---
title: "Soc-Ace: POLECAT Data Analysis [V3]"
author: Gagan Atreya
date: today
format:
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toc: true
toc-location: left
toc-depth: 4
theme: lumen
fontsize: large
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---
# **Section 1. POLECAT Events By Country: 2020 - 2023**
## **1.1 Breakdown of Events by Country**
```{r, error = F, warning = F, message = F}
## Gagan Atreya
## POLECAT Analysis
rm(list = ls())
pacman::p_load(data.table, tidyverse, lubridate,
vtable, stringi, stringr, ggcharts, plyr,
gridExtra, RgoogleMaps, ggmap, mapproj)
df_2020 <- as.data.table(read.delim("~/Desktop/soc_ace_2024/data/polecat/ngecEvents.DV.2020.txt"))
df_2021 <- as.data.table(read.delim("~/Desktop/soc_ace_2024/data/polecat/ngecEvents.DV.2021.txt"))
df_2022 <- as.data.table(read.delim("~/Desktop/soc_ace_2024/data/polecat/ngecEvents.DV.2022.txt"))
df_2023 <- as.data.table(read.delim("~/Desktop/soc_ace_2024/data/polecat/ngecEvents.DV.2023.txt"))
df <- rbindlist(list(df_2020, df_2021, df_2022, df_2023))
country_list <- c("BLR", "GEO", "KAZ",
"POL", "RUS", "UKR")
df01 <- df[df$Country %in% country_list, ]
df <- df01
rm(list = setdiff(ls(), c("df")))
table(df$Country)
df$Year <- year(df$Event.Date)
table(df$Year)
## Register stadiamaps api:
ggmap::register_stadiamaps(key = "ecb62ab3-c884-4be1-9e19-4a49f5f8bed0")
```
# **Section 5. Maps: Poland**
## **5.1. Poland: arrests**
```{r, error = F, message = F, warning = F}
dfpol <- df[df$Country == "POL", ]
dfpol <- dfpol[dfpol$Event.Mode == "arrest", ]
dfpol$Latitude <- as.numeric(dfpol$Latitude)
dfpol$Longitude <- as.numeric(dfpol$Longitude)
dfpol$Event_count <- 1
df01 <- ddply(dfpol,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
mapoutline <- get_map(location = c(left = 13.50, # lon min
bottom = 48.50, # lat min
right = 24.75, # lon max
top = 55.00), # lat max
maptype = "outdoors",
source = "stadia",
color="bw")
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = df01,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Poland, 2020 - 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **5.2. Poland: arrests per year**
### Table:
```{r, error = F, message = F, warning = F}
dfpol20 <- dfpol[dfpol$Year == "2020", ]
dfpol21 <- dfpol[dfpol$Year == "2021", ]
dfpol22 <- dfpol[dfpol$Year == "2022", ]
dfpol23 <- dfpol[dfpol$Year == "2023", ]
table(dfpol$Year)
```
### Maps:
```{r, error = F, message = F, warning = F}
dfpol20 <- ddply(dfpol20,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfpol21 <- ddply(dfpol21,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfpol22 <- ddply(dfpol22,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfpol23 <- ddply(dfpol23,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfpol20,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Poland, 2020"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfpol21,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Poland, 2021"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfpol22,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Poland, 2022"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfpol23,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Poland, 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **5.3. Poland: illegal drugs**
```{r, error = F, message = F, warning = F}
dfpol <- df[df$Country == "POL", ]
dfpol$drugs <- ifelse(str_detect(dfpol$Contexts, "illegal_drugs") == T, 1, 0)
dfpol <- dfpol[dfpol$drugs == 1, ]
dfpol$Longitude <- as.numeric(dfpol$Longitude)
dfpol$Latitude <- as.numeric(dfpol$Latitude)
dfpol$Event_count <- 1
df01 <- ddply(dfpol,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = df01,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Poland, 2020 - 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **5.4. Poland: illegal_drugs per year**
### Table:
```{r, error = F, message = F, warning = F}
dfpol20 <- dfpol[dfpol$Year == "2020", ]
dfpol21 <- dfpol[dfpol$Year == "2021", ]
dfpol22 <- dfpol[dfpol$Year == "2022", ]
dfpol23 <- dfpol[dfpol$Year == "2023", ]
table(dfpol$Year)
```
### Maps:
```{r, error = F, message = F, warning = F}
dfpol20 <- ddply(dfpol20,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfpol21 <- ddply(dfpol21,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfpol22 <- ddply(dfpol22,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfpol23 <- ddply(dfpol23,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfpol20,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Poland, 2020"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfpol21,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("vent contexts tagged as illegal_drugs in Poland, 2021"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfpol22,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("vent contexts tagged as illegal_drugs in Poland, 2022"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfpol23,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("vent contexts tagged as illegal_drugs in Poland, 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
# **Section 6. Maps: Russia**
## **6.1. Russia: arrests**
```{r, error = F, message = F, warning = F}
dfrus <- df[df$Country == "RUS", ]
dfrus <- dfrus[dfrus$Event.Mode == "arrest", ]
dfrus$Latitude <- as.numeric(dfrus$Latitude)
dfrus$Longitude <- as.numeric(dfrus$Longitude)
dfrus$Event_count <- 1
df01 <- ddply(dfrus,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
mapoutline <- get_map(location = c(left = 20.00, # lon min
bottom = 42.00, # lat min
right = 160.00, # lon max
top = 78.00), # lat max
maptype = "outdoors",
source = "stadia",
color="bw")
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = df01,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Russia, 2020 - 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **6.2. Russia: arrests per year**
### Table:
```{r, error = F, message = F, warning = F}
dfrus20 <- dfrus[dfrus$Year == "2020", ]
dfrus21 <- dfrus[dfrus$Year == "2021", ]
dfrus22 <- dfrus[dfrus$Year == "2022", ]
dfrus23 <- dfrus[dfrus$Year == "2023", ]
table(dfrus$Year)
```
### Maps:
```{r, error = F, message = F, warning = F}
