main features of the corpora

Natural language processing (NLP) was applied to English documents coming from Tweets, News and Blogs.

This project analyses the ToothGrowth data in the R datasets package. The structure of this analysis is as follows: 1. Basic exploratory data anlysis 2. Basic summary of the data 3. Use confidence intervals and/or hypothesis tests to compare tooth growth by supp and dose 4. Conclusion

This project investigated the exponential distribution in R and compare it with the Central Limit Theorem. The project sets lambda = 0.2 for all of the simulations. The distribution of averages of 40 exponentials was investigated. A thousand simulations were made.

Week 4 Assignment

Latest earthquakes as 2017-07-30 21:55:42 (UTC)

library(ggplot2) set.seed(100) d <- diamonds[sample(nrow(diamonds),1000),] p<- ggplot(data=d, aes(x=carat,y=price))+ geom_point(aes(text=paste("Clarity:", clarity)), size=4)+ geom_smooth(aes(colour=cut, fill=cut)) + facet_wrap( ~ cut) (gg<-ggplotly(p))

library(plotly) library(tidyr) library(dplyr) data("EuStockMarkets") stocks <- as.data.frame(EuStockMarkets) %>% gather(index, price) %>% mutate(time = rep(time(EuStockMarkets), 4)) plot_ly(stocks, x = ~time, y = ~price, color = ~index, type = "scatter", mode = "lines")

library(plotly) data("airmiles") plot_ly(x = ~time(airmiles), y = ~airmiles, type = "scatter", mode = "lines")

Plotly R API

The basic goal is to explore the NOAA Storm Database in relation severe weather events and answer the following questions: 1.Across the United States, which types of events (as indicated in the EVTYPE variable) are most harmful with respect to population health? 2.Across the United States, which types of events have the greatest economic consequences?

qplot(carat, price, data=diamonds, color=cut, facets=.~cut)+geom_smooth(method = "lm")

qplot(hwy, data=mpg, fill=drv)

qplot(drv, hwy,data=mpg,geom="boxplot", color=manufacturer)

qplot(displ,hwy,data=mpg, color=drv, geom=c("point","smooth"))

With strip=F xyplot(price~carat | color*cut, data=diamonds, pch=20, xlab=myxlab, ylab=myylab, main=mymain)

xyplot(price~carat | color*cut, data=diamonds, strip=FALSE, pch=20, xlab=myxlab, ylab=myylab, main=mymain)

Visualize the most popular names that are shared by both males and females.

Identify the top 5 male and female names from 2014. Visualize the popularity trend over time.

Identify the top 5 male and female names from 1986. Visualize the popularity trend over time.

Analysis of babynames with dplyr Use dplyr syntax to write Apache Spark SQL queries. Use select, where, group by, joins, and window functions in Aparche Spark SQL.

Test

test

Conditioned scatter plots

Test Energy Efficiency Regression Data