Struggling to filter data in R - r
Here is the data that I am using :
https://www.dropbox.com/s/dl/chmzqmus6bfoaim/climate_clean.csv
I added a variable called average_temperature_fahrenheit by doing so
climate = mutate(climate, average_temperature_fahrenheit = 9/5*average_temperature_celsius+32)
Now I want to know the highest temperature in Fahrenheit during the months of June, July and August between 1970 and 1980 in Europe and North America so I thought I needed to filter my data frame climate by doing so
climate %>% filter(continent == c("Europe","North America") & month == c("Jun","Jul","Aug") & year[1970:1980])
But clearly I did not succeed because it shows me only the month of August
Please could you tell me where I messed up in the filter function part
You could go with
library(data.table)
climate <-fread("~/downloads/climate_clean.csv")
climate %>%
mutate(average_temperature_fahrenheit = 9/5*average_temperature_celsius+32) %>%
filter(year %in% 1970:1980, month %in% c("Jun", "Jul", "Aug")) %>%
group_by(continent) %>%
summarise(MaxF = max(average_temperature_fahrenheit))
# A tibble: 6 x 2
continent MaxF
<chr> <dbl>
1 Africa 93.6
2 Asia 98.6
3 Europe 83.9
4 North America 83.0
5 Oceania 83.7
6 South America 80.2
You could reverse the rank function touse it in ave and subset the data where it's 1. Instead of creating a long spaghetti of code I'd do subsetting in multiple steps.
## subset by month, year, continent
res <- climate[climate$month %in% month.abb[6:8] & climate$year %in% 1970:1980 &
climate$continent %in% c("Europe", "North America"), ]
## create rank
res <- transform(res,
ave.temp.F=average_temperature_celsius * 9/5 + 32,
rank=ave(average_temperature_celsius, iso3,
FUN=function(x) rev(rank(x))))
## subset by rank
res <- res[res$rank == 1, ]
## some ordering (`-9` drops the rank column)
res <- res[order(res$continent, res$year, res$month, res$iso3), -9]
Result
res
# country iso3 continent year month average_temperature_celsius average_rainfall_mm ave.temp.F
# 177956 Italy ITA Europe 1970 Aug 20.41250 77.53980 68.74250
# 189836 Monaco MCO Europe 1970 Aug 17.54660 51.22330 63.58388
# 179535 Kazakhstan KAZ Europe 1971 Aug 19.82530 18.28780 67.68554
# 148959 Armenia ARM Europe 1972 Aug 19.71050 34.85870 67.47890
# 150399 Azerbaijan AZE Europe 1972 Aug 23.73650 18.82320 74.72570
# 206420 Spain ESP Europe 1972 Aug 20.46590 29.92810 68.83862
# 170559 Georgia GEO Europe 1972 Aug 19.18560 66.58620 66.53408
# 198500 Portugal PRT Europe 1972 Aug 20.93670 6.03864 69.68606
# 200799 Russia RUS Europe 1972 Aug 11.89720 61.69850 53.41496
# 146684 Albania ALB Europe 1974 Aug 21.45010 46.19520 70.61018
# 152444 Belarus BLR Europe 1974 Aug 17.00830 43.09090 62.61494
# 163047 Cyprus CYP Europe 1974 Aug 27.13730 3.16681 80.84714
# 167204 Estonia EST Europe 1974 Aug 15.27410 56.88330 59.49338
# 169004 Finland FIN Europe 1974 Aug 13.47990 91.12890 56.26382
# 171884 Greece GRC Europe 1974 Aug 23.14990 13.01370 73.66982
# 184844 Lithuania LTU Europe 1974 Aug 16.37240 53.21470 61.47032
# 182684 Latvia LVA Europe 1974 Aug 15.71120 59.34710 60.28016
# 185564 Macedonia MKD Europe 1974 Aug 20.34650 33.97170 68.62370
# 215084 Ukraine UKR Europe 1974 Aug 19.58960 39.45000 67.26128
# 156042 Bulgaria BGR Europe 1974 Jun 17.94660 66.96620 64.30388
# 154602 Bosnia and Herzegovina BIH Europe 1974 Jun 15.80810 128.16000 60.45458
# 189522 Moldova MDA Europe 1974 Jun 18.23260 87.43030 64.81868
# 199602 Republic of Montenegro MNE Europe 1974 Jun 14.96460 103.38300 58.93628
# 175496 Iceland ISL Europe 1975 Aug 8.40970 87.26150 47.13746
# 187736 Malta MLT Europe 1975 Aug 25.47840 36.46360 77.86112
# 194936 Norway NOR Europe 1975 Aug 11.25500 74.38320 52.25900
# 209336 Sweden SWE Europe 1975 Aug 13.22820 60.74740 55.81076
# 149948 Austria AUT Europe 1976 Aug 12.60120 98.79700 54.68216
# 163628 Czech Republic CZE Europe 1976 Aug 15.39740 55.42650 59.71532
# 162188 Croatia HRV Europe 1976 Aug 16.69060 98.21130 62.04308
# 175148 Hungary HUN Europe 1976 Aug 17.16470 48.66250 62.89646
# 198188 Poland