library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(janitor)##
## Attaching package: 'janitor'
##
## The following objects are masked from 'package:stats':
##
## chisq.test, fisher.testcovid_df <- read.csv("~/project/R PROGRAM/covid 19/covid19.csv") %>% clean_names()
head(covid_df)## date continent_name two_letter_country_code country_region
## 1 2020-01-20 Asia KR South Korea
## 2 2020-01-22 North America US United States
## 3 2020-01-22 North America US United States
## 4 2020-01-23 North America US United States
## 5 2020-01-23 North America US United States
## 6 2020-01-24 Asia KR South Korea
## province_state positive hospitalized recovered death total_tested active
## 1 All States 1 0 0 0 4 0
## 2 All States 1 0 0 0 1 0
## 3 Washington 1 0 0 0 1 0
## 4 All States 1 0 0 0 1 0
## 5 Washington 1 0 0 0 1 0
## 6 All States 2 0 0 0 27 0
## hospitalized_curr daily_tested daily_positive
## 1 0 0 0
## 2 0 0 0
## 3 0 0 0
## 4 0 0 0
## 5 0 0 0
## 6 0 5 0dim(covid_df)## [1] 10903 14vector_col <- colnames(covid_df)
vector_col## [1] "date" "continent_name"
## [3] "two_letter_country_code" "country_region"
## [5] "province_state" "positive"
## [7] "hospitalized" "recovered"
## [9] "death" "total_tested"
## [11] "active" "hospitalized_curr"
## [13] "daily_tested" "daily_positive"glimpse(covid_df)## Rows: 10,903
## Columns: 14
## $ date <chr> "2020-01-20", "2020-01-22", "2020-01-22", "202…
## $ continent_name <chr> "Asia", "North America", "North America", "Nor…
## $ two_letter_country_code <chr> "KR", "US", "US", "US", "US", "KR", "US", "US"…
## $ country_region <chr> "South Korea", "United States", "United States…
## $ province_state <chr> "All States", "All States", "Washington", "All…
## $ positive <int> 1, 1, 1, 1, 1, 2, 1, 1, 4, 0, 3, 0, 0, 0, 0, 1…
## $ hospitalized <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ recovered <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ death <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ total_tested <int> 4, 1, 1, 1, 1, 27, 1, 1, 0, 0, 0, 0, 0, 0, 0, …
## $ active <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ hospitalized_curr <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ daily_tested <int> 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ daily_positive <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…covid_df_all_states <- covid_df %>%
filter(province_state == "All States") %>%
select(-province_state)
covid_df_all_states## date continent_name two_letter_country_code country_region
## 1 2020-01-20 Asia KR South Korea
## 2 2020-01-22 North America US United States
## 3 2020-01-23 North America US United States
## 4 2020-01-24 Asia KR South Korea
## 5 2020-01-24 North America US United States
## 6 2020-01-25 Oceania AU Australia
## 7 2020-01-25 Europe GB United Kingdom
## 8 2020-01-25 North America US United States
## 9 2020-01-26 Oceania AU Australia
## 10 2020-01-26 Asia IL Israel
## 11 2020-01-26 Asia KR South Korea
## 12 2020-01-26 Europe GB United Kingdom
## 13 2020-01-26 North America US United States
## 14 2020-01-27 Oceania AU Australia
## 15 2020-01-27 Europe CZ Czech Republic
## 16 2020-01-27 Asia IL Israel
## 17 2020-01-27 Asia KR South Korea
## 18 2020-01-27 Europe GB United Kingdom
## 19 2020-01-27 North America US United States
## 20 2020-01-28 Oceania AU Australia
## 21 2020-01-28 Europe CZ Czech Republic
## 22 2020-01-28 Asia IL Israel
## 23 2020-01-28 Europe GB United Kingdom
## 24 2020-01-28 North America US United States
## 25 2020-01-29 Oceania AU Australia
## 26 2020-01-29 Europe CZ Czech Republic
## 27 2020-01-29 