---
title: "AirBNB Dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source_code: embed
---

```{r setup, include=FALSE}
library(tidyverse)
library(p8105.datasets)
library(flexdashboard)
library(ggridges)
library(plotly)
```

```{r, include = FALSE}
ny_noaa
ny_noaa_df<-
  ny_noaa %>%
  janitor::clean_names() %>% 
  separate(date,into = c("year","month","day"),sep = '-',convert = TRUE) %>% 
  mutate(
    month=month.abb[month],
    prcp=prcp/10,
    tmax=as.numeric(tmax)/10,
    tmin=as.numeric(tmin)/10
  ) %>% 
  select(id,year,month,day,everything())
```

Column {data-width=650}
-----------------------------------------------------------------------------------

### Boxplot of tmin cross every year 

```{r}
ny_noaa_df %>% 
  filter(month=="Jan") %>% 
  group_by(id,year,month) %>% 
  summarize(mean_tmin=mean(tmin)) %>% 
  plot_ly(x=~year,y=~mean_tmin,color = ~year,type = "box")
```

Column {data-width=350}
-----------------------------------------------------------------------------------

### tmax vs tmin for the full dataset

```{r}
tmax_tmin_plot<-
  ny_noaa_df%>% 
  ggplot(aes(x=tmax,y=tmin))+
  geom_hex()+
  labs(
    x="tmax (degree C)",
    y="tmin (degree C)",
    title = "tmax vs tmin for the full dataset",
    caption="Data from ny_noaa"
  )

ggplotly(tmax_tmin_plot)
```

### Scatterplot for station with observation times >8 for snowfall >150 mm

```{r}
scatterplot_snow<-  
ny_noaa_df %>%
  mutate(year=as.factor(year)) %>% 
  filter(snow>=150 & year %in% c("2008","2010")) %>%
  group_by(id,year) %>% 
  summarize(n_obs=n()) %>%
  filter(n_obs>8) %>%
  mutate(id=fct_reorder(id,n_obs)) %>% 
  ggplot(aes(x=id,y=n_obs))+
  geom_col(aes(fill=year))+
  theme(axis.text.x = element_text(angle = 90, hjust = 0.5, vjust = 0.5))

ggplotly(scatterplot_snow)


```