POL Europe 1976 Aug 15.82960 48.73520 60.49328
# 200348 Romania ROU Europe 1976 Aug 16.03970 85.58330 60.87146
# 199988 Republic of Serbia SRB Europe 1976 Aug 16.82680 78.80250 62.28824
# 204308 Slovakia SVK Europe 1976 Aug 14.86390 53.49560 58.75502
# 204668 Slovenia SVN Europe 1976 Aug 14.87980 98.93020 58.78364
# 213519 Turkey TUR Europe 1977 Aug 22.37990 7.52567 72.28382
# 147452 Andorra AND Europe 1978 Aug 18.81170 33.16530 65.86106
# 152852 Belgium BEL Europe 1978 Aug 15.65460 39.78100 60.17828
# 169412 France FRA Europe 1978 Aug 17.11220 41.63730 62.80196
# 215852 United Kingdom GBR Europe 1978 Aug 13.77240 83.64290 56.79032
# 177332 Ireland IRL Europe 1978 Aug 13.97130 86.99350 57.14834
# 185252 Luxembourg LUX Europe 1978 Aug 15.21680 43.07880 59.39024
# 192452 Netherlands NLD Europe 1978 Aug 15.46520 48.70340 59.83736
# 209744 Switzerland CHE Europe 1979 Aug 12.49180 191.84800 54.48524
# 171224 Germany DEU Europe 1979 Aug 15.89550 71.42340 60.61190
# 164024 Denmark DNK Europe 1979 Aug 15.08630 80.27490 59.15534
# 167984 Faroe Islands FRO Europe 1979 Aug 9.45723 82.92610 49.02301
# 184544 Liechtenstein LIE Europe 1979 Aug 9.05277 217.23500 48.29499
# 172208 Greenland GRL North America 1971 Aug -6.22770 52.95410 20.79014
# 157820 Canada CAN North America 1972 Aug 9.42089 53.17810 48.95760
# 148124 Antigua and Barbuda ATG North America 1974 Aug 26.48220 174.62500 79.66796
# 151004 Bahamas BHS North America 1974 Aug 27.64530 149.01000 81.76154
# 162524 Cuba CUB North America 1974 Aug 27.07380 110.54600 80.73284
# 164684 Dominica DMA North America 1974 Aug 25.12810 145.65000 77.23058
# 165044 Dominican Republic DOM North America 1974 Aug 25.07960 143.50400 77.14328
# 174404 Haiti HTI North America 1974 Aug 25.46790 152.89300 77.84222
# 178364 Jamaica JAM North America 1974 Aug 25.69750 329.85900 78.25550
# 207164 St. Kitts and Nevis KNA North America 1974 Aug 25.65000 181.47400 78.17000
# 198884 Puerto Rico PRI North America 1974 Aug 26.26840 246.12400 79.28312
# 212564 Trinidad and Tobago TTO North America 1974 Aug 26.11950 182.57200 79.01510
# 216176 United States USA North America 1975 Aug 18.68970 64.20100 65.64146
# 196375 Panama PAN North America 1975 Jul 24.11360 325.95700 75.40448
# 161454 Costa Rica CRI North America 1975 Jun 23.90800 333.15800 75.03440
# 153223 Belize BLZ North America 1979 Jul 26.74570 349.16200 80.14226
# 172662 Grenada GRD North America 1979 Jun 27.77390 239.63500 81.99302
# 173022 Guatemala GTM North America 1979 Jun 24.49050 400.83000 76.08290
# 174822 Honduras HND North America 1979 Jun 24.59780 372.34600 76.27604
# 207582 St. Lucia LCA North America 1979 Jun 26.97770 335.70000 80.55986
# 189222 Mexico MEX North America 1979 Jun 24.40470 81.00740 75.92846
# 193542 Nicaragua NIC North America 1979 Jun 25.30880 466.90400 77.55584
# 166182 El Salvador SLV North America 1979 Jun 24.14100 348.93900 75.45380
# 207942 St. Vincent and the Grenadines VCT North America 1979 Jun 28.16000 252.66000 82.68800
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Tried to download the data from website but it gives this result. No download occurred. Country Name,Country Code,Region,Year,Fertility Rate Aruba,ABW,The Americas,1960,4.82 Afghanistan,AFG,Asia,1960,7.45 Angola,AGO,Africa,1960,7.379 Albania,ALB,Europe,1960,6.186 United Arab Emirates,ARE,Middle East,1960,6.928 Argentina,ARG,The Americas,1960,3.109 Armenia,ARM,Asia,1960,4.55 Antigua and Barbuda,ATG,The Americas,1960,4.425 Australia,AUS,Oceania,1960,3.453 Austria,AUT,Europe,1960,2.69 Azerbaijan,AZE,Asia,1960,5.571 Burundi,BDI,Africa,1960,6.953 Belgium,BEL,Europe,1960,2.54 Benin,BEN,Africa,1960,6.282 Burkina Faso,BFA,Africa,1960,6.291 Bangladesh,BGD,Asia,1960,6.725 Bulgaria,BGR,Europe,1960,2.31 Bahrain,BHR,Middle East,1960,7.09 "Bahamas, The",BHS,The Americas,1960,4.495 Bosnia and Herzegovina,BIH,Europe,1960,3.77 Belarus,BLR,Europe,1960,2.67 Belize,BLZ,The Americas,1960,6.5 Bolivia,BOL,The Americas,1960,6.7 Brazil,BRA,The Americas,1960,6.21 Barbados,BRB,The Americas,1960,4.333 Brunei