Google Trends

1. This code will collect all of the Google searches under “psychologist”.

psychologist <- trendy("psychologist")

This code creates a line graph of the Google searches for “psychologist”.

psychologist %>%
  get_interest() %>% 
  ggplot(aes(x = date, y = hits)) +
  geom_line() +
  theme_minimal() +
  labs(title = "Google Searches for 'Psychologist' Over Time")

2. This code creates a line graph showing the monthly Google searches for the term “psychologist”.

psychologist %>%
  get_interest() %>% 
  mutate(month = month(date)) %>%           
  group_by(month) %>%                        
  summarize(hits_per_month = mean(hits)) %>%      
  ggplot(aes(x = month, y = hits_per_month)) +    
  geom_line() +
  scale_x_discrete(limits = c(1:12)) +
  theme_minimal() +
  labs(title = "Google Searches for 'Psychologist' By Month")

Continuous limits supplied to discrete scale.
Did you mean `limits = factor(...)` or `scale_*_continuous()`?

3. This code creates a data table of Google searches for “psychologist” by DMA, which means Designated Market Area.

psychologist %>%
  get_interest_dma() %>% 
  datatable()

NA

4. This code collects the data on Google searches for “psychologist” from both the United States and Canada from 2015 to 2020.

psychologist <- trendy("psychologist", geo = c("US", "CA"), from = "2015-01-01", to = "2020-01-01")

This code creates a line graph of the Google searches in each country and compares it by a monthly basis.

psychologist %>%
  get_interest() %>% 
  mutate(month = month(date)) %>%          
  group_by(month, geo) %>%                              
  summarize(hits_per_month = mean(hits)) %>%           
  ggplot(aes(x = month, y = hits_per_month, color = geo)) +       
  geom_line() +
  scale_x_discrete(limits = c(1:12)) +
  theme_minimal() +
  labs(title = "Internet searches for 'Psychologist' By Month and Country")

`summarise()` has grouped output by 'month'. You can override using the `.groups` argument.
Continuous limits supplied to discrete scale.
Did you mean `limits = factor(...)` or `scale_*_continuous()`?

5. This code collects the data for Google searches for both the term “psychologist” and “psychiatrist”.

psychs <- trendy(c("psychologist", "psychiatrist"))

This creates a line graph of the Google searches between “psychology” and “psychiatrist” and compares them over time.

psychs %>%
  get_interest() %>%
  ggplot(aes(x = date, y = hits, color = keyword)) +
  theme_minimal() +
  geom_line() +
  labs(title = "Searches for 'Psychologist' and 'Psychiatrist' Over Time")

6. This code gathers the information from Google images for the terms “psychologist” and “psychiatrist”.

psych_images <- trendy(c("psychologist", "psychiatrist"), gprop = "images")

This code organizes the the Google images information into a line graph comparing the two terms over time.

psych_images %>%
  get_interest() %>% 
  ggplot(aes(x = date, y = hits, color = keyword)) +       
  geom_line() +
  theme_minimal() +
  labs(title = "Image Searches for 'Psychologist' and 'Psychiatrist' Over Time")