Asia IL Israel
## 28 2020-01-29 Europe GB United Kingdom
## 29 2020-01-29 North America US United States
## 30 2020-01-30 Oceania AU Australia
## 31 2020-01-30 Europe CZ Czech Republic
## 32 2020-01-30 Asia IL Israel
## 33 2020-01-30 Asia KR South Korea
## 34 2020-01-30 Europe GB United Kingdom
## 35 2020-01-30 North America US United States
## 36 2020-01-31 Oceania AU Australia
## 37 2020-01-31 North America CA Canada
## 38 2020-01-31 Europe CZ Czech Republic
## 39 2020-01-31 Asia IL Israel
## 40 2020-01-31 Asia RU Russia
## 41 2020-01-31 Asia KR South Korea
## 42 2020-01-31 Europe GB United Kingdom
## 43 2020-01-31 North America US United States
## 44 2020-02-01 Oceania AU Australia
## 45 2020-02-01 Europe CZ Czech Republic
## 46 2020-02-01 Asia IL Israel
## 47 2020-02-01 Asia KR South Korea
## 48 2020-02-01 Europe GB United Kingdom
## 49 2020-02-01 North America US United States
## 50 2020-02-02 Oceania AU Australia
## 51 2020-02-02 Europe CZ Czech Republic
## 52 2020-02-02 Asia IL Israel
## 53 2020-02-02 Asia KR South Korea
## 54 2020-02-02 Europe GB United Kingdom
## 55 2020-02-02 North America US United States
## 56 2020-02-03 Asia AM Armenia
## 57 2020-02-03 Oceania AU Australia
## 58 2020-02-03 Europe CZ Czech Republic
## 59 2020-02-03 Asia IL Israel
## 60 2020-02-03 Europe GB United Kingdom
## 61 2020-02-03 North America US United States
## 62 2020-02-04 Asia AM Armenia
## 63 2020-02-04 Oceania AU Australia
## 64 2020-02-04 Europe CZ Czech Republic
## 65 2020-02-04 Asia IL Israel
## 66 2020-02-04 Asia KR South Korea
## 67 2020-02-04 Europe GB United Kingdom
## 68 2020-02-04 North America US United States
## 69 2020-02-05 Asia AM Armenia
## 70 2020-02-05 Oceania AU Australia
## 71 2020-02-05 Europe CZ Czech Republic
## 72 2020-02-05 Asia IL Israel
## 73 2020-02-05 Asia KR South Korea
## 74 2020-02-05 Europe GB United Kingdom
## 75 2020-02-05 North America US United States
## 76 2020-02-06 Asia AM Armenia
## 77 2020-02-06 Oceania AU Australia
## 78 2020-02-06 Europe CZ Czech Republic
## 79 2020-02-06 Asia IL Israel
## 80 2020-02-06 Asia KR South Korea
## 81 2020-02-06 Europe GB United Kingdom
## 82 2020-02-06 North America US United States
## 83 2020-02-07 Asia AM Armenia
## 84 2020-02-07 Oceania AU Australia
## 85 2020-02-07 Europe CZ Czech Republic
## 86 2020-02-07 Asia IL Israel
## 87 2020-02-07 Asia KR South Korea
## 88 2020-02-07 Europe GB United Kingdom
## 89 2020-02-07 North America US United States
## 90 2020-02-08 Oceania AU Australia
## 91 2020-02-08 North America CA Canada
## 92 2020-02-08 Europe CZ Czech Republic
## 93 2020-02-08 Asia IL Israel
## 94 2020-02-08 Europe GB United Kingdom
## 95 2020-02-08 North America US United States
## 96 2020-02-09 Oceania AU Australia
## 97 2020-02-09 Europe CZ Czech Republic
## 98 2020-02-09 Asia IL Israel
## 99 2020-02-09 Asia KR South Korea
## 100 2020-02-09 Europe GB United Kingdom
## 101 2020-02-09 North America US United States
## 102 2020-02-10 Asia AM Armenia
## 103 2020-02-10 Oceania AU Australia
## 104 2020-02-10 Europe CZ Czech Republic
## 105 2020-02-10 Asia IL Israel
## 106 2020-02-10 Europe GB United Kingdom
## 107 2020-02-10 North America US United States
## 108 2020-02-11 Asia AM Armenia
## 109 2020-02-11 Oceania AU Australia
## 110 2020-02-11 Europe CZ Czech Republic
## 111 2020-02-11 Asia IL Israel
## 112 2020-02-11 Asia RU Russia
## 113 2020-02-11 Asia KR South Korea
## 114 2020-02-11 Europe GB United Kingdom
## 115 2020-02-11 North America US United States
## 116 2020-02-12 Oceania AU Australia
## 117 2020-02-12 Europe CZ Czech Republic
## 