This is Quiz 4 from the Getting and Cleaning Data course within the Data Science Specialization on Coursera.
1. The American Community Survey distributes downloadable data about United States communities. Download the 2006 microdata survey about housing for the state of Idaho using download.file() from here:
https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2Fss06hid.csv
and load the data into R. The code book, describing the variable names is here:
https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2FPUMSDataDict06.pdf
Apply strsplit() to split all the names of the data frame on the characters “wgtp”. What is the value of the 123 element of the resulting list?
library(data.table)
download.file("https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2Fss06hid.csv", destfile = "quiz4data.csv")
d <- read.csv("quiz4data.csv")
strsplit(names(d), split = "wgtp")[123]## [[1]]
## [1] "" "15"2. Load the Gross Domestic Product data for the 190 ranked countries in this data set:
https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2FGDP.csv
Remove the commas from the GDP numbers in millions of dollars and average them. What is the average?
Original data sources:
http://data.worldbank.org/data-catalog/GDP-ranking-table
download.file("https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2FGDP.csv", destfile = "quiz4data.csv")
data <- read.csv("quiz4data.csv")
clean <- gsub(",","",data[,5])
mean(as.numeric(clean[1:215]),na.rm = TRUE)
4. Load the Gross Domestic Product data for the 190 ranked countries in this data set:
https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2FGDP.csv
Load the educational data from this data set:
https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2FEDSTATS_Country.csv
Match the data based on the country shortcode. Of the countries for which the end of the fiscal year is available, how many end in June?
download.file("https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2FGDP.csv", destfile = "quiz4data2.csv")
data2 <- read.csv("quiz4data2.csv")
download.file("https://d396qusza40orc.cloudfront.net/getdata%2Fdata%2FEDSTATS_Country.csv", destfile = "quiz4data3.csv")
data3 <- read.csv("quiz4data3.csv")
setnames(data2, c("X", "X.1", "X.3", "X.4"), c("CountryCode", "rankingGDP", "Long.Name", "gdp"))
all <- merge(data2, data3, by = "CountryCode")
table(grepl("june", tolower(all$Special.Notes)), grepl("fiscal year end", tolower(all$Special.Notes)))[4]## [1] 135.
You can use the quantmod (http://www.quantmod.com/) package to get historical stock prices for publicly traded companies on the NASDAQ and NYSE. Use the following code to download data on Amazon’s stock price and get the times the data was sampled.
library(quantmod)## Loading required package: xts## Loading required package: zoo##
## Attaching package: 'zoo'## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric##
## Attaching package: 'xts'## The following object is masked from 'package:data.table':
##
## last## Loading required package: TTR## Version 0.4-0 included new data defaults. See ?getSymbols.amzn = getSymbols("AMZN",auto.assign=FALSE)## As of 0.4-0, 'getSymbols' uses env=parent.frame() and
## auto.assign=TRUE by default.
##
## This behavior will be phased out in 0.5-0 when the call will
## default to use auto.assign=FALSE. getOption("getSymbols.env") and
## getOptions("getSymbols.auto.assign") are now checked for alternate defaults
##
## This message is shown once per session and may be disabled by setting
## options("getSymbols.warning4.0"=FALSE). See ?getSymbols for more details.sampleTimes = index(amzn)How many values were collected in 2012? How many values were collected on Mondays in 2012? head(data)
length(grep("^2012",sampleTimes))## [1] 250library(lubridate)##
