library(kableExtra)
library(stringr)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following object is masked from 'package:kableExtra':
## 
##     group_rows
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(tidyr)
library(ggplot2)

Dataset 1

The dataset presents estimates of international migrant by age, sex and origin. Estimates are presented for 1990, 1995, 2000, 2005, 2010, 2015 and 2019 and are available for all countries and areas of the world. The estimates are based on official statistics on the foreign-born or the foreign population.

Data can be found in UN Web site

The excel sheet will look like this

Data Transformation

Fetch Data

In this section I will be coverting the data into .csv file format and process data to get the final more structured output.

UN_migration_data <- read.delim("UN_MigrantStockByOriginAndDestination_2019.csv", header = TRUE, stringsAsFactors = FALSE, sep = ",")

head(UN_migration_data) %>% kable() %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive"))%>%scroll_box(width = "100%", height = "400px")
ï..Year Sort.order Major.area..region..country.or.area.of.destination Notes Code Type.of.data..a. Total Other.South Other.North Afghanistan Albania Algeria American.Samoa Andorra Angola Anguilla Antigua.and.Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia..Plurinational.State.of. Bonaire..Sint.Eustatius.and.Saba Bosnia.and.Herzegovina Botswana Brazil British.Virgin.Islands Brunei.Darussalam Bulgaria Burkina.Faso Burundi Cabo.Verde Cambodia Cameroon Canada Cayman.Islands Central.African.Republic Chad Channel.Islands Chile China China..Hong.Kong.SAR China..Macao.SAR Colombia Comoros Congo Cook.Islands Costa.Rica CÃ.te.d.Ivoire Croatia Cuba CuraÃ.ao Cyprus Czechia Dem..People.s.Republic.of.Korea Democratic.Republic.of.the.Congo Denmark Djibouti Dominica Dominican.Republic Ecuador Egypt El.Salvador Equatorial.Guinea Eritrea Estonia Eswatini Ethiopia Falkland.Islands..Malvinas. Faroe.Islands Fiji Finland France French.Guiana French.Polynesia Gabon Gambia Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guam Guatemala Guinea Guinea.Bissau Guyana Haiti Holy.See Honduras Hungary Iceland India Indonesia Iran..Islamic.Republic.of. Iraq Ireland Isle.of.Man Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kiribati Kuwait Kyrgyzstan Lao.People.s.Democratic.Republic Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Madagascar Malawi Malaysia Maldives Mali Malta Marshall.Islands Martinique Mauritania Mauritius Mayotte Mexico Micronesia..Fed..States.of. Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New.Caledonia New.Zealand Nicaragua Niger Nigeria Niue North.Macedonia Northern.Mariana.Islands Norway Oman Pakistan Palau Panama Papua.New.Guinea Paraguay Peru Philippines Poland Portugal Puerto.Rico Qatar Republic.of.Korea Republic.of.Moldova RÃ.union Romania Russian.Federation Rwanda Saint.Helena Saint.Kitts.and.Nevis Saint.Lucia Saint.Pierre.and.Miquelon Saint.Vincent.and.the.Grenadines Samoa San.Marino Sao.Tome.and.Principe Saudi.Arabia