This is a report on “r length(airquality$Temp)” temperature measurements.
The average Solar.R “r mean(airquality$Solar.R)”.
The average Wind “r mean(airquality$Wind)”.
This report was generated on “r format(Sys.Date(),format=”%B%d%Y").
Created by: Data Scientist at DAK consult.
Confidential: Highly
---
title: "Airquality Measurement in New York"
output:
flexdashboard::flex_dashboard:
theme: cerulean
orientation: rows
vertical_layout: fill
social: ["twitter","facebook","menu"]
source_code: embed
---
```{r setup, include=FALSE}
library(flexdashboard)
library(knitr)
library(DT)
library(rpivotTable)
library(ggplot2)
library(plotly)
library(dplyr)
library(openintro)
library(highcharter)
library(ggvis)
#read in data
library(datasets)
data(airquality)
#my colors
mycolors<-c("blue","#FFC125","darkgreen","darkorange")
```
Interactive Data Visualization
=======================================================================
Row {data-width=650}
-----------------------------------------------------------------------
### Airquality Analysis
```{r}
valueBox(paste("Temp"),color="cold")
```
### Temperature in New York
```{r}
valueBox(length(airquality$Month),icon="fa-user")
```
### Temperature Distribution
```{r}
gauge(airquality$Temp,
min=56,
max=97,
gaugeSectors(success=c(80,97),
warning=c(65,80),
danger=c(56,65),
colors=c("green","yellow","red")))
```
### Total Temp May
```{r}
valueBox(sum(subset(airquality$Temp,airquality$Month=="5")),icon="fa-user-times",color="orange")
```
### Total Temp June
```{r}
valueBox(sum(subset(airquality$Temp,airquality$Month=="6")),icon="fa-user-plus",color="yellow")
```
### Total Temp July
```{r}
valueBox(sum(subset(airquality$Temp,airquality$Month=="7")),icon="fa-user-times",color="lightgreen")
```
Row {data-width=350}
-----------------------------------------------------------------------
### Monthly Temperatures
```{r}
p1<-airquality%>%
group_by(Month)%>%
summarise(count=sum(Temp))%>%
plot_ly(x=~Month,
y=~count,
color="yellow",
type="bar")%>%
layout(xaxis=list(title="Month"),
yaxis=list(title="Count"))
p1
```
### Months with higher Temperatures
```{r}
p2<-airquality%>%
group_by(Month)%>%
summarise(count=mean(Temp))%>%
filter(count>75)%>%
plot_ly(labels=~Month,
values=~count,
marker=list(colors=mycolors))%>%
add_pie(hole=0.4)%>%
layout(xaxis=list(zeroline=F,showline=F,showticklabels=F,showgrid=F),
yaxis=list(zeroline=F,showline=F,showticklabels=F,showgrid=F))
p2
```
### Temp vs Solar.R
```{r}
p3<-plot_ly(airquality,
x=~Temp,y=~Solar.R,
test=paste("Temp:",airquality$Temp,
"Solar.R:",airquality$Solar.R),
type="bar")%>%
layout(xaxis=list(title="Temp"),yaxis=list(title="Solar.R"))
p3
```
### Scatterplot
```{r}
airquality <- airquality %>%
filter(!is.na(Solar.R))
fit<-lm(Solar.R~Temp,data=airquality)
p4<-plot_ly(airquality,x=airquality$Temp,y=airquality$Solar.R,type="scatter",mode="markers")%>%
layout(xaxis=list(title="Temp"),yaxis=list(title="Solar.R"))%>%
add_lines(x =airquality$Temp, y = fitted(loess(airquality$Solar.R~airquality$Temp)),
name="Loess Smoother",color="red",showlegend=T,line=list(2))
p4
```
Data Table
=======================================================================
```{r}
datatable(airquality,caption="Temp Data",rownames=T,filter="top",options=list(pageLength=25))
```
Pivot Table
========================================================================
```{r}
rpivotTable(airquality,
aggregatorName="Count",
cols="Temp",
rows="Month",
renderName="Heatmap")
```
Summary Report
========================================================================
Column(data-width=100)
------------------------------------------------------------------------
### Max Temp Month
```{r}
valueBox(max(airquality$Temp),icon="fa-user")
```
### Average Solar Radiation
```{r}
valueBox(max(airquality$Solar.R),icon="fa-area-chart")
```
### Average Wind
```{r}
valueBox(round(mean(airquality$Wind),digits=2),icon="fa-area-chart")
```
### Average Ozone
```{r}
valueBox(round(mean(airquality$Ozone,na.rm=TRUE),digits=2),icon="fa-area-chart")
```
Column
--------------------------------------------------------------------
### Report
* This is a report on "r length(airquality$Temp)" temperature measurements.
* The average Solar.R "r mean(airquality$Solar.R)".
* The average Wind "r mean(airquality$Wind)".
This report was generated on "r format(Sys.Date(),format="%B%d%Y").
Created by: Data Scientist at DAK consult.
Confidential: Highly