Merge branch 'main' into doris

map.html

@@ -0,0 +1 @@
+

map.qmd

@@ -191,3 +191,198 @@ fig <- subplot(violence_map,
 fig
 
 ```
+=======
+---
+title: "Final Project"
+author: "Ziwen Lu, Xuyan Xiu, Doris Yan"
+format: html
+editor: visual
+execute: 
+  warning: false
+embed-resources: true
+---
+
+```{r load libraries, echo=FALSE}
+library(haven)
+library(here)
+library(tidyverse)
+library(icpsrdata)
+library(plotly)
+dir.create("data")
+```
+
+# Reproducible data retrieval
+
+```{r}
+options("icpsr_email" = "dy212@georgetown.edu", "icpsr_password" = "Fbp9nbmKreLsubd8nL5H")
+```
+
+## crime
+
+```{r}
+# takes 1-2 mins
+icpsr_download(
+  file_id = 38649,
+  download_dir = here("data")
+)
+
+crime<-read_dta(here("data","ICPSR_38649","DS0001","38649-0001-Data.dta"))
+```
+
+# Clean data
+
+## crime
+
+```{r}
+# crime data
+crime_data<-crime|>
+  rename_all(tolower)|>
+  rename(county=stcofips)|>
+  mutate(viol = murder+rape+robbery+agasslt)|>
+  mutate(property = burglry+larceny+mvtheft)|>
+  select(county,year,viol,property)
+
+attr(crime_data$viol, "label")<-"Total violent crimes reported (MURDER + RAPE + ROBBERY + AGASSLT)"
+
+attr(crime_data$property, "label")<-"Total property crimes reported (BURGLRY + LARCENY + MVTHEFT)"
+
+```
+
+
+```{r}
+
+# Extract state-level FIPS codes (first two digits of county FIPS codes)
+
+crime_data$state_fips <- 
+  substr(crime_data$county, 
+         1, 2)
+
+state_fips_to_abb <- 
+  tibble(
+  state_fips = c("01", "02", "04", "05", "06", 
+                 "08", "09", "10", "11", "12", 
+                 "13", "15", "16", "17", "18", 
+                 "19", "20", "21", "22", "23", 
+                 "24", "25", "26", "27", "28", 
+                 "29", "30", "31", "32", "33", 
+                 "34", "35", "36", "37", "38", 
+                 "39", "40", "41", "42", "44", 
+                 "45", "46", "47", "48", "49", 
+                 "50", "51", "53", "54", "55", "56"),
+  state_abb = c("AL", "AK", "AZ", "AR", "CA", "CO", 
+                "CT", "DE", "DC", "FL", "GA", "HI", 
+                "ID", "IL", "IN", "IA", "KS", "KY", 
+                "LA", "ME", "MD", "MA", "MI", "MN", 
+                "MS", "MO", "MT", "NE", "NV", "NH", 
+                "NJ", "NM", "NY", "NC", "ND", "OH", 
+                "OK", "OR", "PA", "RI", "SC", "SD", 
+                "TN", "TX", "UT", "VT", "VA", "WA", 
+                "WV", "WI", "WY")
+)
+
+```
+
+## Map
+
+```{r}
+
+# Convert county-level data to state-level data, aggregate violent crime data
+
+crime_data_map <- crime_data |>
+  group_by(state_fips) |>
+  summarise(
+    total_violence = sum(viol, 
+                         na.rm = TRUE),
+    total_property = sum(property, 
+                         na.rm = TRUE)  
+  ) |>
+  
+  left_join(state_fips_to_abb, 
+            by = 'state_fips') |>
+  
+  mutate(
+    hover_violence = paste(state_abb, 
+                           '<br>', 
+                           "Total Violent Crimes: ", 
+                           total_violence),
+    hover_property = paste(state_abb, 
+                           '<br>', 
+                           "Total Property Crimes: ", 
+                           total_property)  
+  ) |>
+  
+  pivot_longer(
+    cols = c(total_violence, 
+             total_property),
+    names_to = "crime_type",
+    values_to = "crime_count"
+  )
+
+```
+
+```{r}
+
+# Create and output the map for total violence
+
+violence_map <- 
+  plot_geo(crime_data_map |>
+             filter(crime_type == "total_violence"),
+           locationmode = 'USA-states') |>
+  
+  add_trace(
+    z = ~crime_count, 
+    text = ~hover_violence,  
+    hoverinfo = 'text',     
+    locations = ~state_abb,
+    color = ~crime_count,
+    colors = c("#1a9641", "#ffffbf", "#fdae61", "#d7191c"),
+    colorbar = list(title = "Total Violent Crimes (million)")
+  ) |>
+  
+  layout(
+    title = 'US Crimes by State, 2009 - 2014',
+    geo = list(
+      scope = 'usa',
+      projection = list(type = 'albers usa'),
+      showlakes = TRUE,
+      lakecolor = toRGB('white')
+    )
+  )
+
+# Create and output the map for total property
+
+property_map <- 
+  plot_geo(crime_data_map |>
+             filter(crime_type == "total_property"),
+           locationmode = 'USA-states') |>
+  
+  add_trace(
+    z = ~crime_count, 
+    text = ~hover_property,   
+    hoverinfo = 'text',       
+    locations = ~state_abb,
+    color = ~crime_count,
+    colors = c("#2b83ba", "#ffffbf", "#fdae61", "#d7191c"),
+    colorbar = list(title = "Total Property Crimes (million)")
+  ) |>
+  
+  layout(
+    title = 'US Crimes by State, 2009 - 2014',
+    geo = list(
+      scope = 'usa',
+      projection = list(type = 'albers usa'),
+      showlakes = TRUE,
+      lakecolor = toRGB('white')
+    )
+  )
+
+# Place the two maps side by side in a stacked layout
+fig <- subplot(violence_map, 
+               property_map, 
+               nrows = 2, 
+               margin = 0.05) 
+
+# Print the figure
+fig
+
+```