Senegal Serbia Seychelles Sierra.Leone Singapore Sint.Maarten..Dutch.part. Slovakia Slovenia Solomon.Islands Somalia South.Africa South.Sudan Spain Sri.Lanka State.of.Palestine Sudan Suriname Sweden Switzerland Syrian.Arab.Republic Tajikistan Thailand Timor.Leste Togo Tokelau Tonga Trinidad.and.Tobago Tunisia Turkey Turkmenistan Turks.and.Caicos.Islands Tuvalu Uganda Ukraine United.Arab.Emirates United.Kingdom United.Republic.of.Tanzania United.States.of.America United.States.Virgin.Islands Uruguay Uzbekistan Vanuatu Venezuela..Bolivarian.Republic.of. Viet.Nam Wallis.and.Futuna.Islands Western.Sahara Yemen Zambia Zimbabwe X X.1 X.2 X.3 X.4 X.5 X.6 X.7 X.8 X.9 X.10 X.11 X.12 X.13 X.14 X.15 X.16 X.17 X.18 X.19 X.20 X.21 X.22 X.23 X.24 X.25 X.26 X.27 X.28 X.29 X.30 X.31 X.32 X.33 X.34 X.35 X.36 X.37 X.38 X.39 X.40 X.41 X.42 X.43 X.44 X.45 X.46 X.47
1990 1990001 WORLD 900 153,011,473 6,548,526 2,366,800 6,823,350 180,284 921,727 2,041 3,792 824,942 2,047 21,753 430,169 899,649 10,596 303,696 506,088 1,634,081 25,182 12,820 5,451,831 84,931 1,767,606 365,360 36,117 234,314 71,702 28,465 224,693 3,206 861,766 26,053 500,392 3,094 26,323 613,093 1,021,332 337,118 91,368 355,430 115,853 998,163 373 46,362 336,802 18,726 493,026 4,231,648 551,080 95,648 1,009,935 40,083 96,372 17,488 69,711 366,348 425,807 835,796 43,190 174,378 277,260 39,784 436,526 201,761 5,308 42,437 466,216 214,008 1,322,178 1,242,075 36,178 170,603 113,905 35,181 1,689,955 260 7,520 90,166 250,765 1,215,895 2,844 3,149 15,352 36,280 919,454 2,929,448 371,162 11,994 1,022,459 9,510 43,249 5,828 1,376 348,332 352,763 55,409 233,731 528,873 31 156,594 387,514 17,621 6,623,177 1,638,365 631,339 1,506,702 917,286 10,735 281,597 3,351,006 589,010 608,921 313,997 2,971,639 250,340 4,053 81,611 522,578 483,021 215,134 509,323 191,339 516,886 76,256 3,428 341,050 36,141 59,424 143,437 562,762 2,193 647,436 110,746 1,426 11,041 134,488 110,708 1,835 4,395,365 7,714 4,479 24,466 77,384 7,188 1,748,251 2,222,369 685,310 16,079 1,419 748,060 723,638 4,151 388,173 442,126 149,779 446,806 5,860 432,296 2,525 138,536 12,535 3,343,328 2,958 134,743 3,111 297,979 314,854 2,033,684 1,510,415 1,873,457 1,200,821 12,204 1,624,729 625,683 3,087 813,066 12,662,893 547,718 884 20,714 22,005 485 37,049 74,861 1,419 13,977 107,166 370,263 742,547 35,633 61,854 156,468 14,823 133,006 91,496 2,212 848,067 308,303 514,943 1,439,019 885,951 1,813,063 584,940 179,870 206,848 326,276 621,881 537,701 311,308 11,261 193,830 1,684 32,666 197,521 465,576 2,640,033 259,987 2,311 2,350 311,602 5,545,760 79,545 3,794,333 203,070 1,739,233 2,362 237,486 1,428,020 5,060 185,946 1,237,873 6,484 168,239 455,492 85,203 204,365 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
1990 1990002 UN development groups 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