Darussalam,BRN,Asia,1960,6.487 Bhutan,BTN,Asia,1960,6.67 Botswana,BWA,Africa,1960,6.615 Central African Republic,CAF,Africa,1960,5.84 Canada,CAN,The Americas,1960,3.811 Switzerland,CHE,Europe,1960,2.44 Chile,CHL,The Americas,1960,5.113 China,CHN,Asia,1960,5.758 Cote d'Ivoire,CIV,Africa,1960,7.351 Cameroon,CMR,Africa,1960,5.647 "Congo, Rep.",COG,Africa,1960,5.88 Colombia,COL,The Americas,1960,6.807 Comoros,COM,Africa,1960,6.792 Cabo Verde,CPV,Africa,1960,6.885 Costa Rica,CRI,The Americas,1960,6.451 Cuba,CUB,The Americas,1960,4.182 Cyprus,CYP,Europe,1960,3.5 Czech Republic,CZE,Europe,1960,2.09 Germany,DEU,Europe,1960,2.37 Djibouti,DJI,Africa,1960,6.461 Denmark,DNK,Europe,1960,2.57 Dominican Republic,DOM,The Americas,1960,7.555 Algeria,DZA,Africa,1960,7.524 Ecuador,ECU,The Americas,1960,6.721 "Egypt, Arab Rep.",EGY,Africa,1960,6.63 Eritrea,ERI,Africa,1960,6.899 Spain,ESP,Europe,1960,2.86 Estonia,EST,Europe,1960,1.98 Ethiopia,ETH,Africa,1960,6.88 Finland,FIN,Europe,1960,2.72 Fiji,FJI,Oceania,1960,6.461 France,FRA,Europe,1960,2.85 "Micronesia, Fed. Sts.",FSM,Oceania,1960,6.934 Gabon,GAB,Africa,1960,4.384 United Kingdom,GBR,Europe,1960,2.69 Georgia,GEO,Asia,1960,2.964 Ghana,GHA,Africa,1960,6.749 Guinea,GIN,Africa,1960,6.114 "Gambia, The",GMB,Africa,1960,5.573 Guinea-Bissau,GNB,Africa,1960,5.921 Equatorial Guinea,GNQ,Africa,1960,5.505 Greece,GRC,Europe,1960,2.23 Grenada,GRD,The Americas,1960,6.743 Guatemala,GTM,The Americas,1960,6.534 Guam,GUM,Oceania,1960,6.052 Guyana,GUY,The Americas,1960,5.754 "Hong Kong SAR, China",HKG,Asia,1960,5.162 Honduras,HND,The Americas,1960,7.458 Croatia,HRV,Europe,1960,2.332 Haiti,HTI,The Americas,1960,6.324 Hungary,HUN,Europe,1960,2.02 Indonesia,IDN,Asia,1960,5.666 India,IND,Asia,1960,5.906 Ireland,IRL,Europe,1960,3.78 "Iran, Islamic Rep.",IRN,Middle East,1960,6.927 Iraq,IRQ,Middle East,1960,6.252 Iceland,ISL,Europe,1960,4.29 Italy,ITA,Europe,1960,2.37 Jamaica,JAM,The Americas,1960,5.419 Jordan,JOR,Middle East,1960,7.687 Japan,JPN,Asia,1960,2.001 Kazakhstan,KAZ,Asia,1960,4.563 Kenya,KEN,Africa,1960,7.946 Kyrgyz Republic,KGZ,Asia,1960,5.166 Cambodia,KHM,Asia,1960,6.967 Kiribati,KIR,Oceania,1960,6.788 "Korea, Rep.",KOR,Asia,1960,6.155 Kuwait,KWT,Middle East,1960,7.251 Lao PDR,LAO,Asia,1960,5.961 Lebanon,LBN,Middle East,1960,5.739 Liberia,LBR,Africa,1960,6.406 Libya,LBY,Africa,1960,7.202 St. Lucia,LCA,The Americas,1960,6.967 Sri Lanka,LKA,Asia,1960,5.541 Lesotho,LSO,Africa,1960,5.839 Lithuania,LTU,Europe,1960,2.56 Luxembourg,LUX,Europe,1960,2.29 Latvia,LVA,Europe,1960,1.94 "Macao SAR, China",MAC,Asia,1960,4.945 Morocco,MAR,Africa,1960,7.065 Moldova,MDA,Europe,1960,3.328 Madagascar,MDG,Africa,1960,7.3 Maldives,MDV,Asia,1960,7.021 Mexico,MEX,The Americas,1960,6.768 "Macedonia, FYR",MKD,Europe,1960,3.842 Mali,MLI,Africa,1960,6.967 Malta,MLT,Europe,1960,3.62 Myanmar,MMR,Asia,1960,6.051 Montenegro,MNE,Europe,1960,3.521 Mongolia,MNG,Asia,1960,6.953 Mozambique,MOZ,Africa,1960,6.6 Mauritania,MRT,Africa,1960,6.775 Mauritius,MUS,Africa,1960,6.167 Malawi,MWI,Africa,1960,6.94 Malaysia,MYS,Asia,1960,6.194 Namibia,NAM,Africa,1960,6.15 New Caledonia,NCL,Oceania,1960,6.278 Niger,NER,Africa,1960,7.407 Nigeria,NGA,Africa,1960,6.354 Nicaragua,NIC,The Americas,1960,7.336 Netherlands,NLD,Europe,1960,3.12 Norway,NOR,Europe,1960,2.85 Nepal,NPL,Asia,1960,5.959 New Zealand,NZL,Oceania,1960,4.129 Oman,OMN,Middle East,1960,7.247 Pakistan,PAK,Asia,1960,6.6 Panama,PAN,The Americas,1960,5.87 Peru,PER,The Americas,1960,6.971 Philippines,PHL,Asia,1960,7.148 Papua New Guinea,PNG,Oceania,1960,6.275 Poland,POL,Europe,1960,2.98 Puerto Rico,PRI,The Americas,1960,4.657 Portugal,PRT,Europe,1960,3.16 Paraguay,PRY,The Americas,1960,6.5 French Polynesia,PYF,Oceania,1960,5.658 Qatar,QAT,Middle East,1960,6.971 Romania,ROU,Europe,1960,2.34 Russian Federation,RUS,Europe,1960,2.52 Rwanda,RWA,Africa,1960,8.187 Saudi Arabia,SAU,Middle East,1960,7.216 Sudan,SDN,Africa,1960,6.691 Senegal,SEN,Africa,1960,6.951 Singapore,SGP,Asia,1960,5.454 Solomon Islands,SLB,Oceania,1960,6.388 Sierra