## Attaching package: 'lubridate'## The following objects are masked from 'package:data.table':
##
## hour, mday, month, quarter, wday, week, yday, year## The following object is masked from 'package:base':
##
## datesampleTimes[grep("^2012",sampleTimes)]## [1] "2012-01-03" "2012-01-04" "2012-01-05" "2012-01-06" "2012-01-09"
## [6] "2012-01-10" "2012-01-11" "2012-01-12" "2012-01-13" "2012-01-17"
## [11] "2012-01-18" "2012-01-19" "2012-01-20" "2012-01-23" "2012-01-24"
## [16] "2012-01-25" "2012-01-26" "2012-01-27" "2012-01-30" "2012-01-31"
## [21] "2012-02-01" "2012-02-02" "2012-02-03" "2012-02-06" "2012-02-07"
## [26] "2012-02-08" "2012-02-09" "2012-02-10" "2012-02-13" "2012-02-14"
## [31] "2012-02-15" "2012-02-16" "2012-02-17" "2012-02-21" "2012-02-22"
## [36] "2012-02-23" "2012-02-24" "2012-02-27" "2012-02-28" "2012-02-29"
## [41] "2012-03-01" "2012-03-02" "2012-03-05" "2012-03-06" "2012-03-07"
## [46] "2012-03-08" "2012-03-09" "2012-03-12" "2012-03-13" "2012-03-14"
## [51] "2012-03-15" "2012-03-16" "2012-03-19" "2012-03-20" "2012-03-21"
## [56] "2012-03-22" "2012-03-23" "2012-03-26" "2012-03-27" "2012-03-28"
## [61] "2012-03-29" "2012-03-30" "2012-04-02" "2012-04-03" "2012-04-04"
## [66] "2012-04-05" "2012-04-09" "2012-04-10" "2012-04-11" "2012-04-12"
## [71] "2012-04-13" "2012-04-16" "2012-04-17" "2012-04-18" "2012-04-19"
## [76] "2012-04-20" "2012-04-23" "2012-04-24" "2012-04-25" "2012-04-26"
## [81] "2012-04-27" "2012-04-30" "2012-05-01" "2012-05-02" "2012-05-03"
## [86] "2012-05-04" "2012-05-07" "2012-05-08" "2012-05-09" "2012-05-10"
## [91] "2012-05-11" "2012-05-14" "2012-05-15" "2012-05-16" "2012-05-17"
## [96] "2012-05-18" "2012-05-21" "2012-05-22" "2012-05-23" "2012-05-24"
## [101] "2012-05-25" "2012-05-29" "2012-05-30" "2012-05-31" "2012-06-01"
## [106] "2012-06-04" "2012-06-05" "2012-06-06" "2012-06-07" "2012-06-08"
## [111] "2012-06-11" "2012-06-12" "2012-06-13" "2012-06-14" "2012-06-15"
## [116] "2012-06-18" "2012-06-19" "2012-06-20" "2012-06-21" "2012-06-22"
## [121] "2012-06-25" "2012-06-26" "2012-06-27" "2012-06-28" "2012-06-29"
## [126] "2012-07-02" "2012-07-03" "2012-07-05" "2012-07-06" "2012-07-09"
## [131] "2012-07-10" "2012-07-11" "2012-07-12" "2012-07-13" "2012-07-16"
## [136] "2012-07-17" "2012-07-18" "2012-07-19" "2012-07-20" "2012-07-23"
## [141] "2012-07-24" "2012-07-25" "2012-07-26" "2012-07-27" "2012-07-30"
## [146] "2012-07-31" "2012-08-01" "2012-08-02" "2012-08-03" "2012-08-06"
## [151] "2012-08-07" "2012-08-08" "2012-08-09" "2012-08-10" "2012-08-13"
## [156] "2012-08-14" "2012-08-15" "2012-08-16" "2012-08-17" "2012-08-20"
## [161] "2012-08-21" "2012-08-22" "2012-08-23" "2012-08-24" "2012-08-27"
## [166] "2012-08-28" "2012-08-29" "2012-08-30" "2012-08-31" "2012-09-04"
## [171] "2012-09-05" "2012-09-06" "2012-09-07" "2012-09-10" "2012-09-11"
## [176] "2012-09-12" "2012-09-13" "2012-09-14" "2012-09-17" "2012-09-18"
## [181] "2012-09-19" "2012-09-20" "2012-09-21" "2012-09-24" "2012-09-25"
## [186] "2012-09-26" "2012-09-27" "2012-09-28" "2012-10-01" "2012-10-02"
## [191] "2012-10-03" "2012-10-04" "2012-10-05" "2012-10-08" "2012-10-09"
## [196] "2012-10-10" "2012-10-11" "2012-10-12" "2012-10-15" "2012-10-16"
## [201] "2012-10-17" "2012-10-18" "2012-10-19" "2012-10-22" "2012-10-23"
## [206] "2012-10-24" "2012-10-25" "2012-10-26" "2012-10-31" "2012-11-01"
## [211] "2012-11-02" "2012-11-05" "2012-11-06" "2012-11-07" "2012-11-08"
## [216] "2012-11-09" "2012-11-12" "2012-11-13" "2012-11-14" "2012-11-15"
## [221] "2012-11-16" "2012-11-19" "2012-11-20" "2012-11-21" "2012-11-23"
## [226] "2012-11-26" "2012-11-27" "2012-11-28" "2012-11-29" "2012-11-30"
## [231] "2012-12-03" "2012-12-04" "2012-12-05" "2012-12-06" "2012-12-07"
## [236] "2012-12-10" "2012-12-11" "2012-12-12" "2012-12-13" "2012-12-14"
## [241] "2012-12-17" "2012-12-18" "2012-12-19" "2012-12-20" "2012-12-21"
## [246] "2012-12-24" "2012-12-26" "2012-12-27" "2012-12-28" "2012-12-31"sum(weekdays(as.Date(sampleTimes[grep("^2012",sampleTimes)]))=="Monday")## [1] 47See more at: http://www.ryantillis.com/