Aliases: plotly_data groups.plotly ungroup.plotly group_by.plotly mutate.plotly do.plotly summarise.plotly arrange.plotly select.plotly filter.plotly distinct.plotly slice.plotly rename.plotly transmute.plotly group_by_.plotly mutate_.plotly do_.plotly summarise_.plotly arrange_.plotly select_.plotly filter_.plotly distinct_.plotly slice_.plotly rename_.plotly transmute_.plotly
Keywords:
### ** Examples # use group_by() to define groups of visual markings p <- txhousing %>% group_by(city) %>% plot_ly(x = ~date, y = ~sales) p
Warning: Ignoring 568 observations
Error in loadNamespace(name): there is no package called 'webshot'
# plotly objects preserve data groupings groups(p)
[[1]] city
plotly_data(p)
# A tibble: 8,602 × 9 city year month sales volume median listings inventory date <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 Abilene 2000 1 72 5380000 71400 701 6.3 2000 2 Abilene 2000 2 98 6505000 58700 746 6.6 2000. 3 Abilene 2000 3 130 9285000 58100 784 6.8 2000. 4 Abilene 2000 4 98 9730000 68600 785 6.9 2000. 5 Abilene 2000 5 141 10590000 67300 794 6.8 2000. 6 Abilene 2000 6 156 13910000 66900 780 6.6 2000. 7 Abilene 2000 7 152 12635000 73500 742 6.2 2000. 8 Abilene 2000 8 131 10710000 75000 765 6.4 2001. 9 Abilene 2000 9 104 7615000 64500 771 6.5 2001. 10 Abilene 2000 10 101 7040000 59300 764 6.6 2001. # … with 8,592 more rows
# dplyr verbs operate on plotly objects as if they were data frames p <- economics %>% plot_ly(x = ~date, y = ~unemploy / pop) %>% add_lines() %>% mutate(rate = unemploy / pop) %>% filter(rate == max(rate)) plotly_data(p)
# A tibble: 1 × 7 date pce pop psavert uempmed unemploy rate <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 1982-12-01 2162. 233160 10.9 10.2 12051 0.0517
add_markers(p)
Error in loadNamespace(name): there is no package called 'webshot'
layout(p, annotations = list(x = ~date, y = ~rate, text = "peak"))
Error in loadNamespace(name): there is no package called 'webshot'
# use group_by() + do() + subplot() for trellis displays d <- group_by(mpg, drv) plots <- do(d, p = plot_ly(., x = ~cty, name = ~drv)) subplot(plots[["p"]], nrows = 3, shareX = TRUE)
Error in loadNamespace(name): there is no package called 'webshot'
# arrange displays by their mean means <- summarise(d, mn = mean(cty, na.rm = TRUE)) means %>% dplyr::left_join(plots) %>% arrange(mn) %>% subplot(nrows = NROW(.), shareX = TRUE)
Error in loadNamespace(name): there is no package called 'webshot'
# more dplyr verbs applied to plotly objects p <- mtcars %>% plot_ly(x = ~wt, y = ~mpg, name = "scatter trace") %>% add_markers() p %>% slice(1) %>% plotly_data()
# A tibble: 1 × 11
mpg cyl disp hp drat wt qsec vs am gear carb
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
p %>% slice(1) %>% add_markers(name = "first observation")
Error in loadNamespace(name): there is no package called 'webshot'
p %>% filter(cyl == 4) %>% plotly_data()
# A tibble: 11 × 11
mpg cyl disp hp drat wt qsec vs am gear carb
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
2 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
3 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
4 32.4 4 78.7 66 4.08 2.2 19.5 1 1 4 1
5 30.4 4 75.7 52 4.93 1.62 18.5 1 1 4 2
6 33.9 4 71.1 65 4.22 1.84 19.9 1 1 4 1
7 21.5 4 120. 97 3.7 2.46 20.0 1 0 3 1
8 27.3 4 79 66 4.08 1.94 18.9 1 1 4 1
9 26 4 120. 91 4.43 2.14 16.7 0 1 5 2
10 30.4 4 95.1 113 3.77 1.51 16.9 1 1 5 2
11 21.4 4 121 109 4.11 2.78 18.6 1 1 4 2
p %>% filter(cyl == 4) %>% add_markers(name = "four cylinders")
Error in loadNamespace(name): there is no package called 'webshot'