Leone,SLE,Africa,1960,5.97 El Salvador,SLV,The Americas,1960,6.674 Somalia,SOM,Africa,1960,7.25 South Sudan,SSD,Africa,1960,6.721 Sao Tome and Principe,STP,Africa,1960,6.242 Suriname,SUR,The Americas,1960,6.608 Slovak Republic,SVK,Europe,1960,3.04 Slovenia,SVN,Europe,1960,2.324 Sweden,SWE,Europe,1960,2.17 Swaziland,SWZ,Africa,1960,6.717 Syrian Arab Republic,SYR,Middle East,1960,7.467 Chad,TCD,Africa,1960,6.25 Togo,TGO,Africa,1960,6.521 Thailand,THA,Asia,1960,6.147 Tajikistan,TJK,Asia,1960,6.235 Turkmenistan,TKM,Asia,1960,6.415 Timor-Leste,TLS,Asia,1960,6.373 Tonga,TON,Oceania,1960,7.363 Trinidad and Tobago,TTO,The Americas,1960,5.264 Tunisia,TUN,Africa,1960,7.043 Turkey,TUR,Europe,1960,6.303 Tanzania,TZA,Africa,1960,6.806 Uganda,UGA,Africa,1960,6.999 Ukraine,UKR,Europe,1960,2.24 Uruguay,URY,The Americas,1960,2.88 United States,USA,The Americas,1960,3.654 Uzbekistan,UZB,Asia,1960,6.707 St. Vincent and the Grenadines,VCT,The Americas,1960,7.224 "Venezuela, RB",VEN,The Americas,1960,6.616 Virgin Islands (U.S.),VIR,The Americas,1960,5.615 Vietnam,VNM,Asia,1960,6.348 Vanuatu,VUT,Oceania,1960,7.197 Samoa,WSM,Oceania,1960,7.651 "Yemen, Rep.",YEM,Middle East,1960,7.38 South Africa,ZAF,Africa,1960,6.173 "Congo, Dem. Rep.",COD,Africa,1960,6.001 Zambia,ZMB,Africa,1960,7.018 Zimbabwe,ZWE,Africa,1960,7.158 Aruba,ABW,The Americas,2013,1.669 Afghanistan,AFG,Asia,2013,5.05 Angola,AGO,Africa,2013,6.165 Albania,ALB,Europe,2013,1.771 United Arab Emirates,ARE,Middle East,2013,1.801 Argentina,ARG,The Americas,2013,2.335 Armenia,ARM,Asia,2013,1.553 Antigua and Barbuda,ATG,The Americas,2013,2.088 Australia,AUS,Oceania,2013,1.921 Austria,AUT,Europe,2013,1.44 Azerbaijan,AZE,Asia,2013,2 Burundi,BDI,Africa,2013,6.035 Belgium,BEL,Europe,2013,1.79 Benin,BEN,Africa,2013,4.846 Burkina Faso,BFA,Africa,2013,5.607 Bangladesh,BGD,Asia,2013,2.209 Bulgaria,BGR,Europe,2013,1.5 Bahrain,BHR,Middle East,2013,2.075 "Bahamas, The",BHS,The Americas,2013,1.883 Bosnia and Herzegovina,BIH,Europe,2013,1.272 Belarus,BLR,Europe,2013,1.62 Belize,BLZ,The Americas,2013,2.611 Bolivia,BOL,The Americas,2013,3.017 Brazil,BRA,The Americas,2013,1.801 Barbados,BRB,The Americas,2013,1.791 Brunei Darussalam,BRN,Asia,2013,1.893 Bhutan,BTN,Asia,2013,2.082 Botswana,BWA,Africa,2013,2.864 Central African Republic,CAF,Africa,2013,4.368 Canada,CAN,The Americas,2013,1.61 Switzerland,CHE,Europe,2013,1.52 Chile,CHL,The Americas,2013,1.774 China,CHN,Asia,2013,1.668 Cote d'Ivoire,CIV,Africa,2013,5.063 Cameroon,CMR,Africa,2013,4.781 "Congo, Rep.",COG,Africa,2013,4.919 Colombia,COL,The Americas,2013,1.922 Comoros,COM,Africa,2013,4.56 Cabo Verde,CPV,Africa,2013,2.339 Costa Rica,CRI,The Americas,2013,1.841 Cuba,CUB,The Americas,2013,1.622 Cyprus,CYP,Europe,2013,1.455 Czech Republic,CZE,Europe,2013,1.45 Germany,DEU,Europe,2013,1.38 Djibouti,DJI,Africa,2013,3.262 Denmark,DNK,Europe,2013,1.73 Dominican Republic,DOM,The Americas,2013,2.51 Algeria,DZA,Africa,2013,2.893 Ecuador,ECU,The Americas,2013,2.571 "Egypt, Arab Rep.",EGY,Africa,2013,3.336 Eritrea,ERI,Africa,2013,4.363 Spain,ESP,Europe,2013,1.32 Estonia,EST,Europe,2013,1.56 Ethiopia,ETH,Africa,2013,4.517 Finland,FIN,Europe,2013,1.8 Fiji,FJI,Oceania,2013,2.589 France,FRA,Europe,2013,2.01 "Micronesia, Fed. Sts.",FSM,Oceania,2013,3.294 Gabon,GAB,Africa,2013,3.963 United Kingdom,GBR,Europe,2013,1.92 Georgia,GEO,Asia,2013,1.817 Ghana,GHA,Africa,2013,4.209 Guinea,GIN,Africa,2013,5.094 "Gambia, The",GMB,Africa,2013,5.751 Guinea-Bissau,GNB,Africa,2013,4.906 Equatorial Guinea,GNQ,Africa,2013,4.924 Greece,GRC,Europe,2013,1.29 Grenada,GRD,The Americas,2013,2.171 Guatemala,GTM,The Americas,2013,3.263 Guam,GUM,Oceania,2013,2.406 Guyana,GUY,The Americas,2013,2.585 "Hong Kong SAR, China",HKG,Asia,2013,1.124 Honduras,HND,The Americas,2013,2.442 Croatia,HRV,Europe,2013,1.51 Haiti,HTI,The Americas,2013,3.098 Hungary,HUN,Europe,2013,1.34 Indonesia,IDN,Asia,2013,2.484 India,IND,Asia,2013,2.465 Ireland,IRL,Europe,2013,2.01 "Iran, Islamic Rep.",IRN,Middle East,2013,1.726 Iraq,IRQ,Middle East,2013,4.026 Iceland,ISL,Europe,2013,2.04 