118 2020-02-12 Asia IL Israel
## 119 2020-02-12 Asia RU Russia
## 120 2020-02-12 Europe GB United Kingdom
## 121 2020-02-12 North America US United States
## 122 2020-02-13 Oceania AU Australia
## 123 2020-02-13 Europe CZ Czech Republic
## 124 2020-02-13 Asia IL Israel
## 125 2020-02-13 Europe GB United Kingdom
## 126 2020-02-13 North America US United States
## 127 2020-02-14 Asia AM Armenia
## 128 2020-02-14 Oceania AU Australia
## 129 2020-02-14 Europe CZ Czech Republic
## 130 2020-02-14 Asia IL Israel
## 131 2020-02-14 Europe GB United Kingdom
## 132 2020-02-14 North America US United States
## 133 2020-02-15 Oceania AU Australia
## 134 2020-02-15 Europe CZ Czech Republic
## 135 2020-02-15 Asia IL Israel
## 136 2020-02-15 Europe GB United Kingdom
## 137 2020-02-15 North America US United States
## 138 2020-02-16 Oceania AU Australia
## 139 2020-02-16 North America CA Canada
## 140 2020-02-16 Europe CZ Czech Republic
## 141 2020-02-16 Asia IL Israel
## 142 2020-02-16 Asia KR South Korea
## 143 2020-02-16 Europe GB United Kingdom
## 144 2020-02-16 North America US United States
## 145 2020-02-17 Oceania AU Australia
## 146 2020-02-17 Europe CZ Czech Republic
## 147 2020-02-17 Asia IL Israel
## 148 2020-02-17 Asia KR South Korea
## 149 2020-02-17 Europe GB United Kingdom
## 150 2020-02-17 North America US United States
## 151 2020-02-18 Asia AM Armenia
## 152 2020-02-18 Oceania AU Australia
## 153 2020-02-18 Europe CZ Czech Republic
## 154 2020-02-18 Asia IL Israel
## 155 2020-02-18 Asia KR South Korea
## 156 2020-02-18 Europe GB United Kingdom
## 157 2020-02-18 North America US United States
## 158 2020-02-19 Asia AM Armenia
## 159 2020-02-19 Oceania AU Australia
## 160 2020-02-19 Europe CZ Czech Republic
## 161 2020-02-19 Asia IL Israel
## 162 2020-02-19 Europe PL Poland
## 163 2020-02-19 Asia KR South Korea
## 164 2020-02-19 Europe GB United Kingdom
## 165 2020-02-19 North America US United States
## 166 2020-02-20 Oceania AU Australia
## 167 2020-02-20 Europe CZ Czech Republic
## 168 2020-02-20 Asia IL Israel
## 169 2020-02-20 Asia KR South Korea
## 170 2020-02-20 Europe GB United Kingdom
## 171 2020-02-20 North America US United States
## 172 2020-02-21 Oceania AU Australia
## 173 2020-02-21 North America CA Canada
## 174 2020-02-21 Europe CZ Czech Republic
## 175 2020-02-21 Asia IL Israel
## 176 2020-02-21 Asia KR South Korea
## 177 2020-02-21 Europe GB United Kingdom
## 178 2020-02-21 North America US United States
## 179 2020-02-22 Oceania AU Australia
## 180 2020-02-22 Europe CZ Czech Republic
## 181 2020-02-22 Asia IL Israel
## 182 2020-02-22 Asia KR South Korea
## 183 2020-02-22 Europe GB United Kingdom
## 184 2020-02-22 North America US United States
## 185 2020-02-23 Oceania AU Australia
## 186 2020-02-23 Europe CZ Czech Republic
## 187 2020-02-23 Asia IL Israel
## 188 2020-02-23 Asia KR South Korea
## 189 2020-02-23 Europe GB United Kingdom
## 190 2020-02-23 North America US United States
## 191 2020-02-24 Asia AM Armenia
## 192 2020-02-24 Oceania AU Australia
## 193 2020-02-24 North America CA Canada
## 194 2020-02-24 Europe CZ Czech Republic
## 195 2020-02-24 Asia IL Israel
## 196 2020-02-24 Europe IT Italy
## 197 2020-02-24 Asia KR South Korea
## 198 2020-02-24 Europe GB United Kingdom
## 199 2020-02-24 North America US United States
## 200 2020-02-25 Asia AM Armenia
## 201 2020-02-25 Oceania AU Australia
## 202 2020-02-25 North America CA Canada
## 203 2020-02-25 Europe CZ Czech Republic
## 204 2020-02-25 Europe EE Estonia
## 205 2020-02-25 Asia IL Israel
## 206 2020-02-25 Europe IT Italy
## 207 2020-02-25 