dfrus20 <- ddply(dfrus20,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfrus21 <- ddply(dfrus21,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfrus22 <- ddply(dfrus22,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfrus23 <- ddply(dfrus23,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfrus20,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Russia, 2020"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfrus21,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Russia, 2021"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfrus22,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Russia, 2022"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfrus23,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Russia, 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **6.3. Russia: illegal drugs**
```{r, error = F, message = F, warning = F}
dfrus <- df[df$Country == "RUS", ]
dfrus$drugs <- ifelse(str_detect(dfrus$Contexts, "illegal_drugs") == T, 1, 0)
dfrus <- dfrus[dfrus$drugs == 1, ]
dfrus$Longitude <- as.numeric(dfrus$Longitude)
dfrus$Latitude <- as.numeric(dfrus$Latitude)
dfrus$Event_count <- 1
df01 <- ddply(dfrus,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = df01,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Russia, 2020 - 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **6.4. Russia: illegal_drugs per year**
### Table:
```{r, error = F, message = F, warning = F}
dfrus20 <- dfrus[dfrus$Year == "2020", ]
dfrus21 <- dfrus[dfrus$Year == "2021", ]
dfrus22 <- dfrus[dfrus$Year == "2022", ]
dfrus23 <- dfrus[dfrus$Year == "2023", ]
table(dfrus$Year)
```
### Maps:
```{r, error = F, message = F, warning = F}
dfrus20 <- ddply(dfrus20,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfrus21 <- ddply(dfrus21,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfrus22 <- ddply(dfrus22,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfrus23 <- ddply(dfrus23,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfrus20,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Russia, 2020"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfrus21,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Russia, 2021"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfrus22,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Russia, 2022"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfrus23,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Russia, 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
# **Section 7. Maps: Ukraine**
## **7.1. Ukraine: arrests**
```{r, error = F, message = F, warning = F}
dfukr <- df[df$Country == "UKR", ]
dfukr <- dfukr[dfukr$Event.Mode == "arrest", ]
dfukr$Latitude <- as.numeric(dfukr$Latitude)
dfukr$Longitude <- as.numeric(dfukr$Longitude)
dfukr$Event_count <- 1
df01 <- ddply(dfukr,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
mapoutline <- get_map(location = c(left = 21.00, # lon min
bottom = 43.00, # lat min
right = 41.00, # lon max
top = 54.00), # lat max
maptype = "outdoors",
source = "stadia",
color="bw")
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = df01,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Ukraine, 2020 - 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **7.2. Ukraine: arrests per year**
### Table:
```{r, error = F, message = F, warning = F}
dfukr20 <- dfukr[dfukr$Year == "2020", ]
dfukr21 <- dfukr[dfukr$Year == "2021", ]
dfukr22 <- dfukr[dfukr$Year == "2022", ]
dfukr23 <- dfukr[dfukr$Year == "2023", ]
table(dfukr$Year)
```
### Maps:
```{r, error = F, message = F, warning = F}
dfukr20 <- ddply(dfukr20,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfukr21 <- ddply(dfukr21,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfukr22 <- ddply(dfukr22,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfukr23 <- ddply(dfukr23,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfukr20,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Ukraine, 2020"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfukr21,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Ukraine, 2021"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfukr22,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Ukraine, 2022"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfukr23,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event mode tagged as arrests in Ukraine, 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **7.3. Ukraine: illegal drugs**
```{r, error = F, message = F, warning = F}
dfukr <- df[df$Country == "UKR", ]
dfukr$drugs <- ifelse(str_detect(dfukr$Contexts, "illegal_drugs") == T, 1, 0)
dfukr <- dfukr[dfukr$drugs == 1, ]
dfukr$Longitude <- as.numeric(dfukr$Longitude)
dfukr$Latitude <- as.numeric(dfukr$Latitude)
dfukr$Event_count <- 1
df01 <- ddply(dfukr,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = df01,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Ukraine, 2020 - 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
## **7.4. Ukraine: illegal_drugs per year**
### Table:
```{r, error = F, message = F, warning = F}
dfukr20 <- dfukr[dfukr$Year == "2020", ]
dfukr21 <- dfukr[dfukr$Year == "2021", ]
dfukr22 <- dfukr[dfukr$Year == "2022", ]
dfukr23 <- dfukr[dfukr$Year == "2023", ]
table(dfukr$Year)
```
### Maps:
```{r, error = F, message = F, warning = F}
dfukr20 <- ddply(dfukr20,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfukr21 <- ddply(dfukr21,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfukr22 <- ddply(dfukr22,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
dfukr23 <- ddply(dfukr23,
.(Latitude, Longitude),
summarize,
Event_count = sum(Event_count))
## Fill up the map with our data:
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfukr20,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Ukraine, 2020"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfukr21,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Ukraine, 2021"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfukr22,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Ukraine, 2022"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
map01 <- print(ggmap(mapoutline) +
geom_point(data = dfukr23,
aes(x = Longitude,
y = Latitude,
size = Event_count),
alpha = 0.5,
colour="black")+
ggtitle("Event contexts tagged as illegal_drugs in Ukraine, 2023"))+
theme_bw()+
theme(axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank())
```