Italy,ITA,Europe,2013,1.43 Jamaica,JAM,The Americas,2013,2.26 Jordan,JOR,Middle East,2013,3.244 Japan,JPN,Asia,2013,1.43 Kazakhstan,KAZ,Asia,2013,2.64 Kenya,KEN,Africa,2013,4.406 Kyrgyz Republic,KGZ,Asia,2013,3.2 Cambodia,KHM,Asia,2013,2.683 Kiribati,KIR,Oceania,2013,3.765 "Korea, Rep.",KOR,Asia,2013,1.187 Kuwait,KWT,Middle East,2013,2.6 Lao PDR,LAO,Asia,2013,3.063 Lebanon,LBN,Middle East,2013,1.495 Liberia,LBR,Africa,2013,4.793 Libya,LBY,Africa,2013,2.507 St. Lucia,LCA,The Americas,2013,1.913 Sri Lanka,LKA,Asia,2013,2.339 Lesotho,LSO,Africa,2013,3.222 Lithuania,LTU,Europe,2013,1.6 Luxembourg,LUX,Europe,2013,1.57 Latvia,LVA,Europe,2013,1.44 "Macao SAR, China",MAC,Asia,2013,1.204 Morocco,MAR,Africa,2013,2.535 Moldova,MDA,Europe,2013,1.456 Madagascar,MDG,Africa,2013,4.468 Maldives,MDV,Asia,2013,2.152 Mexico,MEX,The Americas,2013,2.272 "Macedonia, FYR",MKD,Europe,2013,1.511 Mali,MLI,Africa,2013,6.314 Malta,MLT,Europe,2013,1.43 Myanmar,MMR,Asia,2013,2.239 Montenegro,MNE,Europe,2013,1.666 Mongolia,MNG,Asia,2013,2.657 Mozambique,MOZ,Africa,2013,5.418 Mauritania,MRT,Africa,2013,4.662 Mauritius,MUS,Africa,2013,1.44 Malawi,MWI,Africa,2013,5.22 Malaysia,MYS,Asia,2013,1.956 Namibia,NAM,Africa,2013,3.56 New Caledonia,NCL,Oceania,2013,2.28 Niger,NER,Africa,2013,7.623 Nigeria,NGA,Africa,2013,5.707 Nicaragua,NIC,The Americas,2013,2.3 Netherlands,NLD,Europe,2013,1.72 Norway,NOR,Europe,2013,1.85 Nepal,NPL,Asia,2013,2.292 New Zealand,NZL,Oceania,2013,1.95 Oman,OMN,Middle East,2013,2.823 Pakistan,PAK,Asia,2013,3.682 Panama,PAN,The Americas,2013,2.465 Peru,PER,The Americas,2013,2.48 Philippines,PHL,Asia,2013,3.011 Papua New Guinea,PNG,Oceania,2013,3.812 Poland,POL,Europe,2013,1.3 Puerto Rico,PRI,The Americas,2013,1.636 Portugal,PRT,Europe,2013,1.28 Paraguay,PRY,The Americas,2013,2.581 French Polynesia,PYF,Oceania,2013,2.059 Qatar,QAT,Middle East,2013,2.043 Romania,ROU,Europe,2013,1.53 Russian Federation,RUS,Europe,2013,1.7 Rwanda,RWA,Africa,2013,4.012 Saudi Arabia,SAU,Middle East,2013,2.818 Sudan,SDN,Africa,2013,4.421 Senegal,SEN,Africa,2013,5.134 Singapore,SGP,Asia,2013,1.19 Solomon Islands,SLB,Oceania,2013,4.031 Sierra Leone,SLE,Africa,2013,4.746 El Salvador,SLV,The Americas,2013,1.958 Somalia,SOM,Africa,2013,6.565 South Sudan,SSD,Africa,2013,5.108 Sao Tome and Principe,STP,Africa,2013,4.634 Suriname,SUR,The Americas,2013,2.386 Slovak Republic,SVK,Europe,2013,1.34 Slovenia,SVN,Europe,2013,1.58 Sweden,SWE,Europe,2013,1.91 Swaziland,SWZ,Africa,2013,3.334 Syrian Arab Republic,SYR,Middle East,2013,2.964 Chad,TCD,Africa,2013,6.264 Togo,TGO,Africa,2013,4.655 Thailand,THA,Asia,2013,1.524 Tajikistan,TJK,Asia,2013,3.514 Turkmenistan,TKM,Asia,2013,2.326 Timor-Leste,TLS,Asia,2013,5.2 Tonga,TON,Oceania,2013,3.768 Trinidad and Tobago,TTO,The Americas,2013,1.789 Tunisia,TUN,Africa,2013,2.25 Turkey,TUR,Europe,2013,2.041 Tanzania,TZA,Africa,2013,5.215 Uganda,UGA,Africa,2013,5.869 Ukraine,UKR,Europe,2013,1.506 Uruguay,URY,The Americas,2013,2.033 United States,USA,The Americas,2013,1.8695 Uzbekistan,UZB,Asia,2013,2.2 St. Vincent and the Grenadines,VCT,The Americas,2013,1.997 "Venezuela, RB",VEN,The Americas,2013,2.391 Virgin Islands (U.S.),VIR,The Americas,2013,1.77 Vietnam,VNM,Asia,2013,1.743 Vanuatu,VUT,Oceania,2013,3.383 Samoa,WSM,Oceania,2013,4.147 "Yemen, Rep.",YEM,Middle East,2013,4.284 South Africa,ZAF,Africa,2013,2.387 "Congo, Dem. Rep.",COD,Africa,2013,6.103 Zambia,ZMB,Africa,2013,5.429 Zimbabwe,ZWE,Africa,2013,3.977