Asia KR South Korea
## 208 2020-02-25 Europe GB United Kingdom
## 209 2020-02-25 North America US United States
## 210 2020-02-26 Asia AM Armenia
## 211 2020-02-26 Oceania AU Australia
## 212 2020-02-26 North America CA Canada
## 213 2020-02-26 Europe CZ Czech Republic
## 214 2020-02-26 Europe EE Estonia
## 215 2020-02-26 Europe GR Greece
## 216 2020-02-26 Asia IL Israel
## 217 2020-02-26 Europe IT Italy
## 218 2020-02-26 Oceania NZ New Zealand
## 219 2020-02-26 Asia KR South Korea
## 220 2020-02-26 Europe GB United Kingdom
## 221 2020-02-26 North America US United States
## 222 2020-02-27 Asia AM Armenia
## 223 2020-02-27 Oceania AU Australia
## 224 2020-02-27 North America CA Canada
## 225 2020-02-27 Europe CZ Czech Republic
## 226 2020-02-27 Europe EE Estonia
## 227 2020-02-27 Europe GR Greece
## 228 2020-02-27 Europe IS Iceland
## 229 2020-02-27 Asia IL Israel
## 230 2020-02-27 Europe IT Italy
## 231 2020-02-27 Europe PL Poland
## 232 2020-02-27 Asia KR South Korea
## 233 2020-02-27 Europe GB United Kingdom
## 234 2020-02-27 North America US United States
## 235 2020-02-28 Asia AM Armenia
## 236 2020-02-28 Oceania AU Australia
## 237 2020-02-28 Europe CZ Czech Republic
## 238 2020-02-28 Europe EE Estonia
## 239 2020-02-28 Europe GR Greece
## 240 2020-02-28 Europe IS Iceland
## 241 2020-02-28 Asia IL Israel
## 242 2020-02-28 Europe IT Italy
## 243 2020-02-28 Europe LT Lithuania
## 244 2020-02-28 Europe PL Poland
## 245 2020-02-28 Asia KR South Korea
## 246 2020-02-28 Europe GB United Kingdom
## 247 2020-02-28 North America US United States
## 248 2020-02-29 Asia AM Armenia
## 249 2020-02-29 Oceania AU Australia
## 250 2020-02-29 North America CA Canada
## 251 2020-02-29 Europe CZ Czech Republic
## 252 2020-02-29 Europe EE Estonia
## 253 2020-02-29 Europe GR Greece
## 254 2020-02-29 Europe IS Iceland
## 255 2020-02-29 Asia IL Israel
## 256 2020-02-29 Europe IT Italy
## 257 2020-02-29 Europe LT Lithuania
## 258 2020-02-29 Europe PL Poland
## 259 2020-02-29 Asia KR South Korea
## 260 2020-02-29 Europe GB United Kingdom
## 261 2020-02-29 North America US United States
## 262 2020-03-01 Asia AM Armenia
## 263 2020-03-01 Oceania AU Australia
## 264 2020-03-01 Europe BE Belgium
## 265 2020-03-01 North America CA Canada
## 266 2020-03-01 Europe CZ Czech Republic
## 267 2020-03-01 Europe EE Estonia
## 268 2020-03-01 Europe GR Greece
## 269 2020-03-01 Europe IS Iceland
## 270 2020-03-01 Asia IL Israel
## 271 2020-03-01 Europe IT Italy
## 272 2020-03-01 Europe LT Lithuania
## 273 2020-03-01 Europe PL Poland
## 274 2020-03-01 Asia KR South Korea
## 275 2020-03-01 Europe SE Sweden
## 276 2020-03-01 Europe GB United Kingdom
## 277 2020-03-01 North America US United States
## 278 2020-03-02 Asia AM Armenia
## 279 2020-03-02 Oceania AU Australia
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## 281 2020-03-02 Europe CZ Czech Republic
## 282 2020-03-02 Europe EE Estonia
## 283 2020-03-02 Europe GR Greece
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## 291 2020-03-02 Asia RU Russia
## 292 2020-03-02 Asia KR South Korea
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## 294 2020-03-02 North America US United States
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## 296 2020-03-03 Oceania AU Australia
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## 298 2020-03-03 North America CA Canada
## 299 2020-03-03 Europe CZ Czech Republic
## 300 2020-03-03 Europe EE Estonia
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## 310 2020-03-03 North America US United States
