718 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | Honduras | HN | 15.2 | -86.24 | 427718 | confirmed | 2022-07-07 00:00:00+00:00 | |||
| 898 | Honduras | HN | 15.2 | -86.24 | 429408 | confirmed | 2022-07-09 00:00:00+00:00 |
899 rows × 10 columns
url_casos_hn = 'https://api.covid19api.com/country/honduras/status/confirmed/live'
df_rt_hn = pd.read_json(url_casos_hn)
casos_hn = df_rt_hn.set_index('Date')['Cases']
casos_hn.plot(title="Casos de Covid19 en Honduras")
<AxesSubplot:title={'center':'Casos de Covid19 en Honduras'}, xlabel='Date'>
df[df['Country'] == 'Guatemala']
| Country | Slug | ISO2 | |
|---|---|---|---|
| 239 | Guatemala | guatemala | GT |
url_casos_gt = 'https://api.covid19api.com/country/guatemala/status/confirmed/live'
df_rt_gt = pd.read_json(url_casos_gt)
df_rt_gt
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Guatemala | GT | 15.78 | -90.23 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | Guatemala | GT | 15.78 | -90.23 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | Guatemala | GT | 15.78 | -90.23 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | Guatemala | GT | 15.78 | -90.23 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | Guatemala | GT | 15.78 | -90.23 | 0 | confirmed | 2020-01-26 00:00:00+00:00 | |||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 894 | Guatemala | GT | 15.78 | -90.23 | 921146 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | Guatemala | GT | 15.78 | -90.23 | 922340 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | Guatemala | GT | 15.78 | -90.23 | 927473 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | Guatemala | GT | 15.78 | -90.23 | 933259 | confirmed | 2022-07-07 00:00:00+00:00 | |||
| 898 | Guatemala | GT | 15.78 | -90.23 | 939300 | confirmed | 2022-07-09 00:00:00+00:00 |
899 rows × 10 columns
url_casos_gt = 'https://api.covid19api.com/country/guatemala/status/confirmed/live'
df_rt_gt = pd.read_json(url_casos_gt)
casos_gt = df_rt_gt.set_index('Date')['Cases']
casos_gt.plot(title="Casos de Covid19 en Guatemala")
<AxesSubplot:title={'center':'Casos de Covid19 en Guatemala'}, xlabel='Date'>
df[df['Country'] == 'Costa Rica']
| Country | Slug | ISO2 | |
|---|---|---|---|
| 242 | Costa Rica | costa-rica | CR |
url_casos_cr = 'https://api.covid19api.com/country/costa-rica/status/confirmed/live'
df_rt_cr = pd.read_json(url_casos_cr)
df_rt_cr
| Country | CountryCode | Province | City | CityCode | Lat | Lon | Cases | Status | Date | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Costa Rica | CR | 9.75 | -83.75 | 0 | confirmed | 2020-01-22 00:00:00+00:00 | |||
| 1 | Costa Rica | CR | 9.75 | -83.75 | 0 | confirmed | 2020-01-23 00:00:00+00:00 | |||
| 2 | Costa Rica | CR | 9.75 | -83.75 | 0 | confirmed | 2020-01-24 00:00:00+00:00 | |||
| 3 | Costa Rica | CR | 9.75 | -83.75 | 0 | confirmed | 2020-01-25 00:00:00+00:00 | |||
| 4 | Costa Rica | CR | 9.75 | -83.75 | 0 | confirmed | 2020-01-26 00:00:00+00:00 | |||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 894 | Costa Rica | CR | 9.75 | -83.75 | 904934 | confirmed | 2022-07-04 00:00:00+00:00 | |||