If you don't want to save to a file, select all the text and copy it to your clipboard. For example, I just selected and copied the data in your question. Then in R you can do: df <- read.csv(file = "clipboard") So now df is the following data frame: df Country.Name Country.Code Region Year Fertility.Rate 1 Aruba ABW The Americas 1960 4.820 2 Afghanistan AFG Asia 1960 7.450 3 Angola AGO Africa 1960 7.379 4 Albania ALB Europe 1960 6.186 5 United Arab Emirates ARE Middle East 1960 6.928 6 Argentina ARG The Americas 1960 3.109 7 Armenia ARM Asia 1960 4.550 8 Antigua and Barbuda ATG The Americas 1960 4.425 9 Australia AUS Oceania 1960 3.453 10 Austria AUT Europe 1960 2.690 11 Azerbaijan AZE Asia 1960 5.571 12 Burundi BDI Africa 1960 6.953 13 Belgium BEL Europe 1960 2.540 14 Benin BEN Africa 1960 6.282 15 Burkina Faso BFA Africa 1960 6.291 16 Bangladesh BGD Asia 1960 6.725 17 Bulgaria BGR Europe 1960 2.310 18 Bahrain BHR Middle East 1960 7.090 19 Bahamas, The BHS The Americas 1960 4.495 20 Bosnia and Herzegovina BIH Europe 1960 3.770 21 Belarus BLR Europe 1960 2.670 22 Belize BLZ The Americas 1960 6.500 23 Bolivia BOL The Americas 1960 6.700 24 Brazil BRA The Americas 1960 6.210 25 Barbados BRB The Americas 1960 4.333 26 Brunei Darussalam BRN Asia 1960 6.487 27 Bhutan BTN Asia 1960 6.670 28 Botswana BWA Africa 1960 6.615 29 Central African Republic CAF Africa 1960 5.840 30 Canada CAN The Americas 1960 3.811 31 Switzerland CHE Europe 1960 2.440 32 Chile CHL The Americas 1960 5.113 33 China CHN Asia 1960 5.758 34 Cote d'Ivoire CIV Africa 1960 7.351 35 Cameroon CMR Africa 1960 5.647 36 Congo, Rep. COG Africa 1960 5.880 37 Colombia COL The Americas 1960 6.807 38 Comoros COM Africa 1960 6.792 39 Cabo Verde CPV Africa 1960 6.885 40 Costa Rica CRI The Americas 1960 6.451 41 Cuba CUB The Americas 1960 4.182 42 Cyprus CYP Europe 1960 3.500 43 Czech Republic CZE Europe 1960 2.090 44 Germany DEU Europe 1960 2.370 45 Djibouti DJI Africa 1960 6.461 46 Denmark DNK Europe 1960 2.570 47 Dominican Republic DOM The Americas 1960 7.555 48 Algeria DZA Africa 1960 7.524 49 Ecuador ECU The Americas 1960 6.721 50 Egypt, Arab Rep. EGY Africa 1960 6.630 51 Eritrea ERI Africa 1960 6.899 52 Spain ESP Europe 1960 2.860 53 Estonia EST Europe 1960 1.980 54 Ethiopia ETH Africa 1960 6.880 55 Finland FIN Europe 1960 2.720 56 Fiji FJI Oceania 1960 6.461 57 France FRA Europe 1960 2.850 58 Micronesia, Fed. Sts. FSM Oceania 1960 6.934 59 Gabon GAB Africa 1960 4.384 60 United Kingdom GBR Europe 1960 2.690 61 Georgia GEO Asia 1960 2.964 62 Ghana GHA Africa 1960 6.749 63 Guinea GIN Africa 1960 6.114 64 Gambia, The GMB Africa 1960 5.573 65 Guinea-Bissau GNB Africa 1960 5.921 66 Equatorial Guinea GNQ Africa 1960 5.505 67 Greece GRC Europe 1960 2.230 68 Grenada GRD The Americas 1960 6.743 69 Guatemala GTM The Americas 1960 6.534 70 Guam GUM Oceania 1960 6.052 71 Guyana GUY The Americas 1960 5.754 72 Hong Kong SAR, China HKG Asia 1960 5.162 73 Honduras HND The Americas 1960 7.458 74 Croatia HRV Europe 1960 2.332 75 Haiti HTI The Americas 1960 6.324 76 Hungary HUN Europe 1960 2.020 77 Indonesia IDN Asia 1960 5.666 78 India IND Asia 1960 5.906 79 Ireland IRL Europe 1960 3.780 80 Iran, Islamic Rep. IRN Middle East 1960 6.927 81 Iraq IRQ Middle East 1960 6.252 82 Iceland ISL Europe 1960 4.290 83 Italy ITA Europe 1960 2.370 84 Jamaica JAM The Americas 1960 5.419 85 Jordan JOR Middle East 1960 7.687 86 Japan JPN Asia 1960 2.001 87 Kazakhstan KAZ Asia 1960 4.563 88 Kenya KEN Africa 1960 7.946 89 Kyrgyz Republic KGZ Asia 1960 5.166 90 Cambodia KHM Asia 1960 6.967 91 Kiribati KIR Oceania 1960 6.788 92 Korea, Rep. KOR Asia 1960 6.155 93 Kuwait KWT Middle East 1960 7.251 94 Lao PDR LAO Asia 1960 5.961 95 Lebanon LBN Middle East 1960 5.739 96 Liberia LBR Africa 1960 6.406 97 Libya LBY Africa 1960 7.202 98 St. Lucia LCA The Americas 1960 6.967 99 Sri Lanka LKA Asia 1960 5.541 100 Lesotho LSO Africa 1960 5.839 101 Lithuania LTU Europe 1960 2.560 102 Luxembourg LUX Europe 1960 2.290 103 Latvia LVA Europe 1960 1.940 104 Macao SAR, China MAC Asia 1960 4.945 105 Morocco MAR Africa 1960 7.065 106 Moldova MDA Europe 1960 3.328 107 Madagascar MDG Africa 1960 7.300 108 Maldives MDV Asia 1960 7.021 109 Mexico MEX The Americas 1960 6.768 110 Macedonia, FYR MKD Europe 1960 3.842 111 Mali MLI Africa 1960 6.967 112 Malta MLT Europe 1960 3.620 113 Myanmar MMR Asia 1960 6.051 114 Montenegro MNE Europe 1960 3.521 115 Mongolia MNG Asia 1960 6.953 116 Mozambique MOZ Africa 1960 6.600 117 Mauritania MRT Africa 1960 6.775 118 Mauritius MUS Africa 1960 6.167 119 Malawi MWI Africa 1960 6.940 120 Malaysia MYS Asia 