## 311 2020-03-04 Asia AM Armenia
## 312 2020-03-04 Oceania AU Australia
## 313 2020-03-04 Europe BE Belgium
## 314 2020-03-04 Europe CZ Czech Republic
## 315 2020-03-04 Europe EE Estonia
## 316 2020-03-04 Europe GR Greece
## 317 2020-03-04 Europe IS Iceland
## 318 2020-03-04 Asia IL Israel
## 319 2020-03-04 Europe IT Italy
## 320 2020-03-04 Europe LV Latvia
## 321 2020-03-04 Europe LT Lithuania
## 322 2020-03-04 Oceania NZ New Zealand
## 323 2020-03-04 Europe PL Poland
## 324 2020-03-04 Asia KR South Korea
## 325 2020-03-04 Europe GB United Kingdom
## 326 2020-03-04 North America US United States
## 327 2020-03-05 Asia AM Armenia
## 328 2020-03-05 Oceania AU Australia
## 329 2020-03-05 Europe BE Belgium
## 330 2020-03-05 North America CA Canada
## 331 2020-03-05 Europe CZ Czech Republic
## 332 2020-03-05 Europe EE Estonia
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## 334 2020-03-05 Europe IS Iceland
## 335 2020-03-05 Asia IL Israel
## 336 2020-03-05 Europe IT Italy
## 337 2020-03-05 Europe LV Latvia
## 338 2020-03-05 Europe LT Lithuania
## 339 2020-03-05 Oceania NZ New Zealand
## 340 2020-03-05 Europe PL Poland
## 341 2020-03-05 Asia RU Russia
## 342 2020-03-05 Asia KR South Korea
## 343 2020-03-05 Europe GB United Kingdom
## 344 2020-03-05 North America US United States
## 345 2020-03-06 Asia AM Armenia
## 346 2020-03-06 Oceania AU Australia
## 347 2020-03-06 Europe BE Belgium
## 348 2020-03-06 North America CA Canada
## 349 2020-03-06 North America CR Costa Rica
## 350 2020-03-06 Europe CZ Czech Republic
## 351 2020-03-06 Europe EE Estonia
## 352 2020-03-06 Europe GR Greece
## 353 2020-03-06 Europe IS Iceland
## 354 2020-03-06 Asia IL Israel
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## 356 2020-03-06 Europe LV Latvia
## 357 2020-03-06 Europe LT Lithuania
## 358 2020-03-06 Oceania NZ New Zealand
## 359 2020-03-06 Europe PL Poland
## 360 2020-03-06 Asia RU Russia
## 361 2020-03-06 Europe RS Serbia
## 362 2020-03-06 Europe SK Slovakia
## 363 2020-03-06 Asia KR South Korea
## 364 2020-03-06 Europe GB United Kingdom
## 365 2020-03-06 North America US United States
## 366 2020-03-07 Asia AM Armenia
## 367 2020-03-07 Oceania AU Australia
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## 400 2020-03-08 Europe PL Poland
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## 402 2020-03-08 Europe RS Serbia
## 403 2020-03-08 Europe SK Slovakia
## 404 2020-03-08 Asia KR South Korea
## 405 2020-03-08 Europe SE Sweden
## 406 2020-03-08 Europe GB United Kingdom
## 407 2020-03-08 North America US United States
## 408 2020-03-09 Asia AM Armenia
## 409 2020-03-09 Oceania AU Australia
## 410 2020-03-09 Europe BE Belgium
## 411 2020-03-09 North America CA Canada
## 412 2020-03-09 North America CR Costa Rica
## 413 2020-03-09 Europe CZ Czech Republic
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## 3739 5896 603 210
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## 3780 0 237 0
## 3781 0 0 0covid_df_all_states_daily <- covid_df_all_states %>%
select(date, country_region, active, hospitalized_curr, daily_tested, daily_positive)
covid_df_all_states_daily## date country_region active hospitalized_curr daily_tested
