Example code and data for "Practical Data Science with R" by Nina Zumel and John Mount, Manning 2014.
- The book: "Practical Data Science with R" by Nina Zumel and John Mount, Manning 2014 (book copyright Manning Publications Co., all rights reserved)
- The support site: GitHub WinVector/zmPDSwR
- Appendix A: Working with R And Other Tools
Material from Practical Data Science with R examples GitHub archive In support of the Hotel/SQL example in Appendix A of Practical Data Science with R by Nina Zumel and John Mount.
- start with README.Rmd and Workbook1.xlsx
- produce README.md, HotelRelation.pdf and figure/* by running "knit('README.Rmd')" in R
- produce README.html by running "pandoc README.md -o README.html" in bash shell
- or all in one shot at the bash shell: echo "library('knitr'); knit('README.Rmd')" | R --vanilla ; pandoc README.md -o README.html
library('xlsx')
## Loading required package: xlsxjars
## Loading required package: rJava
bookings <- read.xlsx('Workbook1.xlsx',1,startRow=3)
prices <- read.xlsx('Workbook1.xlsx',2,startRow=3)
library('reshape2')
bthin <- melt(bookings,id.vars=c('date'),
variable.name='daysBefore',value.name='bookings')
pthin <- melt(prices,id.vars=c('date'),
variable.name='daysBefore',value.name='price')
daysCodes <- c('day.of.stay', 'X1.before', 'X2.before', 'X3.before')
bthin$nDaysBefore <- match(bthin$daysBefore,daysCodes)-1
pthin$nDaysBefore <- match(pthin$daysBefore,daysCodes)-1
# prevent sqldf from triggering tcl/tk dependency
# see: https://code.google.com/p/sqldf/ Troubleshooting
options(gsubfn.engine = "R")
library('sqldf')
## Loading required package: DBI
## Loading required package: gsubfn
## Loading required package: proto
## Loading required package: chron
## Loading required package: RSQLite
## Loading required package: RSQLite.extfuns
joined <- sqldf('
select
bCurrent.date as StayDate,
bCurrent.daysBefore as daysBefore,
bCurrent.nDaysBefore as nDaysBefore,
p.price as price,
bCurrent.bookings as bookingsCurrent,
bPrevious.bookings as bookingsPrevious,
bCurrent.bookings - bPrevious.bookings as pickup
from
bthin bCurrent
join
bthin bPrevious
on
bCurrent.date=bPrevious.date
and bCurrent.nDaysBefore+1=bPrevious.nDaysBefore
join
pthin p
on
bCurrent.date=p.date
and bCurrent.nDaysBefore=p.nDaysBefore
')
library('ggplot2')
plt <- ggplot(data=joined,aes(x=price,y=pickup)) +
geom_point() + geom_jitter() + geom_smooth(method='lm')
print(plt)
ggsave(filename='HotelRelation.pdf',plot=plt)
## Saving 7 x 7 in image
print(summary(lm(pickup~price,data=joined)))
##
## Call:
## lm(formula = pickup ~ price, data = joined)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.62 -2.81 -1.21 3.39 6.38
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 11.0077 7.9874 1.38 0.2
## price -0.0280 0.0319 -0.88 0.4
##
## Residual standard error: 4.21 on 10 degrees of freedom
## Multiple R-squared: 0.0714, Adjusted R-squared: -0.0214
## F-statistic: 0.769 on 1 and 10 DF, p-value: 0.401
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