1960 6.194 121 Namibia NAM Africa 1960 6.150 122 New Caledonia NCL Oceania 1960 6.278 123 Niger NER Africa 1960 7.407 124 Nigeria NGA Africa 1960 6.354 125 Nicaragua NIC The Americas 1960 7.336 126 Netherlands NLD Europe 1960 3.120 127 Norway NOR Europe 1960 2.850 128 Nepal NPL Asia 1960 5.959 129 New Zealand NZL Oceania 1960 4.129 130 Oman OMN Middle East 1960 7.247 131 Pakistan PAK Asia 1960 6.600 132 Panama PAN The Americas 1960 5.870 133 Peru PER The Americas 1960 6.971 134 Philippines PHL Asia 1960 7.148 135 Papua New Guinea PNG Oceania 1960 6.275 136 Poland POL Europe 1960 2.980 137 Puerto Rico PRI The Americas 1960 4.657 138 Portugal PRT Europe 1960 3.160 139 Paraguay PRY The Americas 1960 6.500 140 French Polynesia PYF Oceania 1960 5.658 141 Qatar QAT Middle East 1960 6.971 142 Romania ROU Europe 1960 2.340 143 Russian Federation RUS Europe 1960 2.520 144 Rwanda RWA Africa 1960 8.187 145 Saudi Arabia SAU Middle East 1960 7.216 146 Sudan SDN Africa 1960 6.691 147 Senegal SEN Africa 1960 6.951 148 Singapore SGP Asia 1960 5.454 149 Solomon Islands SLB Oceania 1960 6.388 150 Sierra Leone SLE Africa 1960 5.970 151 El Salvador SLV The Americas 1960 6.674 152 Somalia SOM Africa 1960 7.250 153 South Sudan SSD Africa 1960 6.721 154 Sao Tome and Principe STP Africa 1960 6.242 155 Suriname SUR The Americas 1960 6.608 156 Slovak Republic SVK Europe 1960 3.040 157 Slovenia SVN Europe 1960 2.324 158 Sweden SWE Europe 1960 2.170 159 Swaziland SWZ Africa 1960 6.717 160 Syrian Arab Republic SYR Middle East 1960 7.467 161 Chad TCD Africa 1960 6.250 162 Togo TGO Africa 1960 6.521 163 Thailand THA Asia 1960 6.147 164 Tajikistan TJK Asia 1960 6.235 165 Turkmenistan TKM Asia 1960 6.415 166 Timor-Leste TLS Asia 1960 6.373 167 Tonga TON Oceania 1960 7.363 168 Trinidad and Tobago TTO The Americas 1960 5.264 169 Tunisia TUN Africa 1960 7.043 170 Turkey TUR Europe 1960 6.303 171 Tanzania TZA Africa 1960 6.806 172 Uganda UGA Africa 1960 6.999 173 Ukraine UKR Europe 1960 2.240 174 Uruguay URY The Americas 1960 2.880 175 United States USA The Americas 1960 3.654 176 Uzbekistan UZB Asia 1960 6.707 177 St. Vincent and the Grenadines VCT The Americas 1960 7.224 178 Venezuela, RB VEN The Americas 1960 6.616 179 Virgin Islands (U.S.) VIR The Americas 1960 5.615 180 Vietnam VNM Asia 1960 6.348 181 Vanuatu VUT Oceania 1960 7.197 182 Samoa WSM Oceania 1960 7.651 183 Yemen, Rep. YEM Middle East 1960 7.380 184 South Africa ZAF Africa 1960 6.173 185 Congo, Dem. Rep. COD Africa 1960 6.001 186 Zambia ZMB Africa 1960 7.018 187 Zimbabwe ZWE Africa 1960 7.158 188 Aruba ABW The Americas 2013 1.669 189 Afghanistan AFG Asia 2013 5.050 190 Angola AGO Africa 2013 6.165 191 Albania ALB Europe 2013 1.771 192 United Arab Emirates ARE Middle East 2013 1.801 193 Argentina ARG The Americas 2013 2.335 194 Armenia ARM Asia 2013 1.553 195 Antigua and Barbuda ATG The Americas 2013 2.088 196 Australia AUS Oceania 2013 1.921 197 Austria AUT Europe 2013 1.440 198 Azerbaijan AZE Asia 2013 2.000 199 Burundi BDI Africa 2013 6.035 200 Belgium BEL Europe 2013 1.790
We can use soread from overflow package after selecting and copying the file library(overflow) df1 <- soread(sep=",") head(df1) # Country.Name Country.Code Region Year Fertility.Rate #1 Aruba ABW The Americas 1960 4.820 #2 Afghanistan AFG Asia 1960 7.450 #3 Angola AGO Africa 1960 7.379 #4 Albania ALB Europe 1960 6.186 #5 United Arab Emirates ARE Middle East 1960 6.928 #6 Argentina ARG The Americas 1960 3.109
Creating panel data, filling gaps between years and repeating the last value in the subsequent years using R
I have the following sample: I am trying to turn it into the following panel data: As you can see in the last image, I would like to repeat the values between years for the same country, and repeat the last value for the subsequent years until the year 2020.
You can use grid.expand to get the country / year combinations you want, then left_join the main data frame to this, and finally fill the missing data, ensuring you filter out any remaining NAs.
