library(mosaicCalc)
## Loading required package: mosaic
## Registered S3 method overwritten by 'mosaic':
##   method                           from   
##   fortify.SpatialPolygonsDataFrame ggplot2
## 
## The 'mosaic' package masks several functions from core packages in order to add 
## additional features.  The original behavior of these functions should not be affected by this.
## 
## Attaching package: 'mosaic'
## The following objects are masked from 'package:dplyr':
## 
##     count, do, tally
## The following object is masked from 'package:Matrix':
## 
##     mean
## The following object is masked from 'package:ggplot2':
## 
##     stat
## The following objects are masked from 'package:stats':
## 
##     binom.test, cor, cor.test, cov, fivenum, IQR, median, prop.test,
##     quantile, sd, t.test, var
## The following objects are masked from 'package:base':
## 
##     max, mean, min, prod, range, sample, sum
## Loading required package: mosaicCore
## 
## Attaching package: 'mosaicCore'
## The following objects are masked from 'package:dplyr':
## 
##     count, tally
## 
## Attaching package: 'mosaicCalc'
## The following object is masked from 'package:stats':
## 
##     D
slice_plot(3 * x - 2 ~ x, domain(x = range(0, 10)))

m = -3
b = -2
slice_plot(m * x + b ~ x, domain(x = range(0, 10)))

library(mosaicCalc)
m = -3
b = -2
slice_plot(m * x + b ~ x, domain(x = range(0, 10)))

g  <- makeFun(2*x^2 - 5*x + 2 ~ x)
slice_plot(g(x) ~ x , domain(x = range(-2, 2)))

slice_plot(sqrt(abs(g(x))) ~ x, domain(x = range(-5,5)))

x <- 10
slice_plot(A * x ^  2 ~ A, domain(A = range(-2,  3)))

slice_plot( 4 * x - 7 ~ x, domain(x = range(0, 10) ))

slice_plot( cos(5 * x) ~ x, domain(x = range(-1, 1)))

slice_plot( cos(2 * t) ~ t, domain(t = range(0,5) ))

slice_plot( sqrt(t) * cos(5 * t) ~ t, domain(t = range(0, 5) ))

Housing = read.csv("http://www.mosaic-web.org/go/datasets/Income-Housing.csv")
Housing
##   Income IncomePercentile CrimeProblem AbandonedBuildings IncompleteBathroom
## 1   3914                5         39.6               12.6                2.6
## 2  10817               15         32.4               10.0                3.3
## 3  21097               30         26.7                7.1                2.3
## 4  34548               50         23.9                4.1                2.1
## 5  51941               70         21.4                2.3                2.4
## 6  72079               90         19.9                1.2                2.0
##   NoCentralHeat ExposedWires AirConditioning TwoBathrooms MotorVehicle
## 1          32.3          5.5            52.3         13.9         57.3
## 2          34.7          5.0            55.4         16.9         82.1
## 3          28.1          2.4            61.7         24.8         91.7
## 4          21.4          2.1            69.8         39.6         97.0
## 5          14.9          1.4            73.9         51.2         98.0
## 6           9.6          1.0            76.7         73.2         99.0
##   TwoVehicles ClothesWasher ClothesDryer Dishwasher Telephone
## 1        17.3          57.8         37.5       16.5      68.7
## 2        34.3          61.4         38.0       16.0      79.7
## 3        56.4          78.6         62.0       25.8      90.8
## 4        75.3          84.4         75.2       41.6      96.5
## 5        86.6          92.8         88.9       58.2      98.3
## 6        92.9          97.1         95.6       79.7      99.5
##   DoctorVisitsUnder7 DoctorVisits7To18 NoDoctorVisitUnder7 NoDoctorVisit7To18
## 1                3.6               2.6                13.7               31.2
## 2                3.7               2.6                14.9               32.0
## 3                3.6               2.1                13.8               31.4
## 4                4.0               2.3                10.4               27.3
## 5                4.0               2.5                 7.7               23.9
## 6                4.7               3.1                 5.3               17.5
Housing[,1:2]
##   Income IncomePercentile
## 1   3914                5
## 2  10817               15
## 3  21097               30
## 4  34548               50
## 5  51941               70
## 6  72079               90
gf_point(CrimeProblem ~ Income, data = Housing )

gf_point( 
  CrimeProblem ~ Income, data=Housing ) %>%
  slice_plot(
    40 - Income/2000 ~ Income, color = "red")

contour_plot(
  sqrt( (v-3)^2 + (w-4)^2 ) ~ v & w, 
  domain(v=0:6, w=0:6))

Utilities <- read.csv(
  "http://www.mosaic-web.org/go/datasets/utilities.csv")

gf_point( 
  temp ~ month, data=Utilities) %>% 
  gf_labs(x = "Month (Jan=1, Dec=12)",
          y = "Temperature (F)",
          main = "Ave. Monthly Temp.")