1990 1990003 More developed regions b 901 82,767,216 3,385,103 1,077,179 119,386 177,986 867,015 1,027 3,737 167,381 540 14,561 223,308 654,111 4,639 245,256 471,950 1,056,543 23,376 1,783 161,091 79,563 1,570,292 338,069 32,183 14,838 71,550 554 43,272 2,900 854,349 2,843 282,969 158 6,623 122,758 6,386 4,620 80,227 237,274 50,166 938,586 269 9,114 3,608 18,625 191,694 1,460,345 516,749 14,382 365,140 18,946 61,595 17,441 48,040 49,237 422,110 774,534 39,067 163,985 268,472 15,643 95,528 194,363 3,466 23,814 387,566 165,601 269,821 507,652 8,443 25,565 110,168 546 116,900 237 7,518 85,997 247,088 881,133 61 324 8,717 12,656 801,710 2,488,935 127,620 11,920 890,569 8,997 23,826 162 43 245,297 14,712 16,106 206,865 294,766 10 114,335 360,160 17,533 1,232,954 309,159 518,437 145,177 908,952 10,735 169,372 2,789,415 575,132 430,558 70,531 2,833,828 154,625 989 16,425 483,043 251,777 200,654 370,568 365 18,354 25,322 3,250 310,298 35,779 43,500 11,584 188,217 304 51,354 110,502 1,115 316 13,255 101,617 0 4,350,586 2,764 4,200 24,300 77,143 5,174 1,567,742 78,957 44,698 1,304 465 7,177 660,809 1,268 371,488 179,003 3,433 148,202 5,821 380,767 274 130,212 714 447,344 12 90,144 1,845 14,571 228,073 1,349,642 1,346,970 1,475,456 1,180,927 904 1,382,392 567,165 125 661,082 7,566,200 8,427 539 9,886 10,108 433 18,424 59,558 1,376 5,881 24,905 130,627 738,976 28,990 19,718 90,554 13,911 132,447 89,464 1,115 67,402 224,304 1 917,001 260,120 35,600 15,083 160,380 197,121 288,203 126,353 471,233 206,019 10,514 19,358 1,523 29,974 182,904 416,484 2,548,456 249,213 221 1,171 71,129 4,668,356 5,600 3,462,531 61,033 889,414 70 56,838 1,078,563 1,017 114,991 1,085,310 884 333 11,457 26,062 40,957 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
1990 1990004 Less developed regions c 902 70,244,257 3,163,423 1,289,621 6,703,964 2,298 54,712 1,014 55 657,561 1,507 7,192 206,861 245,538 5,957 58,440 34,138 577,538 1,806 11,037 5,290,740 5,368 197,314 27,291 3,934 219,476 152 27,911 181,421 306 7,417 23,210 217,423 2,936 19,700 490,335 1,014,946 332,498 11,141 118,156 65,687 59,577 104 37,248 333,194 101 301,332 2,771,303 34,331 81,266 644,795 21,137 34,777 47 21,671 317,111 3,697 61,262 4,123 10,393 8,788 24,141 340,998 7,398 1,842 18,623 78,650 48,407 1,052,357 734,423 27,735 145,038 3,737 34,635 1,573,055 23 2 4,169 3,677 334,762 2,783 2,825 6,635 23,624 117,744 440,513 243,542 74 131,890 513 19,423 5,666 1,333 103,035 338,051 39,303 26,866 234,107 21 42,259 27,354 88 5,390,223 1,329,206 112,902 1,361,525 8,334 0 112,225 561,591 13,878 178,363 243,466 137,811 95,715 3,064 65,186 39,535 231,244 14,480 138,755 190,974 498,532 50,934 178 30,752 362 15,924 131,853 374,545 1,889 596,082 244 311 10,725 121,233 9,091 1,835 44,779 4,950 279 166 241 2,014 180,509 2,143,412 640,612 14,775 954 740,883 62,829 2,883 16,685 263,123 146,346 298,604 39 51,529 2,251 8,324 11,821 2,895,984 2,946 44,599 1,266 283,408 86,781 684,042 163,445 398,001 19,894 11,300 242,337 58,518 2,962 151,984 5,096,693 539,291 345 10,828 11,897 52 18,625 15,303 43 8,096 82,261 239,636 3,571 6,643 42,136 65,914 912 559 2,032 1,097 780,665 83,999 514,942 522,018 625,831 1,777,463 569,857 19,490 9,727 38,073 495,528 66,468 105,289 747 174,472 161 2,692 14,617 49,092 91,577 10,774 2,090 1,179 240,473 877,404 73,945 331,802 142,037 849,819 2,292 180,648 349,457 4,043 70,955 152,563 5,600 167,906 444,035 59,141 163,408 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
