Usando los datos de COVID-19
library(data.table)
mydat<- read.csv('https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/owid-covid-data.csv')
#write.csv(mydat, "COVID19_world.csv")
gt(tail(mydat, n=4))| iso_code | continent | location | date | total_cases | new_cases | new_cases_smoothed | total_deaths | new_deaths | new_deaths_smoothed | total_cases_per_million | new_cases_per_million | new_cases_smoothed_per_million | total_deaths_per_million | new_deaths_per_million | new_deaths_smoothed_per_million | reproduction_rate | icu_patients | icu_patients_per_million | hosp_patients | hosp_patients_per_million | weekly_icu_admissions | weekly_icu_admissions_per_million | weekly_hosp_admissions | weekly_hosp_admissions_per_million | total_tests | new_tests | total_tests_per_thousand | new_tests_per_thousand | new_tests_smoothed | new_tests_smoothed_per_thousand | positive_rate | tests_per_case | tests_units | total_vaccinations | people_vaccinated | people_fully_vaccinated | total_boosters | new_vaccinations | new_vaccinations_smoothed | total_vaccinations_per_hundred | people_vaccinated_per_hundred | people_fully_vaccinated_per_hundred | total_boosters_per_hundred | new_vaccinations_smoothed_per_million | new_people_vaccinated_smoothed | new_people_vaccinated_smoothed_per_hundred | stringency_index | population_density | median_age | aged_65_older | aged_70_older | gdp_per_capita | extreme_poverty | cardiovasc_death_rate | diabetes_prevalence | female_smokers | male_smokers | handwashing_facilities | hospital_beds_per_thousand | life_expectancy | human_development_index | population | excess_mortality_cumulative_absolute | excess_mortality_cumulative | excess_mortality | excess_mortality_cumulative_per_million |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ZWE | Africa | Zimbabwe | 2024-03-28 | 266359 | 0 | 0 | 5740 | 0 | 0 | 16320.48 | 0 | 0 | 351.704 | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 42.729 | 19.6 | 2.822 | 1.882 | 1899.775 | 21.4 | 307.846 | 1.82 | 1.6 | 30.7 | 36.791 | 1.7 | 61.49 | 0.571 | 16320539 | NA | NA | NA | NA | |
| ZWE | Africa | Zimbabwe | 2024-03-29 | 266359 | 0 | 0 | 5740 | 0 | 0 | 16320.48 | 0 | 0 | 351.704 | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 42.729 | 19.6 | 2.822 | 1.882 | 1899.775 | 21.4 | 307.846 | 1.82 | 1.6 | 30.7 | 36.791 | 1.7 | 61.49 | 0.571 | 16320539 | NA | NA | NA | NA | |
| ZWE | Africa | Zimbabwe | 2024-03-30 | 266359 | 0 | 0 | 5740 | 0 | 0 | 16320.48 | 0 | 0 | 351.704 | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 42.729 | 19.6 | 2.822 | 1.882 | 1899.775 | 21.4 | 307.846 | 1.82 | 1.6 | 30.7 | 36.791 | 1.7 | 61.49 | 0.571 | 16320539 | NA | NA | NA | NA | |
| ZWE | Africa | Zimbabwe | 2024-03-31 | 266359 | 0 | 0 | 5740 | 0 | 0 | 16320.48 | 0 | 0 | 351.704 | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | 42.729 | 19.6 | 2.822 | 1.882 | 1899.775 | 21.4 | 307.846 | 1.82 | 1.6 | 30.7 | 36.791 | 1.7 | 61.49 | 0.571 | 16320539 | NA | NA | NA | NA |
## [1] "Afghanistan" "Africa"
## [3] "Albania" "Algeria"
## [5] "American Samoa" "Andorra"
## [7] "Angola" "Anguilla"
## [9] "Antigua and Barbuda" "Argentina"
## [11] "Armenia" "Aruba"
## [13] "Asia" "Australia"
## [15] "Austria" "Azerbaijan"
## [17] "Bahamas" "Bahrain"
## [19] "Bangladesh" "Barbados"
## [21] "Belarus" "Belgium"
## [23] "Belize" "Benin"
## [25] "Bermuda" "Bhutan"
## [27] "Bolivia" "Bonaire Sint Eustatius and Saba"
## [29] "Bosnia and Herzegovina" "Botswana"
## [31] "Brazil" "British Virgin Islands"
## [33] "Brunei" "Bulgaria"
## [35] "Burkina Faso" "Burundi"
## [37] "Cambodia" "Cameroon"
## [39] "Canada" "Cape Verde"
## [41] "Cayman Islands" "Central African Republic"
## [43] "Chad" "Chile"
