---

---
title: "Assignment 8"
author: "Team Maitreyi"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    social: menu
    source_code: embed
---

------------------------------------------------------------------------

```{r setup, include=FALSE}
library(plotly)
library(flexdashboard)
library(dplyr)
library(ggplot2)
library(tidyr)
library("gtools")
```

### Imports Over Time

```{r}
trade <- read.csv('trade.csv')

trade$Countries <- as.character(trade$X)
View(trade)

set.seed(123)
sampled_trade <- trade %>%
  sample_n(500)  # Sample 500 observations for a clearer plot

trade_long <- trade %>%
  pivot_longer(
    cols = matches("^X19|^X20"),
    names_to = "Year",
    values_to = "Value"
  ) %>%
  mutate(Year = as.numeric(sub("X","", Year)))

View(trade_long)

aggregated_trade <- trade_long %>% 
  group_by(Year, Trade.Flow) %>%
  summarise(Mean_Value = mean(Value, na.rm = TRUE), .groups = 'drop')

p<-ggplot(aggregated_trade, aes(x = Year, y = Mean_Value, color = Trade.Flow)) +
  geom_line(size = 1) +
  geom_point() +
  labs(
    title = "Trade Trends Over Time",
    x = "Year",
    y = "Mean Trade Value",
    color = "Trade Flow"
  ) +
  theme_minimal()
ggplotly(p)
```

### SIPRI Time Series Data

```{r}
weapons <- read.csv('wpns.csv') 
set.seed(123456) 
sampled_weapons <- weapons %>% sample_n(100)

top_weaponstrade <- weapons %>% top_n(50, TIV.delivery.values)

q<-ggplot(sampled_weapons, aes(x = Delivery.year, y = Recipient, color = Supplier)) + geom_line(size = 1) + geom_point() + labs( title = "Arms Transfer Trends Over Time", x = "Year", y = "Recipient", color = "Supplier" ) + theme_minimal()
ggplotly(q)
```