## 1 2020-01-20 South Korea 0 0 0
## 2 2020-01-22 United States 0 0 0
## 3 2020-01-23 United States 0 0 0
## 4 2020-01-24 South Korea 0 0 5
## 5 2020-01-24 United States 0 0 0
## 6 2020-01-25 Australia 0 0 0
## 7 2020-01-25 United Kingdom 0 0 0
## 8 2020-01-25 United States 0 0 0
## 9 2020-01-26 Australia 0 0 0
## 10 2020-01-26 Israel 0 0 0
## 11 2020-01-26 South Korea 0 0 12
## 12 2020-01-26 United Kingdom 0 0 21
## 13 2020-01-26 United States 0 0 0
## 14 2020-01-27 Australia 0 0 0
## 15 2020-01-27 Czech Republic 0 0 0
## 16 2020-01-27 Israel 0 0 1
## 17 2020-01-27 South Korea 0 0 10
## 18 2020-01-27 United Kingdom 0 0 21
## 19 2020-01-27 United States 0 0 0
## 20 2020-01-28 Australia 0 0 0
## 21 2020-01-28 Czech Republic 0 0 8
## 22 2020-01-28 Israel 0 0 0
## 23 2020-01-28 United Kingdom 0 0 24
## 24 2020-01-28 United States 0 0 0
## 25 2020-01-29 Australia 0 0 0
## 26 2020-01-29 Czech Republic 0 0 5
## 27 2020-01-29 Israel 0 0 3
## 28 2020-01-29 United Kingdom 0 0 33
## 29 2020-01-29 United States 0 0 0
## 30 2020-01-30 Australia 0 0 0
## 31 2020-01-30 Czech Republic 0 0 1
## 32 2020-01-30 Israel 0 0 4
## 33 2020-01-30 South Korea 0 0 0
## 34 2020-01-30 United Kingdom 0 0 31
## 35 2020-01-30 United States 0 0 0
## 36 2020-01-31 Australia 0 0 0
## 37 2020-01-31 Canada 0 0 0
## 38 2020-01-31 Czech Republic 0 0 3
## 39 2020-01-31 Israel 0 0 0
## 40 2020-01-31 Russia 0 0 0
## 41 2020-01-31 South Korea 0 0 0
## 42 2020-01-31 United Kingdom 0 0 16
## 43 2020-01-31 United States 0 0 0
## 44 2020-02-01 Australia 0 0 0
## 45 2020-02-01 Czech Republic 0 0 1
## 46 2020-02-01 Israel 0 0 0
## 47 2020-02-01 South Korea 0 0 0
## 48 2020-02-01 United Kingdom 0 0 26
## 49 2020-02-01 United States 0 0 0
## 50 2020-02-02 Australia 0 0 0
## 51 2020-02-02 Czech Republic 0 0 5
## 52 2020-02-02 Israel 0 0 7
## 53 2020-02-02 South Korea 0 0 58
## 54 2020-02-02 United Kingdom 0 0 63
## 55 2020-02-02 United States 0 0 0
## 56 2020-02-03 Armenia 0 0 0
## 57 2020-02-03 Australia 0 0 0
## 58 2020-02-03 Czech Republic 0 0 5
## 59 2020-02-03 Israel 0 0 7
## 60 2020-02-03 United Kingdom 0 0 60
## 61 2020-02-03 United States 0 0 0
## 62 2020-02-04 Armenia 0 0 12
## 63 2020-02-04 Australia 0 0 0
## 64 2020-02-04 Czech Republic 0 0 5
## 65 2020-02-04 Israel 0 0 6
## 66 2020-02-04 South Korea 0 0 89
## 67 2020-02-04 United Kingdom 0 0 90
## 68 2020-02-04 United States 0 0 0
## 69 2020-02-05 Armenia 0 0 5
## 70 2020-02-05 Australia 0 0 0
## 71 2020-02-05 Czech Republic 0 0 0
## 72 2020-02-05 Israel 0 0 0
## 73 2020-02-05 South Korea 0 0 107
## 74 2020-02-05 United Kingdom 0 0 52
## 75 2020-02-05 United States 0 0 0
## 76 2020-02-06 Armenia 0 0 16
## 77 2020-02-06 Australia 0 0 0
## 78 2020-02-06 Czech Republic 0 0 3
## 79 2020-02-06 Israel 0 0 0
## 80 2020-02-06 South Korea 0 0 171
## 81 2020-02-06 United Kingdom 0 0 98
## 82 2020-02-06 United States 0 0 0
## 83 2020-02-07 Armenia 0 0 9
## 84 2020-02-07 Australia 0 0 0
## 85 2020-02-07 Czech Republic 0 0 6
## 86 2020-02-07 Israel 0 0 0
## 87 2020-02-07 South Korea 0 0 245
## 88 2020-02-07 United Kingdom 0 0 54
## 89 2020-02-07 United States 0 0 1
## 90 2020-02-08 Australia 0 0 0
## 91 2020-02-08 Canada 0 0 0
## 92 2020-02-08 Czech Republic 0 0 0
## 93 2020-02-08 Israel 0 0 0
## 94 2020-02-08 United Kingdom 0 0 66
## 95 2020-02-08 United States 0 0 0
## 96 2020-02-09 Australia 0 0 0
## 97 2020-02-09 Czech Republic 0 0 2
## 98 2020-02-09 Israel 0 0 40
## 99 2020-02-09 South Korea 0 0 734
## 100 2020-02-09 United Kingdom 0 0 109
## 101 2020-02-09 United States 0 0 0
## 102 2020-02-10 Armenia 0 0 1
## 103 2020-02-10 Australia 0 0 0
## 104 2020-02-10 Czech Republic 0 0 8
## 105 2020-02-10 Israel 0 0 28
## 106 2020-02-10 United Kingdom 0 0 319
## 107 2020-02-10 United States 0 0 0
## 108 2020-02-11 Armenia 0 0 11
## 109 2020-02-11 Australia 0 0 0
## 110 2020-02-11 Czech Republic 0 0 2
## 111 2020-02-11 Israel 0 0 50
## 112 2020-02-11 Russia 0 0 0
## 113 2020-02-11 South Korea 0 0 515
## 114 2020-02-11 United Kingdom 0 0 244
## 115 