## [45] "China" "Colombia"
## [47] "Comoros" "Congo"
## [49] "Cook Islands" "Costa Rica"
## [51] "Cote d'Ivoire" "Croatia"
## [53] "Cuba" "Curacao"
## [55] "Cyprus" "Czechia"
## [57] "Democratic Republic of Congo" "Denmark"
## [59] "Djibouti" "Dominica"
## [61] "Dominican Republic" "Ecuador"
## [63] "Egypt" "El Salvador"
## [65] "England" "Equatorial Guinea"
## [67] "Eritrea" "Estonia"
## [69] "Eswatini" "Ethiopia"
## [71] "Europe" "European Union"
## [73] "Faeroe Islands" "Falkland Islands"
## [75] "Fiji" "Finland"
## [77] "France" "French Guiana"
## [79] "French Polynesia" "Gabon"
## [81] "Gambia" "Georgia"
## [83] "Germany" "Ghana"
## [85] "Gibraltar" "Greece"
## [87] "Greenland" "Grenada"
## [89] "Guadeloupe" "Guam"
## [91] "Guatemala" "Guernsey"
## [93] "Guinea" "Guinea-Bissau"
## [95] "Guyana" "Haiti"
## [97] "High income" "Honduras"
## [99] "Hong Kong" "Hungary"
## [101] "Iceland" "India"
## [103] "Indonesia" "Iran"
## [105] "Iraq" "Ireland"
## [107] "Isle of Man" "Israel"
## [109] "Italy" "Jamaica"
## [111] "Japan" "Jersey"
## [113] "Jordan" "Kazakhstan"
## [115] "Kenya" "Kiribati"
## [117] "Kosovo" "Kuwait"
## [119] "Kyrgyzstan" "Laos"
## [121] "Latvia" "Lebanon"
## [123] "Lesotho" "Liberia"
## [125] "Libya" "Liechtenstein"
## [127] "Lithuania" "Low income"
## [129] "Lower middle income" "Luxembourg"
## [131] "Macao" "Madagascar"
## [133] "Malawi" "Malaysia"
## [135] "Maldives" "Mali"
## [137] "Malta" "Marshall Islands"
## [139] "Martinique" "Mauritania"
## [141] "Mauritius" "Mayotte"
## [143] "Mexico" "Micronesia (country)"
## [145] "Moldova" "Monaco"
## [147] "Mongolia" "Montenegro"
## [149] "Montserrat" "Morocco"
## [151] "Mozambique" "Myanmar"
## [153] "Namibia" "Nauru"
## [155] "Nepal" "Netherlands"
## [157] "New Caledonia" "New Zealand"
## [159] "Nicaragua" "Niger"
## [161] "Nigeria" "Niue"
## [163] "North America" "North Korea"
## [165] "North Macedonia" "Northern Cyprus"
## [167] "Northern Ireland" "Northern Mariana Islands"
## [169] "Norway" "Oceania"
## [171] "Oman" "Pakistan"
## [173] "Palau" "Palestine"
## [175] "Panama" "Papua New Guinea"
## [177] "Paraguay" "Peru"
## [179] "Philippines" "Pitcairn"
## [181] "Poland" "Portugal"
## [183] "Puerto Rico" "Qatar"
## [185] "Reunion" "Romania"
## [187] "Russia" "Rwanda"
## [189] "Saint Barthelemy" "Saint Helena"
## [191] "Saint Kitts and Nevis" "Saint Lucia"
## [193] "Saint Martin (French part)" "Saint Pierre and Miquelon"
## [195] "Saint Vincent and the Grenadines" "Samoa"
## [197] "San Marino" "Sao Tome and Principe"
## [199] "Saudi Arabia" "Scotland"
## [201] "Senegal" "Serbia"
## [203] "Seychelles" "Sierra Leone"
## [205] "Singapore" "Sint Maarten (Dutch part)"
## [207] "Slovakia" "Slovenia"
## [209] "Solomon Islands" "Somalia"
## [211] "South Africa" "South America"
## [213] "South Korea" "South Sudan"
## [215] "Spain" "Sri Lanka"
## [217] "Sudan" "Suriname"
## [219] "Sweden" "Switzerland"
## [221] "Syria" "Taiwan"
## [223] "Tajikistan" "Tanzania"
## [225] "Thailand" "Timor"
## [227] "Togo" "Tokelau"
## [229] "Tonga" "Trinidad and Tobago"
## [231] "Tunisia" "Turkey"
## [233] "Turkmenistan" "Turks and Caicos Islands"
## [235] "Tuvalu" "Uganda"
## [237] "Ukraine" "United Arab Emirates"
## [239] "United Kingdom" "United States"
## [241] "United States Virgin Islands" "Upper middle income"
## [243] "Uruguay" "Uzbekistan"
## [245] "Vanuatu" "Vatican"
## [247] "Venezuela" "Vietnam"
## [249] "Wales" "Wallis and Futuna"
## [251] "Western Sahara" "World"
## [253] "Yemen" "Zambia"
## [255] "Zimbabwe"5 puntos
5 puntos
3 puntos
Selecciona cinco países pequeños del Caribe y reproduzca la gráfica anterior. Para que la gráfica se puede apreciar tendrán que usar los países con poblaciones más pequeño.