| 895 | Costa Rica | CR | 9.75 | -83.75 | 904934 | confirmed | 2022-07-05 00:00:00+00:00 | |||
| 896 | Costa Rica | CR | 9.75 | -83.75 | 904934 | confirmed | 2022-07-06 00:00:00+00:00 | |||
| 897 | Costa Rica | CR | 9.75 | -83.75 | 904934 | confirmed | 2022-07-07 00:00:00+00:00 | |||
| 898 | Costa Rica | CR | 9.75 | -83.75 | 904934 | confirmed | 2022-07-09 00:00:00+00:00 |
899 rows × 10 columns
url_casos_cr = 'https://api.covid19api.com/country/costa-rica/status/confirmed/live'
df_rt_cr = pd.read_json(url_casos_cr)
casos_cr = df_rt_cr.set_index('Date')['Cases']
casos_cr.plot(title="Casos de Covid19 en Costa Rica")
<AxesSubplot:title={'center':'Casos de Covid19 en Costa Rica'}, xlabel='Date'>
pa_vs_sv_vs_ni_vs_cr_vs_gt_vs_hn = pd.concat([casos_pa,casos_sv,casos_ni,casos_cr,casos_gt,casos_hn],axis=1)
pa_vs_sv_vs_ni_vs_cr_vs_gt_vs_hn
| Cases | Cases | Cases | Cases | Cases | Cases | |
|---|---|---|---|---|---|---|
| Date | ||||||
| 2020-01-22 00:00:00+00:00 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2020-01-23 00:00:00+00:00 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2020-01-24 00:00:00+00:00 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2020-01-25 00:00:00+00:00 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2020-01-26 00:00:00+00:00 | 0 | 0 | 0 | 0 | 0 | 0 |
| ... | ... | ... | ... | ... | ... | ... |
| 2022-07-04 00:00:00+00:00 | 925254 | 169646 | 14690 | 904934 | 921146 | 427718 |
| 2022-07-05 00:00:00+00:00 | 925254 | 169646 | 14690 | 904934 | 922340 | 427718 |
| 2022-07-06 00:00:00+00:00 | 925254 | 169646 | 14721 | 904934 | 927473 | 427718 |
| 2022-07-07 00:00:00+00:00 | 925254 | 169646 | 14721 | 904934 | 933259 | 427718 |
| 2022-07-09 00:00:00+00:00 | 925254 | 169646 | 14721 | 904934 | 939300 | 429408 |
899 rows × 6 columns
pa_vs_sv_vs_ni_vs_cr_vs_gt_vs_hn.columns = ['Panamá', 'El Savador', 'Nicaragua', 'Costa Rica', 'Guatemala', 'Honduras']
pa_vs_sv_vs_ni_vs_cr_vs_gt_vs_hn
| Panamá | El Savador | Nicaragua | Costa Rica | Guatemala | Honduras | |
|---|---|---|---|---|---|---|
| Date | ||||||
| 2020-01-22 00:00:00+00:00 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2020-01-23 00:00:00+00:00 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2020-01-24 00:00:00+00:00 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2020-01-25 00:00:00+00:00 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2020-01-26 00:00:00+00:00 | 0 | 0 | 0 | 0 | 0 | 0 |
| ... | ... | ... | ... | ... | ... | ... |
| 2022-07-04 00:00:00+00:00 | 925254 | 169646 | 14690 | 904934 | 921146 | 427718 |
| 2022-07-05 00:00:00+00:00 | 925254 | 169646 | 14690 | 904934 | 922340 | 427718 |
| 2022-07-06 00:00:00+00:00 | 925254 | 169646 | 14721 | 904934 | 927473 | 427718 |
| 2022-07-07 00:00:00+00:00 | 925254 | 169646 | 14721 | 904934 | 933259 | 427718 |
| 2022-07-09 00:00:00+00:00 | 925254 | 169646 | 14721 | 904934 | 939300 | 429408 |
899 rows × 6 columns
pa_vs_sv_vs_ni_vs_cr_vs_gt_vs_hn.plot(title="Comparación del virus Covid-19 en países de Centroamérica")
<AxesSubplot:title={'center':'Comparación del virus Covid-19 en países de Centroamérica'}, xlabel='Date'>