library(dplyr)
library(tidyr)
panel <- expand.grid(year = min(df$year):2020,
country = unique(df$country),
stringsAsFactors = FALSE) %>%
left_join(df) %>%
group_by(country) %>%
fill(c("id", "regioncode", "prespowl")) %>%
filter(!is.na(id)) %>%
as.data.frame()
Which gives the following result:
panel
#> year country id regioncode prespowl
#> 1 2011 Albania 1 Europe 0.1817557
#> 2 2012 Albania 1 Europe 0.1817557
#> 3 2013 Albania 1 Europe 0.1817557
#> 4 2014 Albania 1 Europe 0.1817557
#> 5 2015 Albania 1 Europe 0.1817557
#> 6 2016 Albania 1 Europe 0.1817557
#> 7 2017 Albania 1 Europe 0.1817557
#> 8 2018 Albania 1 Europe 0.1411482
#> 9 2019 Albania 1 Europe 0.1411482
#> 10 2020 Albania 1 Europe 0.1411482
#> 11 2016 Algeria 2 Africa 0.3837466
#> 12 2017 Algeria 2 Africa 0.3837466
#> 13 2018 Algeria 2 Africa 0.4837466
#> 14 2019 Algeria 2 Africa 0.4837466
#> 15 2020 Algeria 2 Africa 0.4837466
#> 16 1999 Argentina 3 Americas 0.2887138
#> 17 2000 Argentina 3 Americas 0.2887138
#> 18 2001 Argentina 3 Americas 0.2887138
#> 19 2002 Argentina 3 Americas 0.2887138
#> 20 2003 Argentina 3 Americas 0.2887138
#> 21 2004 Argentina 3 Americas 0.2887138
#> 22 2005 Argentina 3 Americas 0.2887138
#> 23 2006 Argentina 3 Americas 0.4322523
#> 24 2007 Argentina 3 Americas 0.4322523
#> 25 2008 Argentina 3 Americas 0.4322523
#> 26 2009 Argentina 3 Americas 0.4322523
#> 27 2010 Argentina 3 Americas 0.4322523
#> 28 2011 Argentina 3 Americas 0.4322523
#> 29 2012 Argentina 3 Americas 0.4322523
#> 30 2013 Argentina 3 Americas 0.5453171
#> 31 2014 Argentina 3 Americas 0.5453171
#> 32 2015 Argentina 3 Americas 0.5453171
#> 33 2016 Argentina 3 Americas 0.5453171
#> 34 2017 Argentina 3 Americas 0.5453171
#> 35 2018 Argentina 3 Americas 0.5453171
#> 36 2019 Argentina 3 Americas 0.5453171
#> 37 2020 Argentina 3 Americas 0.5453171
Data used:
df <- read.table(text= 'country year id regioncode prespowl
Albania 2011 1 Europe 0.1817557
Albania 2018 1 Europe 0.1411482
Algeria 2016 2 Africa 0.3837466
Algeria 2018 2 Africa 0.4837466
Argentina 1999 3 Americas 0.2887138
Argentina 2006 3 Americas 0.4322523
Argentina 2013 3 Americas 0.5453171
', header = TRUE, stringsAsFactors = FALSE)
I have a dataset with columns: c(country, element, 1961, 1961flags, 1962, 1962 flags)
That goes on for until 2011. I know that 1961:2011 would assign all years in between, but is there a way to accommodate the separate flag column?
To be more specific, it is a csv file. I am reading in the data as
data <-read.csv("file",
col.names=(country, element, *would be 1961:2011 if there were no flag columns*), header=True)
You can use paste0 to generate the names.
col.names = c(country, element, paste0(rep(1961:2011, each=2), c("", "flags")))
the rep call will generate:
[1] 1961 1961 1962 1962 1963 1963 1964 1964 1965 1965 1966 1966 1967 1967 1968
[16] 1968 1969 1969 1970 1970 1971 1971 1972 1972 1973 1973 1974 1974 1975 1975
[31] 1976 1976 1977 1977 1978 1978 1979 1979 1980 1980 1981 1981 1982 1982 1983
[46] 1983 1984 1984 1985 1985 1986 1986 1987 1987 1988 1988 1989 1989 1990 1990
[61] 1991 1991 1992 1992 1993 1993 1994 1994 1995 1995 1996 1996 1997 1997 1998
[76] 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005
[91] 2006 2006 2007 2007 2008 2008 2009 2009 2010 2010 2011 2011
Note that I am using each and not times which would instead result in appending twice the sequence 1961:2011.
Creating a column with differences based on another column
I have a data frame that looks like this (simplified from 699 treaties):
TRT <- data.frame(T.ID=c(1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,8),
Treaty=c("hungary slovenia 1994", "hungary slovenia 1994",
"nicaragua taiwan 2006", "nicaragua taiwan 2006",
"ukraine uzbekistan 1994", "ukraine uzbekistan 1994",
"brazil uruguay 1986", "brazil uruguay 1986",
"albania macedonia 2002", "albania macedonia 2002",
"albania moldova 2003", "albania moldova 2003",
"albania romania 2003", "albania romania 2003",
"Treaty of Izmir 1977","Treaty of Izmir 1977",
"Treaty of Izmir 1977"),
sc.y=c("HUN1994", "SLV1994", "NIC2006", "TAW2006", "UKR1994",
"UZB1994", "BRA1986", "URU1986", "ALB2002", "MAC2002",
"ALB2003", "MLD2003", "ALB2003", "RUM2003", "IRN1977",
"TUR1977", "PAK1977"),
prom.demo=c(1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0),
polity=c(10,10,8,10,7,-9,7,9,7,9,7,8,7,8,-10,-7,9))
In the end, I want to have a data frame that lists each treaty only once, its value of the “prom.demo”-column and one column that contains the difference of the maximum and minimum among the “polity”-values of the contracting parties of each treaty (most treaties have only two contracting parties, but some have up to 51).
Is there any R command that spares me 699 calculations?
Using dplyr its a join on scode and year followed by grouping by Treaty and then working out the difference between the min and max polity:
require(dplyr)
left_join(treaties, Polity, c("scode","year")) %>% group_by(Treaty) %>% summarise(PolityDiff=max(polity,na.rm=TRUE)-min(polity,na.rm=TRUE))
Source: local data frame [8 x 2]
Treaty PolityDiff
1 albania macedonia 2002 2
2 albania moldova 2003 1
3 albania romania 2003 1
4 brazil uruguay 1986 2
5 hungary slovenia 1994 0
6 nicaragua taiwan 2006 2
7 Treaty of Izmir 1977 NA
8 ukraine uzbekistan 1994 16
The NA's are where you don't have any matching scode/year (The Treaty of Izmir is IRN/TUR/PAK in 1977, and none of those are in the Polity data).
Note that if you want NA if any one of the participating countries are not in the Polity data, use:
left_join(treaties, Polity, c("scode","year")) %>% group_by(Treaty) %>% summarise(PolityDiff=max(polity)-min(polity))
which gives:
Treaty PolityDiff
1 albania macedonia 2002 2
2 albania moldova 2003 1
3 albania romania 2003 1
4 brazil uruguay 1986 2
5 hungary slovenia 1994 NA
6 nicaragua taiwan 2006 2
7 Treaty of Izmir 1977 NA
8 ukraine uzbekistan 1994 16
because Slovenia is coded as SLV in Polity but there's SLO in the treaties - mistake? Anyway, there's no SLO/1994 in Polity so that treaty returns as NA in this variant. It returns zero in my first example because the NA gets dropped and the polity difference is the difference between one number and itself...