---
title: "ANLY512 - Lab2"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: fill
source_code: embed
---
```{r setup, include=FALSE}
library(flexdashboard)
library(quantmod)
library(plyr)
library(ggplot2)
library(maps)
library(dplyr)
library(ggalt)
gsom <- read.csv("gsom.csv")
cleanup <- theme(panel.grid.major = element_blank(), #no grid lines
panel.grid.minor = element_blank(), #no grid lines
panel.background = element_blank(), #no background
axis.line.x = element_line(color = 'black'), #black x axis line
axis.line.y = element_line(color = 'black'), #black y axis line
legend.key = element_rect(fill = 'white'), #no legend background
text = element_text(size = 15)) #bigger text size
```
## Stations Map {.storyboard data-orientation=rows data-icon="fa_list"}
### Data Sampling {data-height=150}
Randomly Sampled Global Summary of the Month Climatology data from 10 stations\
10 Stations across 10 States (5 from West and 5 from East)\
West: California, Nevada, Idaho, Oregon, Washington \
East: Connecticut, Massachusetts, North Carolina, New Jersey, Virginia\
\
### Stations Map {data-height=500}
```{r message=FALSE}
all_states <- map_data("state")
west <- all_states[all_states$region %in% c("california", "nevada", "idaho",
"oregon", "washington"), ]
east <- all_states[all_states$region %in% c("connecticut", "massachusetts", "north carolina",
"new jersey", "virginia"), ]
ggplot()+ geom_polygon(data=all_states,
aes(x=long, y=lat, group = group),
colour="black", fill="#eeeeee")+
geom_polygon(data = west,
aes(x=long, y=lat, group = group),
colour="black", fill="#7ff9e9")+
geom_polygon(data = east, aes(x=long, y=lat, group = group),
colour="black", fill="#fbb1b5")+
theme_void()+
cleanup
```
## Analysis {.tabset .tabset-fade}
### Precipitation {.storyboard data-orientation=rows data-icon="fa_list"}
#### Idea1 {data-height=150}
Precipitation is higher in the east sides compared with the west sides \
The variance of precipitation in the east side is much smaller \
\
#### Visulization {data-height=500}
```{r message=FALSE}
gsom$State <-factor(gsom$State, levels=c("CA", "ID", "NV", "OR", "WA",
"CT", "MA", "NC", "NJ", "VA"))
p <- ggplot(gsom, aes(x=reorder(State, Division), y=PRCP, colour = Division)) +
geom_jitter(width = 0.2, alpha = 0.25)+
geom_boxplot(alpha = 0.25, coef = 2.5)+
labs(x="State", y="Total Monthly Precipitation (inches)",
subtitle="Total Monthly Precipitation Box Plot across States")+
cleanup
p
```
### Temperature {.storyboard data-orientation=rows data-icon="fa_list"}
#### Idea2: {data-height=150}
The Temperature is keep increasing in both east and west sides\
East side has relatively higher temperature compared with the west side \
#### Visualization {data-height=150}
```{r message=FALSE}
gsom$DATE <- as.Date(paste0(gsom$DATE, '-01'), format="%Y-%m-%d")
gsom$YEAR <- format(gsom$DATE, "%Y")
gsom$YEAR <- as.Date(paste0(gsom$YEAR, '-01-01'), format="%Y-%m-%d")
gsom_year <- gsom %>% group_by(YEAR, Division) %>%
summarise(mean_temp=mean(TAVG, na.rm=TRUE))
P <- ggplot(gsom_year,
aes(x=gsom_year$YEAR, y=mean_temp, group=Division,
colour=Division))+
geom_line(size=0.7)+
geom_point()+
labs(x="Year", y="Yearly Average Temperature (Celsius)",
subtitle="Average Temperature Time Series across Divisions")+
cleanup
P
```
### Snowfall {.storyboard data-orientation=rows data-icon="fa_list"}
#### Idea3: {data-height=150}
The east side has heavier snowfall compared with the east side \
\
#### Visualization {data-height=500}
```{r message=FALSE}
gsom_snow_year <- gsom %>% group_by(YEAR, Division) %>%
summarise(tot_snow=sum(SNOW, na.rm=TRUE))
ggplot(gsom_snow_year,
aes(tot_snow, group=Division, fill=Division))+
geom_density(stat = "density", alpha=0.5)+
labs(x="Yearly Snowfall(inches)", y="Density",
subtitle="Yearly Snowfall Density across Divisions")+
cleanup
```
### Temperature Gap {.storyboard data-orientation=rows data-icon="fa_list"}
#### Idea4 {data-height=150}
OR has the narrowest gap between highest and the lowest temperature \
NV has the broadest gap between the highest and the lowest temperature \
\
#### Visualization {data-height=500}
```{r message=FALSE}
gsom_state_diff <- gsom[as.character(format(gsom$YEAR,'%Y'))=="2021", ] %>%
group_by(State) %>%
summarise(TMAX=max(TMAX, na.rm=TRUE),
TMIN=min(TMIN, na.rm=TRUE))
gsom_state_diff$diff <- gsom_state_diff$TMAX - gsom_state_diff$TMIN
p <- ggplot()+
# doing this vs y axis major grid line
geom_segment(data=gsom_state_diff,
aes(y=State, yend=State, x=-10, xend=40),
color="#b2b2b2", size=0.15)+
geom_dumbbell(data=gsom_state_diff,
aes(y=State, x=TMIN, xend=TMAX),
size=1.5, color="#b2b2b2",
point.size.l=3, point.size.r=3,
point.colour.l="#9fb059", point.colour.r="#edae52")+
geom_text(data=filter(gsom_state_diff, State=="VA"),
aes(x=TMIN, y=State, label="Min Temperature"),
color="#9fb059", size=3, vjust=-2,
fontface="bold", family="Calibri")+
geom_text(data=filter(gsom_state_diff, State=="VA"),
aes(x=TMAX, y=State, label="Max Temperature"),
color="#edae52", size=3, vjust=-2,
fontface="bold", family="Calibri")+
geom_text(data=gsom_state_diff,
aes(x=TMIN, y=State, label=TMIN),
color="#9fb059", size=2.75,
vjust=2.5, family="Calibri")+
geom_text(data=gsom_state_diff,
color="#edae52", size=2.75, vjust=2.5, family="Calibri",
aes(x=TMAX, y=State, label=TMAX))+
geom_rect(data=gsom_state_diff,
aes(xmin=42.05, xmax=42.175, ymin=-Inf, ymax=Inf),
fill="#efefe3")+
geom_text(data=gsom_state_diff,
aes(label=diff, y=State, x=42.1125),
fontface="bold", size=3, family="Calibri")+
geom_text(data=filter(gsom_state_diff, State=="VA"),
aes(x=42.1125, y=State, label="DIFF"),
color="#7a7d7e", size=3.1, vjust=-2,
fontface="bold", family="Calibri")+
scale_x_continuous(expand=c(0.075,0))+
scale_y_discrete(expand=c(0.1,0))+
labs(x=NULL, title="The 2021 Temperature across 10 States")+
theme_bw(base_family="Calibri")+
theme(panel.grid.major=element_blank())+
theme(panel.grid.minor=element_blank())+
theme(panel.border=element_blank())+
theme(axis.ticks=element_blank())+
theme(axis.text.x=element_blank())+
theme(plot.title=element_text(face="bold"))+
theme(plot.subtitle=element_text(face="italic",
size=9, margin=margin(b=12)))+
theme(plot.caption=element_text(size=7, margin=margin(t=12),
color="#7a7d7e"))
p
```
