## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( fig.width=5.5, fig.height=3, collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(lessR) ## ----read--------------------------------------------------------------------- d <- Read("Employee") ## ----labels------------------------------------------------------------------- l <- rd("Employee_lbl") l ## ----bcEx, fig.width=4, fig.height=3.5, fig.align='center', fig.cap="Bar chart of tablulated counts of employees in each department."---- BarChart(Dept) ## ----fig.width=4, fig.height=3.75, fig.align='center'------------------------- BarChart(Dept, fill="darkred", color="black", transparency=.8, labels_color="black") ## ----fig.width=4, fig.height=3.5, fig.align='center'-------------------------- BarChart(Dept, theme="gray", labels="off", horiz=TRUE) ## ----hs, fig.width=4, fig.height=3.5, fig.align='center', fig.cap="Histogram of tablulated counts for the bins of Salary."---- Histogram(Salary) ## ----binwidth, fig.width=4, fig.height=3.5, fig.align='center', fig.cap="Customized histogram."---- Histogram(Salary, bin_start=35000, bin_width=14000, fill="reds") ## ----sp, fig.width=4---------------------------------------------------------- Plot(Years, Salary) ## ----spEnhance, fig.width=4--------------------------------------------------- Plot(Years, Salary, enhance=TRUE) ## ----x1, fig.height=3--------------------------------------------------------- Plot(Salary) ## ----spBubble, fig.width=4---------------------------------------------------- Plot(JobSat, Gender) ## ----fig.height=4.25, fig.width=5--------------------------------------------- ttest(Salary ~ Gender) ## ----fig.width=5-------------------------------------------------------------- ANOVA(breaks ~ tension * wool, data=warpbreaks) ## ----------------------------------------------------------------------------- d <- Read("Jackets") Prop_test(Jacket, by=Bike) ## ----------------------------------------------------------------------------- d <- Read("Employee", quiet=TRUE) reg(Salary ~ Years + Pre) ## ----------------------------------------------------------------------------- r <- reg(Salary ~ Years + Pre) names(r) ## ----------------------------------------------------------------------------- r$out_fit ## ----------------------------------------------------------------------------- d <- Read("StockPrice") head(d) ## ----------------------------------------------------------------------------- d <- Read("StockPrice") Plot(Month, Price, filter=(Company=="Apple"), area_fill="on") ## ----------------------------------------------------------------------------- Plot(Month, Price, by=Company) ## ----------------------------------------------------------------------------- Plot(Month, Price, ts_unit="quarters", ts_agg="mean") ## ----------------------------------------------------------------------------- d <- d[400:473,] Plot(Month, Price, ts_unit="months", ts_agg="mean", ts_ahead=24) ## ----------------------------------------------------------------------------- d <- Read("Mach4", quiet=TRUE) l <- Read("Mach4_lbl", var_labels=TRUE) ## ----fig.width=3.5, fig.height=3.5-------------------------------------------- mycor <- cr(m01:m20) R <- mycor$R ## ----------------------------------------------------------------------------- efa(R, n_factors=4) ## ----------------------------------------------------------------------------- MeasModel <- " Deceit =~ m07 + m06 + m10 + m09 Trust =~ m12 + m05 + m13 + m01 Cynicism =~ m11 + m16 + m04 Flattery =~ m15 + m02 " ## ----------------------------------------------------------------------------- d <- Read("StockPrice", quiet=TRUE) pivot(d, c(mean, sd), Price, by=Company) ## ----------------------------------------------------------------------------- getColors("hues") ## ----echo=FALSE--------------------------------------------------------------- getColors("hues", output=TRUE) ## ----------------------------------------------------------------------------- getColors("blues") ## ----echo=FALSE--------------------------------------------------------------- getColors("blues", output=TRUE) ## ----------------------------------------------------------------------------- getColors("rusts", "blues") ## ----echo=FALSE--------------------------------------------------------------- getColors("rusts", "blues", output=TRUE)