ggtimeline

ggtimeline allows you to create static timeline charts from time series data based on ggplot2 syntax. It is based off of Ben Alex Keen's work.

Getting Started

We'll use some data from the New York Times API as an example. We'll pull the last 10 results related to artificial intelligence:

nyt_data <- GET(paste0("https://api.nytimes.com/svc/search/v2/articlesearch.json?q=artificial%20intelligence&api-key=", Sys.getenv("NYT_KEY"))) %>%
    content(as = "text") %>%
    fromJSON(simplifyDataFrame = TRUE)

nyt_data2 <- nyt_data$response$docs

headlines <- nyt_data2$headline %>% select(main)
    
nyt_data3 <- nyt_data2 %>% 
    janitor::clean_names() %>% 
    bind_cols(headlines) %>% 
    mutate(pub_date = as.Date(lubridate::ymd_hms(pub_date)),
           abstract = str_wrap(abstract, 20),
           main_headline = str_wrap(main, 20)) %>% 
    arrange(desc(pub_date))

Note that it is highly recommended to use lubridate to edit your date column. I also edit the abstract and main headline columns with stringr::str_wrap so that the text for each timeline point can fit in the timeline.

ggtimeline(nyt_data3, date_col = "pub_date", title_col = "main_headline", color_col = "news_desk", time_span = "day", time_space = 5) +
    ggrepel::geom_text_repel(size = 3, vjust = 1) +
    theme_classic() +
    theme(axis.line.y=element_blank(),
          axis.text.y=element_blank(),
          axis.title.x=element_blank(),
          axis.title.y=element_blank(),
          axis.ticks.y=element_blank(),
          axis.text.x =element_blank(),
          axis.ticks.x =element_blank(),
          axis.line.x =element_blank(),
          legend.position = "bottom")

ggtimeline requires you to specify the columns in your dataframe related to the date (date_col), the title (title_col, the text that will actually be in your timeline). Specifying a column that contains groups for timeline point colors is optional. You are also optionally able to change the height positions of the points.

The time_span argument must be one of c("day", "month", "year"), while the time_space argument specifies the number of days, months, or years that aren't shown in between the days/months/years that are shown in the timeline.

Because this is based on ggplot2, you can add additional formatting changes with "+", just like you'd do for other ggplot visualizations.