We will use plotly to plot “emissions” data set, which is listing GDP, GDP per capita, and CO2 emissions for 1999.
data(emissions)
summary(emissions)
## GDP perCapita CO2
## Min. : 59900 Min. : 2507 Min. : 54.0
## 1st Qu.: 123100 1st Qu.:13393 1st Qu.: 77.0
## Median : 206250 Median :20993 Median : 200.0
## Mean : 830427 Mean :17724 Mean : 669.4
## 3rd Qu.: 683500 3rd Qu.:22250 3rd Qu.: 547.5
## Max. :8083000 Max. :29647 Max. :6750.0
countryName <- rownames(emissions)
em <- cbind(countryName, emissions)
rownames(em) <- NULL
em
## countryName GDP perCapita CO2
## 1 UnitedStates 8083000 29647 6750
## 2 Japan 3080000 24409 1320
## 3 Germany 1740000 21197 1740
## 4 France 1320000 22381 550
## 5 UnitedKingdom 1242000 21010 675
## 6 Italy 1240000 21856 540
## 7 Russia 692000 4727 2000
## 8 Canada 658000 21221 700
## 9 Spain 642400 16401 370
## 10 Australia 394000 20976 480
## 11 Netherlands 343900 21755 240
## 12 Poland 280700 7270 400
## 13 Belgium 236300 23208 145
## 14 Sweden 176200 19773 75
## 15 Austria 174100 21390 80
## 16 Switzerland 172400 23696 54
## 17 Portugal 149500 15074 75
## 18 Greece 137400 12833 125
## 19 Ukraine 124900 2507 420
## 20 Denmark 122500 22868 75
## 21 Norway 120500 27149 56
## 22 Romania 114200 5136 160
## 23 CzechRepublic 111900 10885 150
## 24 Finland 102100 19793 76
## 25 Hungary 73200 7186 85
## 26 Ireland 59900 16488 63
You can also embed plots, for example:
p <- plot_ly(em, x = ~countryName, y = ~GDP/100, type = 'bar', name = 'GDP') %>%
add_trace(y = ~perCapita, name = 'perCapita') %>%
add_trace(y = ~em$CO2, name = 'CO2') %>%
layout(yaxis = list(title = " GDP - Per Capita- CO2 emissions"), barmode = 'stack', autosize = F, width = 700, height = 700)
## Warning: Specifying width/height in layout() is now deprecated.
## Please specify in ggplotly() or plot_ly()
p