1990 1990005 Least developed countries d 941 11,060,221 482,753 239,756 0 0 5,622 0 0 608,108 0 0 526 0 0 1,465 190 0 0 89 2,046 0 0 973 0 41,733 0 16,805 0 0 0 652 1,631 0 0 0 43,162 329,604 10,796 14,322 33,380 1,876 0 26,440 208,161 0 333 245,923 54 0 828 8,549 25,168 0 274 308,481 0 1,493 0 5 0 78 257,210 189 904 0 2,406 0 30,582 0 355 134,471 0 102 1,432,950 0 0 721 0 38,541 0 0 5,273 13,064 0 4,776 58,990 0 40 0 0 0 0 0 200,952 37,630 0 0 0 0 10 0 462,470 75,246 0 5,020 1 0 0 2,401 0 9,729 0 0 82,931 1,054 29 0 58,843 0 7,337 2,954 477,733 3,757 0 0 0 10,810 47,615 92,880 0 132,257 0 0 0 107,801 113 0 306 0 0 0 0 0 3,711 1,265,353 226,295 3,080 928 10,025 548 292 487 0 55,934 114,276 0 0 0 4,249 0 17,315 0 0 1,160 0 351 818 0 8,194 1,546 0 354 0 957 0 1,465 532,395 0 0 0 0 0 21 0 3,219 2,132 196,154 0 6,426 39,039 10,678 0 0 15 83 757,421 21,041 498,608 1,778 115 2,697 244,607 0 1,170 686 2,393 40,537 32,076 0 32,868 0 24 0 221 6 0 0 377 149,308 84 62 15,760 72,693 38,316 0 286 2,027 9 2,510 71,579 0 0 357 26,254 75,122 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
1990 1990006 Less developed regions, excluding least developed countries 934 59,184,036 2,680,670 1,049,865 6,703,964 2,298 49,090 1,014 55 49,453 1,507 7,192 206,335 245,538 5,957 56,975 33,948 577,538 1,806 10,948 5,288,694 5,368 197,314 26,318 3,934 177,743 152 11,106 181,421 306 7,417 22,558 215,792 2,936 19,700 490,335 971,784 2,894 345 103,834 32,307 57,701 104 10,808 125,033 101 300,999 2,525,380 34,277 81,266 643,967 12,588 9,609 47 21,397 8,630 3,697 59,769 4,123 10,388 8,788 24,063 83,788 7,209 938 18,623 76,244 48,407 1,021,775 734,423 27,380 10,567 3,737 34,533 140,105 23 2 3,448 3,677 296,221 2,783 2,825 1,362 10,560 117,744 435,737 184,552 74 131,850 513 19,423 5,666 1,333 103,035 137,099 1,673 26,866 234,107 21 42,259 27,344 88 4,927,753 1,253,960 112,902 1,356,505 8,333 0 112,225 559,190 13,878 168,634 243,466 137,811 12,784 2,010 65,157 39,535 172,401 14,480 131,418 188,020 20,799 47,177 178 30,752 362 5,114 84,238 281,665 1,889 463,825 244 311 10,725 13,432 8,978 1,835 44,473 4,950 279 166 241 2,014 176,798 878,059 414,317 11,695 26 730,858 62,281 2,591 16,198 263,123 90,412 184,328 39 51,529 2,251 4,075 11,821 2,878,669 2,946 44,599 106 283,408 86,430 683,224 163,445 389,807 18,348 11,300 241,983 58,518 2,005 151,984 5,095,228 6,896 345 10,828 11,897 52 18,625 15,282 43 4,877 80,129 43,482 3,571 217 3,097 55,236 912 559 2,017 1,014 23,244 62,958 16,334 520,240 625,716 1,774,766 325,250 19,490 8,557 37,387 493,135 25,931 73,213 747 141,604 161 2,668 14,617 48,871 91,571 10,774 2,090 802 91,165 877,320 73,883 316,042 69,344 811,503 2,292 180,362 347,430 4,034 68,445 80,984 5,600 167,906 443,678 32,887 88,286 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA

