---
title: Raster Data
week: 6
type: Case Study
subtitle: The hottest country on each continent.
reading:
- Raster Vector Interactions [GCR](https://geocompr.robinlovelace.net/geometric-operations.html#raster-vector){target='blank'}
tasks:
- Download daily weather data for Buffalo, NY using an API
- Generate a dynamic html visualization of the timeseries.
---
```{r setup, include=FALSE, purl=F}
source("functions.R")
source("knitr_header.R")
```
# Reading
```{r reading,results='asis',echo=F,purl=F}
md_bullet(rmarkdown::metadata$reading)
```
# Tasks
```{r tasks,results='asis',echo=F, purl=F}
md_bullet(rmarkdown::metadata$tasks)
```
## Background
# Objective
> Make a dygraph of recent daily maximum temperature data from Buffalo, NY.
## Detailed Steps
First use the following code to download the daily weather data.
```{r, messages=F, warning=F, results=F}
library(rnoaa)
library(xts)
library(dygraphs)
library(htmlwidgets)
d=meteo_tidy_ghcnd("USW00014733",
date_min = "2016-01-01",
var = c("TMAX"),
keep_flags=T)
d$date=as.Date(d$date)
```
Remaining steps:
1. Convert `d` into an `xts` time series object using `xts()`. You will need to specifify which column has the data (`d$tmax`) and `order.by=d$date`. See `?xts` for help.
2. Use `dygraph()` to draw the plot
3. Set the title of the dygraph to be `main="Daily Maximum Temperature in Buffalo, NY"`
3. Add a `dyRangeSelector()` with a `dateWindow` of `c("2017-01-01", "2017-12-31")`
```{r, echo=F, purl=F, warning=F, message=F}
# Convert to a xts time series object as required by dygraph
dt=xts(d$tmax,order.by=d$date)
dygraph(dt, main = "Daily Maximum Temperature in Buffalo, NY") %>%
dyRangeSelector(dateWindow = c("2017-01-01", "2017-12-31"))%>%
frameWidget(height =500)
```