The dataset was used from here: https://www.kaggle.com/uciml/red-wine-quality-cortez-et-al-2009

The wine dataset has 12 variables with the 12th variable being the dependent, y variable.

library(plotly)

## Loading required package: ggplot2

## Registered S3 methods overwritten by 'ggplot2':
##   method         from 
##   [.quosures     rlang
##   c.quosures     rlang
##   print.quosures rlang

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
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##     layout

wine <- read.csv("winequality-red.csv")
p <- plot_ly(wine, x = ~quality, y = ~alcohol, type = 'box')

The dataset was taken from “https://www.kaggle.com/sogun3/uspollution” There appears to be seasonality every 12 months, the dataset observations were taken only from Houston for the first of the month for this project. Just used this dataset for my Time Series project this semester. This dataset was uploaded to plotly and it produced a time series.

library(plotly)
texas <- read.csv("Pollution.csv")
p <- plot_ly(texas, x = ~date, y = ~NO2.Mean, type = 'scatter', mode = 'markers')

##Texas Plot