Merge branch 'master' of github.com:CommunityDataScienceCollective/COVID-19_Digital_O...

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diff --git a/keywords/analysis/related_searches_tidyverse_example.R b/keywords/analysis/related_searches_tidyverse_example.R
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+### COVID-19 Digital Observatory
+### 2020-03-28
+### 
+### Minimal example analysis file using trending search data
+
+library(tidyverse)
+
+### Import and cleanup data
+
+
+related.searches.top = read_csv("https://github.com/CommunityDataScienceCollective/COVID-19_Digital_Observatory/raw/master/keywords/output/intermediate/related_searches_top.csv")
+
+
+## Plot how often the top 10 queries appear in the top 10 suggested list each day
+
+plot <- related.searches.top %>% 
+  group_by(term, date) %>% # Group by term and date
+  arrange(-value) %>% # Sort by value (this should already be done anyway)
+  top_n(10) %>% # Get the top 10 queries for each term-day pair
+  group_by(query) %>% # Group by again, this time for each query
+  summarize(appearances = n()) %>% # Count how often this query appears in the top 10 (which is how many Google displays)
+  arrange(-appearances) %>% # Sort by appearances
+  top_n(10) %>% # And get the top 10 queries
+  ggplot(aes(x=reorder(query, appearances), y=appearances)) + # Plot the number of appearances, ordered by appearances
+  geom_bar(stat = 'identity') + # Tell R that we want to use the values of `appearances` as the counts
+  coord_flip() + # Flip the plot
+  xlab("Query") + 
+  ylab("Number of appearances in top 10 suggested queries") +
+  theme_minimal() # And make it minimal
+
+ggsave('./output/top_queries_plot.png', plot)
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