Clean the data

UN_migration_data <- UN_migration_data %>% filter(Type.of.data..a.!= "")

UN_migration_data <- UN_migration_data %>% 
  select(-Sort.order, -Notes, -Code, -Type.of.data..a., -Total, -Other.North, -Other.South)
names(UN_migration_data)[1] <- "Year"
names(UN_migration_data)[2] <- "Destination_country"
head(UN_migration_data) %>% kable() %>% kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive")) %>% scroll_box(width="100%",height="400px")
Year Destination_country Afghanistan Albania Algeria American.Samoa Andorra Angola Anguilla Antigua.and.Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia..Plurinational.State.of. Bonaire..Sint.Eustatius.and.Saba Bosnia.and.Herzegovina Botswana Brazil British.Virgin.Islands Brunei.Darussalam Bulgaria Burkina.Faso Burundi Cabo.Verde Cambodia Cameroon Canada Cayman.Islands Central.African.Republic Chad Channel.Islands Chile China China..Hong.Kong.SAR China..Macao.SAR Colombia Comoros Congo Cook.Islands Costa.Rica CÃ.te.d.Ivoire Croatia Cuba CuraÃ.ao Cyprus Czechia Dem..People.s.Republic.of.Korea Democratic.Republic.of.the.Congo Denmark Djibouti Dominica Dominican.Republic Ecuador Egypt El.Salvador Equatorial.Guinea Eritrea Estonia Eswatini Ethiopia Falkland.Islands..Malvinas. Faroe.Islands Fiji Finland France French.Guiana French.Polynesia Gabon Gambia Georgia Germany Ghana Gibraltar Greece Greenland Grenada Guadeloupe Guam Guatemala Guinea Guinea.Bissau Guyana Haiti Holy.See Honduras Hungary Iceland India Indonesia Iran..Islamic.Republic.of. Iraq Ireland Isle.of.Man Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kiribati Kuwait Kyrgyzstan Lao.People.s.Democratic.Republic Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Madagascar Malawi Malaysia Maldives Mali Malta Marshall.Islands Martinique Mauritania Mauritius Mayotte Mexico Micronesia..Fed..States.of. Monaco Mongolia Montenegro Montserrat Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New.Caledonia New.Zealand Nicaragua Niger Nigeria Niue North.Macedonia Northern.Mariana.Islands Norway Oman Pakistan Palau Panama Papua.New.Guinea Paraguay Peru Philippines Poland Portugal Puerto.Rico Qatar Republic.of.Korea Republic.of.Moldova RÃ.union Romania Russian.Federation Rwanda Saint.Helena Saint.Kitts.and.Nevis Saint.Lucia Saint.Pierre.and.Miquelon Saint.Vincent.and.the.Grenadines Samoa San.Marino Sao.Tome.and.Principe Saudi.Arabia Senegal Serbia Seychelles Sierra.Leone Singapore Sint.Maarten..Dutch.part. Slovakia Slovenia Solomon.Islands Somalia South.Africa South.Sudan Spain Sri.Lanka State.of.Palestine Sudan Suriname Sweden Switzerland Syrian.Arab.Republic Tajikistan Thailand Timor.Leste Togo Tokelau Tonga Trinidad.and.Tobago Tunisia Turkey Turkmenistan Turks.and.Caicos.Islands Tuvalu Uganda Ukraine United.Arab.Emirates United.Kingdom United.Republic.of.Tanzania United.States.of.America United.States.Virgin.Islands Uruguay Uzbekistan Vanuatu Venezuela..Bolivarian.Republic.of. Viet.Nam Wallis.and.Futuna.Islands Western.Sahara Yemen Zambia Zimbabwe X X.1 X.2 X.3 X.4 X.5 X.6 X.7 X.8 X.9 X.10 X.11 X.12 X.13 X.14 X.15 X.16 X.17 X.18 X.19 X.20 X.21 X.22 X.23 X.24 X.25 X.26 X.27 X.28 X.29 X.30 X.31 X.32 X.33 X.34 X.35 X.36 X.37 X.38 X.39 X.40 X.41 X.42 X.43 X.44 X.45 X.46 X.47
1990 Burundi 642 36,654 321 186 221,943 1,833 11,912 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
1990 Comoros 543 87 10,810 957 163 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
1990 Djibouti 13,405 101,216 289 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
1990 Eritrea 247 618 8 27 407 1,284 108 39 187 114 3,537 991 1,438 97 933 131 175 34 218 91 82 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
1990 Ethiopia 19 48 904 69,681 71 616,940 384,266 53,857 103 68 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
1990 Kenya 99 394 0 26,695 1,043 119 3,874 7,875 197 5,801 814 83,355 66,464 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 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 
### Country to Continenet Map
countryDF <- read.delim("UNCountryContinentMap.csv",header = TRUE, stringsAsFactors = FALSE, sep = ",")

Use tidyr function gather() to unpivot Country of origin columns into a variable called ‘origin_country’ and replace ‘.’ character in ‘Destination’origin_country’ variable with a space character

UN_migration_data <- UN_migration_data %>% 
  gather(key = origin_country, value = "no_of_migrants", -Year, -Destination_country)

UN_migration_data$origin_country <- str_replace_all(UN_migration_data$origin_country, "\\."," ")

UN_migration_data <- UN_migration_data %>% 
  filter(no_of_migrants != "..")
UN_migration_data$no_of_migrants <- str_replace_all(UN_migration_data$no_of_migrants, "\\."," ")

UN_migration_data$no_of_migrants <- as.numeric(UN_migration_data$no_of_migrants)
## Warning: NAs introduced by coercion
UN_migration_data <- UN_migration_data %>% 
  filter(!is.na(no_of_migrants))

### Lookup and Tag Continenet attribute based on destination_country

UN_migration_data <- UN_migration_data %>% 
  inner_join(countryDF, by = c("Destination_country" = "Country"))
head(UN_migration_data) %>% 
  kable() %>% 
  kable_styling(bootstrap_options = c("striped", "hover", "condensed", "responsive")) %>% 
  scroll_box(width="100%",height="400px")
Year Destination_country origin_country no_of_migrants Continent
1990 Namibia Afghanistan 64 Africa
1990 South Africa Afghanistan 59 Africa
1990 Egypt Afghanistan 237 Africa
1990 Libya Afghanistan 677 Africa
1990 Azerbaijan Afghanistan 254 Europe
1990 Bahrain Afghanistan 215 Asia

Dataset 2

Introduction

Dataset 3

Introduction