2020-02-11 United States 0 0 0
## 116 2020-02-12 Australia 0 0 0
## 117 2020-02-12 Czech Republic 0 0 1
## 118 2020-02-12 Israel 0 0 35
## 119 2020-02-12 Russia 0 0 0
## 120 2020-02-12 United Kingdom 0 0 400
## 121 2020-02-12 United States 0 0 0
## 122 2020-02-13 Australia 0 0 0
## 123 2020-02-13 Czech Republic 0 0 1
## 124 2020-02-13 Israel 0 0 35
## 125 2020-02-13 United Kingdom 0 0 763
## 126 2020-02-13 United States 0 0 0
## 127 2020-02-14 Armenia 0 0 1
## 128 2020-02-14 Australia 0 0 0
## 129 2020-02-14 Czech Republic 0 0 0
## 130 2020-02-14 Israel 0 0 30
## 131 2020-02-14 United Kingdom 0 0 443
## 132 2020-02-14 United States 0 0 0
## 133 2020-02-15 Australia 0 0 0
## 134 2020-02-15 Czech Republic 0 0 1
## 135 2020-02-15 Israel 0 0 3
## 136 2020-02-15 United Kingdom 0 0 28
## 137 2020-02-15 United States 0 0 0
## 138 2020-02-16 Australia 0 0 0
## 139 2020-02-16 Canada 0 0 0
## 140 2020-02-16 Czech Republic 0 0 1
## 141 2020-02-16 Israel 0 0 23
## 142 2020-02-16 South Korea 0 0 858
## 143 2020-02-16 United Kingdom 0 0 117
## 144 2020-02-16 United States 0 0 0
## 145 2020-02-17 Australia 0 0 0
## 146 2020-02-17 Czech Republic 0 0 2
## 147 2020-02-17 Israel 0 0 41
## 148 2020-02-17 South Korea 0 0 252
## 149 2020-02-17 United Kingdom 0 0 1392
## 150 2020-02-17 United States 0 0 0
## 151 2020-02-18 Armenia 0 0 0
## 152 2020-02-18 Australia 0 0 0
## 153 2020-02-18 Czech Republic 0 0 0
## 154 2020-02-18 Israel 0 0 46
## 155 2020-02-18 South Korea 0 0 1094
## 156 2020-02-18 United Kingdom 0 0 415
## 157 2020-02-18 United States 0 0 0
## 158 2020-02-19 Armenia 0 0 5
## 159 2020-02-19 Australia 0 0 0
## 160 2020-02-19 Czech Republic 0 0 2
## 161 2020-02-19 Israel 0 0 34
## 162 2020-02-19 Poland 0 0 0
## 163 2020-02-19 South Korea 0 0 1908
## 164 2020-02-19 United Kingdom 0 0 291
## 165 2020-02-19 United States 0 0 0
## 166 2020-02-20 Australia 0 0 0
## 167 2020-02-20 Czech Republic 0 0 0
## 168 2020-02-20 Israel 0 0 29
## 169 2020-02-20 South Korea 87 0 2029
## 170 2020-02-20 United Kingdom 0 0 342
## 171 2020-02-20 United States 0 0 0
## 172 2020-02-21 Australia 0 0 0
## 173 2020-02-21 Canada 0 0 0
## 174 2020-02-21 Czech Republic 0 0 0
## 175 2020-02-21 Israel 0 2 37
## 176 2020-02-21 South Korea 185 0 3198
## 177 2020-02-21 United Kingdom 0 0 336
## 178 2020-02-21 United States 0 0 0
## 179 2020-02-22 Australia 0 0 0
## 180 2020-02-22 Czech Republic 0 0 1
## 181 2020-02-22 Israel 0 2 13
## 182 2020-02-22 South Korea 413 0 5186
## 183 2020-02-22 United Kingdom 0 0 267
## 184 2020-02-22 United States 0 0 0
## 185 2020-02-23 Australia 0 0 0
## 186 2020-02-23 Czech Republic 0 0 3
## 187 2020-02-23 Israel 0 2 56
## 188 2020-02-23 South Korea 580 0 3991
## 189 2020-02-23 United Kingdom 0 0 172
## 190 2020-02-23 United States 0 0 0
## 191 2020-02-24 Armenia 0 0 1
## 192 2020-02-24 Australia 0 0 0
## 193 2020-02-24 Canada 0 0 0
## 194 2020-02-24 Czech Republic 0 0 12
## 195 2020-02-24 Israel 0 2 76
## 196 2020-02-24 Italy 221 127 0
## 197 2020-02-24 South Korea 804 0 6346
## 198 2020-02-24 United Kingdom 0 0 212
## 199 2020-02-24 United States 0 0 0
## 200 2020-02-25 Armenia 0 0 7
## 201 2020-02-25 Australia 0 0 0
## 202 2020-02-25 Canada 0 0 0
## 203 2020-02-25 Czech Republic 0 0 14
## 204 2020-02-25 Estonia 0 1 0
## 205 2020-02-25 Israel 0 2 108
## 206 2020-02-25 Italy 312 150 4299
## 207 2020-02-25 South Korea 945 0 8381
## 208 2020-02-25 United Kingdom 0 0 259
## 209 2020-02-25 United States 0 0 0
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## 3781 0covid_df_all_states_daily_sum <- covid_df_all_states_daily %>%
