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+---
+title: "syphilis traffic"
+output: html_document
+date: "2024-11-19"
+---
+
+```{r}
+
+library(ggplot2)
+library(dplyr)
+
+posts_per_year = syphilisall %>%
+  filter(!is.na(Year) & Year != 2021) %>%
+  group_by(Year) %>%
+  summarise(Number_of_Posts = n())
+
+ggplot(posts_per_year, aes(x = Year, y = Number_of_Posts)) +
+  geom_line() + 
+  geom_point() +  
+  labs(title = "Volume of Syphilis Traffic Over Time",
+       x = "Year",
+       y = "Number of Posts Across All of Reddit")
+
+
+```
+
+
+
+```{r}
+
+sum(is.na(syphilisall$Year))
+sum(syphilisall$Year == "")
+
+```
+
+
+
+```{r}
+
+posts_per_year = syphilisall %>%
+  filter(!is.na(Year) & Year != 2021) %>%  # Exclude NA values and 2021
+  group_by(Year, subreddit) %>%            # Group by both 'Year' and 'subreddit'
+  summarise(Number_of_Posts = n(), .groups = "drop")  # Count the number of posts per subreddit and year
+
+# Plotting the result
+ggplot(posts_per_year, aes(x = Year, y = Number_of_Posts, color = subreddit)) +
+  geom_line(aes(group = subreddit)) +   # Draw a line for each subreddit
+  geom_point() +                        # Add points for each year/subreddit combination
+  theme(legend.position="none") +
+  labs(title = "Volume of Syphilis Traffic Over Time",
+       x = "Year",
+       y = "Number of Posts per Subreddit")
+
+```
+
+```{r}
+
+unique_values = unique(syphilisall$subreddit)
+
+length(unique_values)
+
+```
+
+```{r}
+
+top_subreddits = syphilisall %>%
+  filter(!is.na(Year) & Year != 2021) %>%
+  group_by(subreddit) %>%
+  summarise(total_posts = n(), .groups = "drop") %>%
+  top_n(10, total_posts) 
+
+posts_per_year = syphilisall %>%
+  filter(subreddit %in% top_subreddits$subreddit, !is.na(Year) & Year != 2021) %>%
+  group_by(Year, subreddit) %>%
+  summarise(Number_of_Posts = n(), .groups = "drop")
+
+ggplot(posts_per_year, aes(x = Year, y = Number_of_Posts, color = subreddit)) +
+  geom_line(aes(group = subreddit)) + 
+  geom_point() +  
+  labs(title = "Volume of Syphilis Traffic Over Time",
+       x = "Year",
+       y = "Number of Posts per Subreddit")
+
+```
+
+
+```{r}
+
+sum(is.na(syphilisall$subreddit)) 
+
+sum(syphilisall$subreddit == "")
+
+
+```
+
+
+```{r}
+
+top_subreddits = syphilisall %>%
+  filter(!is.na(Year) & Year != 2021, subreddit != "") %>%
+  group_by(subreddit) %>%
+  summarise(total_posts = n(), .groups = "drop") %>%
+  top_n(10, total_posts) 
+
+posts_per_year = syphilisall %>%
+  filter(subreddit %in% top_subreddits$subreddit, !is.na(Year) & Year != 2021) %>%
+  group_by(Year, subreddit) %>%
+  summarise(Number_of_Posts = n(), .groups = "drop")
+
+ggplot(posts_per_year, aes(x = Year, y = Number_of_Posts, color = subreddit)) +
+  geom_line(aes(group = subreddit)) + 
+  geom_point() +  
+  labs(title = "Volume of Syphilis Traffic Over Time in Top Ten Subreddits",
+       x = "Year",
+       y = "Number of Posts per Subreddit")
+
+```
+
+
+```{r}
+
+top_subreddits = syphilistotal %>%
+  filter(!is.na(Year) & Year != 2021) %>%
+  group_by(subreddit) %>%
+  summarise(total_posts = n(), .groups = "drop") %>%
+  top_n(10, total_posts) 
+
+posts_per_year = syphilistotal %>%
+  filter(subreddit %in% top_subreddits$subreddit, !is.na(Year) & Year != 2021) %>%
+  group_by(Year, subreddit) %>%
+  summarise(Number_of_Posts = n(), .groups = "drop")
+
+ggplot(posts_per_year, aes(x = Year, y = Number_of_Posts, color = subreddit)) +
+  geom_line(aes(group = subreddit)) + 
+  geom_point() +  
+  labs(title = "Volume of Syphilis Traffic Over Time",
+       x = "Year",
+       y = "Number of Posts per Subreddit")
+
+```
+
+