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Home » Security Bloggers Network » Short Attention Span Theatre: Reproducing Axios’ “1 Big Thing” Google Trends 2019 News In Review with {ggplot2}

Short Attention Span Theatre: Reproducing Axios’ “1 Big Thing” Google Trends 2019 News In Review with {ggplot2}

by hrbrmstr on December 27, 2019

I woke up to Axios’ “1 Big Thing” ridgeline chart showing the crazy that was the 2019 news cycle:

and, I decided to reproduce it in {ggplot2}.

Getting The Data

First, I had to find the data. The Axios chart is interactive, so I assumed the visualization was built on-load. It was, but the data was embedded in a javascript file vs loaded as JSON via an XHR request:

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which was easy enough to turn into JSON anyone can use.

library(ggalt)library(hrbrthemes) # hrbrmstr/hrbrthemeslibrary(tidyverse)jsonlite::fromJSON("https://rud.is/dl/2019-axios-news.json") %>%   as_tibble() -> xdfxdf## # A tibble: 31 x 3##    name                    avg data      ##    <chr>                 <dbl> <list>    ##  1 Gov't shutdown        20.5  <int [51]>##  2 Mexico-U.S. border    22.8  <int [51]>##  3 Green New Deal        11.3  <int [51]>##  4 Blackface              9.61 <int [51]>##  5 N. Korea-Hanoi Summit 11.2  <int [51]>##  6 Boeing 737 Max         4.79 <int [51]>##  7 Brexit                28.5  <int [51]>##  8 Israel                42.1  <int [51]>##  9 SpaceX                24.1  <int [51]>## 10 Game of Thrones       16.8  <int [51]>## # … with 21 more rows

This is pretty tidy already, but we’ll need to expand the data column and give each week an index:

unnest(xdf, data) %>%   group_by(name) %>%   mutate(idx = 1:n()) %>%   ungroup() %>%   mutate(name = fct_inorder(name)) -> xdf # making a factor foe strip/panel ordering xdf## # A tibble: 1,581 x 4##    name             avg  data   idx##    <fct>          <dbl> <int> <int>##  1 Gov't shutdown  20.5    69     1##  2 Gov't shutdown  20.5   100     2##  3 Gov't shutdown  20.5    96     3##  4 Gov't shutdown  20.5   100     4##  5 Gov't shutdown  20.5    19     5##  6 Gov't shutdown  20.5     9     6##  7 Gov't shutdown  20.5    17     7##  8 Gov't shutdown  20.5     3     8##  9 Gov't shutdown  20.5     2     9## 10 Gov't shutdown  20.5     1    10## # … with 1,571 more rows

We’ll take this opportunity to find the first week of each month (via rle()) so we can have decent axis labels:

# get index placement for each month axis labelsprintf("2019-%02s-1", 1:51) %>%   as.Date(format = "%Y-%W-%w") %>%   format("%b") %>%   rle() -> monsmons## Run Length Encoding##   lengths: int [1:12] 4 4 4 5 4 4 5 4 5 4 ...##   values : chr [1:12] "Jan" "Feb" "Mar" "Apr" "May" "Jun" "Jul" "Aug" "Sep" "Oct" ...month_idx <- cumsum(mons$lengths)-3month_idx##  [1]  1  5  9 14 18 22 27 31 36 40 44 48

We’ve got all we need to make a {ggplot2} version of the chart. Here’s the plan:

use geom_area() and map colour and fill to avg (like Axios did), using an medium alpha value so we can still see below the overlapped areas
also use an xspline() stat with geom_area() so we get smooth lines vs pointy ones
use geom_hline() vs an axis line so we can map a colour aesthetic to avg as well
make a custom x-axis scale so we can place the labels we just made
expand the y-axis upper limit to avoid cutting off any part of the geoms
use the inferno viridis palette, but not the extremes of it
make facets/panels on the name, positioning the labels on the left
finally, tweak strip positioning so we get overlapped charts

ggplot(xdf, aes(idx, data)) +  geom_area(alpha = 1/2, stat = "xspline", aes(fill = avg, colour = avg)) +  geom_hline(    data = distinct(xdf, name, avg),    aes(yintercept = 0, colour = avg), size = 0.5  ) +  scale_x_continuous(    expand = c(0,0.125), limits = c(1, 51),    breaks = month_idx, labels = month.abb  ) +  scale_y_continuous(expand = c(0,0), limits = c(0, 105)) +  scale_colour_viridis_c(option = "inferno", direction = -1, begin = 0.1, end = 0.9) +  scale_fill_viridis_c(option = "inferno", direction = -1, begin = 0.1, end = 0.9) +  facet_wrap(~name, ncol = 1, strip.position = "left", dir = "h") +  labs(    x = NULL, y = NULL, fill = NULL, colour = NULL,    title = "1 big thing: The insane news cycles of 2019",    subtitle = "Height is search interest in a given topic, indexed to 100.\nColor is average search interest between Dec. 30, 2018–Dec. 20, 2019",    caption = "Source: Axios <https://www.axios.com/newsletters/axios-am-1d9cd913-6142-43b8-9186-4197e6da7669.html?chunk=0#story0>\nData: Google News Lab. Orig. Chart: Danielle Alberti/Axios"  ) +  theme_ipsum_es(grid="X", axis = "") +  theme(strip.text.y = element_text(angle = 180, hjust = 1, vjust = 0)) +  theme(panel.spacing.y = unit(-0.5, "lines")) +  theme(axis.text.y = element_blank()) +  theme(legend.position = "none")

To produce this finished product: