data <- read_excel("../01_module4/data/myData.xlsx")data$country## [1] "Iceland" "Norway"
## [3] "Switzerland" "Denmark"
## [5] "Germany" "Sweden"
## [7] "Australia" "Hong Kong, China (SAR)"
## [9] "Netherlands" "Belgium"
## [11] "Ireland" "Finland"
## [13] "Singapore" "United Kingdom"
## [15] "United Arab Emirates" "Canada"
## [17] "Liechtenstein" "New Zealand"
## [19] "United States" "Korea (Republic of)"
## [21] "Slovenia" "Austria"
## [23] "Japan" "Malta"
## [25] "Luxembourg" "France"
## [27] "Israel" "Spain"
## [29] "Czechia" "Italy"
## [31] "San Marino" "Andorra"
## [33] "Cyprus" "Greece"
## [35] "Poland" "Estonia"
## [37] "Saudi Arabia" "Bahrain"
## [39] "Lithuania" "Portugal"
## [41] "Croatia" "Latvia"
## [43] "Qatar" "Slovakia"
## [45] "Chile" "Hungary"
## [47] "Argentina" "Montenegro"
## [49] "Uruguay" "Oman"
## [51] "Türkiye" "Kuwait"
## [53] "Antigua and Barbuda" "Seychelles"
## [55] "Bulgaria" "Romania"
## [57] "Georgia" "Saint Kitts and Nevis"
## [59] "Panama" "Brunei Darussalam"
## [61] "Kazakhstan" "Costa Rica"
## [63] "Serbia" "Russian Federation"
## [65] "Belarus" "Bahamas"
## [67] "Malaysia" "North Macedonia"
## [69] "Armenia" "Barbados"
## [71] "Albania" "Trinidad and Tobago"
## [73] "Mauritius" "Bosnia and Herzegovina"
## [75] "Iran (Islamic Republic of)" "Saint Vincent and the Grenadines"
## [77] "Thailand" "China"
## [79] "Peru" "Grenada"
## [81] "Azerbaijan" "Mexico"
## [83] "Colombia" "Brazil"
## [85] "Palau" "Moldova (Republic of)"
## [87] "Ukraine" "Ecuador"
## [89] "Dominican Republic" "Guyana"
## [91] "Sri Lanka" "Tonga"
## [93] "Maldives" "Viet Nam"
## [95] "Turkmenistan" "Algeria"
## [97] "Cuba" "Dominica"
## [99] "Paraguay" "Egypt"
## [101] "Jordan" "Lebanon"
## [103] "Saint Lucia" "Mongolia"
## [105] "Tunisia" "South Africa"
## [107] "Uzbekistan" "Bolivia (Plurinational State of)"
## [109] "Gabon" "Marshall Islands"
## [111] "Botswana" "Fiji"
## [113] "Indonesia" "Suriname"
## [115] "Belize" "Libya"
## [117] "Jamaica" "Kyrgyzstan"
## [119] "Philippines" "Morocco"
## [121] "Venezuela (Bolivarian Republic of)" "Samoa"
## [123] "Nicaragua" "Nauru"
## [125] "Bhutan" "Eswatini (Kingdom of)"
## [127] "Iraq" "Tajikistan"
## [129] "Tuvalu" "Bangladesh"
## [131] "India" "El Salvador"
## [133] "Equatorial Guinea" "Palestine, State of"
## [135] "Cabo Verde" "Namibia"
## [137] "Guatemala" "Congo"
## [139] "Honduras" "Kiribati"
## [141] "Sao Tome and Principe" "Timor-Leste"
## [143] "Ghana" "Kenya"
## [145] "Nepal" "Vanuatu"
## [147] "Lao People's Democratic Republic" "Angola"
## [149] "Micronesia (Federated States of)" "Myanmar"
## [151] "Cambodia" "Comoros"
## [153] "Zimbabwe" "Zambia"
## [155] "Cameroon" "Solomon Islands"
## [157] "Côte d'Ivoire" "Uganda"
## [159] "Rwanda" "Papua New Guinea"
## [161] "Togo" "Syrian Arab Republic"
## [163] "Mauritania" "Nigeria"
## [165] "Tanzania (United Republic of)" "Haiti"
## [167] "Lesotho" "Pakistan"
## [169] "Senegal" "Gambia"
## [171] "Congo (Democratic Republic of the)" "Malawi"
## [173] "Benin" "Guinea-Bissau"
## [175] "Djibouti" "Sudan"
## [177] "Liberia" "Eritrea"
## [179] "Guinea" "Ethiopia"
## [181] "Afghanistan" "Mozambique"
## [183] "Madagascar" "Yemen"
## [185] "Sierra Leone" "Burkina Faso"
## [187] "Burundi" "Mali"
## [189] "Niger" "Chad"
## [191] "Central African Republic" "Somalia"
## [193] "South Sudan"str_detect(data$country, "China")## [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE
## [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [49] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [73] FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE
## [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [97] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [109] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [121] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [133] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [145] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [157] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [169] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [181] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [193] FALSEsum(str_detect(data$country, "China"))## [1] 2data %>%
summarise(num_China = sum(str_detect(country, "China")))## # A tibble: 1 × 1
## num_China
## <int>
## 1 2data %>%
mutate(col_China = str_extract(country, "China")) %>%
select(country, col_China) %>%
filter(!is.na(col_China))## # A tibble: 2 × 2
## country col_China
## <chr> <chr>
## 1 Hong Kong, China (SAR) China
## 2 China Chinadata %>%
mutate(col_Cathay = str_replace(country, "China", "Cathay")) %>%
select(country, col_Cathay)## # A tibble: 193 × 2
## country col_Cathay
## <chr> <chr>
## 1 Iceland Iceland
## 2 Norway Norway
## 3 Switzerland Switzerland
## 4 Denmark Denmark
## 5 Germany Germany
## 6 Sweden Sweden
## 7 Australia Australia
## 8 Hong Kong, China (SAR) Hong Kong, Cathay (SAR)
## 9 Netherlands Netherlands
## 10 Belgium Belgium
## # ℹ 183 more rows