```{r}
top10_increses_rate <- murder_tiny %>%
  filter(state %in% total_change$state & change>=0)
top10_increses_rate
```

```{r}
p1 <- ggplot(top10_increses_rate,
             aes(x=reorder(state,change), y=change))+
      geom_col(aes(fill=city))+
      coord_flip()+
      labs(x="State", y="Number of Change", title = "Top 10 Murder Increses Rate in each State") +
      theme_minimal()
p1
```