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JohnCoene avatar JohnCoene commented on May 23, 2024 1

I think I came up with a reasonable solution. Use the functions as you would before, however, extract the year from the dates to plot then group the data by

dates <- seq.Date(as.Date("2017-01-01"), as.Date("2018-12-31"), by = "day")
values <- rnorm(length(dates), 20, 6)

year <- data.frame(date = dates, values = values)

year %>% 
  dplyr::mutate(year = format(date, "%Y")) %>% 
  dplyr::group_by(year) %>% 
  e_charts(date) %>% 
  e_calendar(range = "2017",top="40") %>% 
  e_calendar(range = "2018",top="260") %>% 
  e_heatmap(values, coord.system = "calendar") %>% 
  e_visual_map(max = 30) %>% 
  e_title("Calendar", "Heatmap")%>%
  e_tooltip("item")

If you lay the calendars before running e_heatmap then the function will apply the data to its corresponding calendar, however if you add the calendars (e_calendar) afterwards then you will have to specify the index of calendar index (as in the previous example).

dates <- seq.Date(as.Date("2017-01-01"), as.Date("2018-12-31"), by = "day")
values <- rnorm(length(dates), 20, 6)

year <- data.frame(date = dates, values = values)

year %>% 
  dplyr::mutate(year = format(date, "%Y")) %>% 
  dplyr::group_by(year) %>% 
  e_charts(date) %>% 
  e_heatmap(values, coord.system = "calendar", 
    calendar = c(0 ,1)  # pass calendar indices
  ) %>% 
  e_calendar(range = "2017",top="40") %>% 
  e_calendar(range = "2018",top="260") %>% 
  e_visual_map(max = 30) %>% 
  e_title("Calendar", "Heatmap")%>%
  e_tooltip("item")

Let me know if that works for you.

from echarts4r.

JohnCoene avatar JohnCoene commented on May 23, 2024

The API for the heatmap/calendar is a bit clunky, I'll work on improving that. The solution to what you want to achieve is over at #31.

from echarts4r.

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