group_by(country_region) %>%
summarise(tested = sum(daily_tested),
positive = sum(daily_positive),
active = sum(active),
hospitalized = sum(hospitalized_curr)) %>%
arrange(desc(tested)) #this is equivalent to `arrange(-tested)`
covid_df_all_states_daily_sum## # A tibble: 108 × 5
## country_region tested positive active hospitalized
## <chr> <int> <int> <int> <int>
## 1 United States 17282363 1877179 0 0
## 2 Russia 10542266 406368 6924890 0
## 3 Italy 4091291 251710 6202214 1699003
## 4 India 3692851 60959 0 0
## 5 Turkey 2031192 163941 2980960 0
## 6 Canada 1654779 90873 56454 0
## 7 United Kingdom 1473672 166909 0 0
## 8 Australia 1252900 7200 134586 6655
## 9 Peru 976790 59497 0 0
## 10 Poland 928256 23987 538203 0
## # ℹ 98 more rowscovid_top_10 <- head(covid_df_all_states_daily_sum, 10)
covid_top_10## # A tibble: 10 × 5
## country_region tested positive active hospitalized
## <chr> <int> <int> <int> <int>
## 1 United States 17282363 1877179 0 0
## 2 Russia 10542266 406368 6924890 0
## 3 Italy 4091291 251710 6202214 1699003
## 4 India 3692851 60959 0 0
## 5 Turkey 2031192 163941 2980960 0
## 6 Canada 1654779 90873 56454 0
## 7 United Kingdom 1473672 166909 0 0
## 8 Australia 1252900 7200 134586 6655
## 9 Peru 976790 59497 0 0
## 10 Poland 928256 23987 538203 0countries <- covid_top_10$country_region
tested_cases <- covid_top_10$tested
positive_cases <- covid_top_10$positive
active_cases <- covid_top_10$active
hospitalized_cases <- covid_top_10$hospitalizednames(positive_cases) <- countries
names(tested_cases) <- countries
names(active_cases) <- countries
names(hospitalized_cases) <- countriespositive_cases## United States Russia Italy India Turkey
## 1877179 406368 251710 60959 163941
## Canada United Kingdom Australia Peru Poland
## 90873 166909 7200 59497 23987sum(positive_cases)## [1] 3108623mean(positive_cases)## [1] 310862.3positive_cases/sum(positive_cases)## United States Russia Italy India Turkey
## 0.603861903 0.130722831 0.080971543 0.019609647 0.052737498
## Canada United Kingdom Australia Peru Poland
## 0.029232557 0.053692262 0.002316138 0.019139342 0.007716278positive_cases/tested_cases## United States Russia Italy India Turkey
## 0.108618191 0.038546552 0.061523368 0.016507300 0.080711720
## Canada United Kingdom Australia Peru Poland
## 0.054915490 0.113260617 0.005746668 0.060910738 0.025840932positive_tested_top_3 <- c("United Kingdom" = 0.11, "United States" = 0.10, "Turkey" = 0.08)united_kingdom <- c(0.11, 1473672, 166909, 0, 0)
united_states <- c(0.10, 17282363, 1877179, 0, 0)
turkey <- c(0.08, 2031192, 163941, 2980960, 0)covid_mat <- rbind(united_kingdom, united_states, turkey)
colnames(covid_mat) <- c("Ratio", "tested", "positive", "active", "hospitalized")
covid_mat## Ratio tested positive active hospitalized
## united_kingdom 0.11 1473672 166909 0 0
## united_states 0.10 17282363 1877179 0 0
## turkey 0.08 2031192 163941 2980960 0question <- "Which countries have had the highest number of positive cases against the number of tests?"
answer <- c("Positive tested cases" = positive_tested_top_3)
datasets <- list(
original = covid_df,
allstates = covid_df_all_states,
daily = covid_df_all_states_daily,
top_10 = covid_top_10
)
matrices <- list(covid_mat)
vectors <- list(vector_col, countries)
data_structure_list <- list("dataframe" = datasets, "matrix" = matrices, "vector" = vectors)
covid_analysis_list <- list(question, answer, data_structure_list)
covid_analysis_list[[2]]## Positive tested cases.United Kingdom Positive tested cases.United States
## 0.11 0.10
## Positive tested cases.Turkey
## 0.08