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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
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
library(mosaicCalc)
subset1 <- Housing[2:4,1:2]
subset1
##   Income IncomePercentile
## 2  10817               15
## 3  21097               30
## 4  34548               50
income <- Housing$IncomePercentile
income
## [1]  5 15 30 50 70 90
library(mosaicCalc)
gf_point(CrimeProblem ~ Income, data = Housing )

library(mosaicCalc)
gf_point( 
  MotorVehicle ~ Income, data=Housing ) %>%
  slice_plot(
    80 - Income/8000 ~ Income, color = "white")

library(mosaicCalc)
gf_point(
  CrimeProblem ~ Telephone, data = Housing) 

library(mosaicCalc)
gf_point(
  income ~ income, data = Housing) %>% 
  slice_plot(
    92 - Telephone / 80 ~ Telephone, color = "blue")

gf_point(
  CrimeProblem ~ Income, data = Housing) %>% 
  slice_plot(
    40 - Income / 2000 ~ Income, color = "blue") %>%
  gf_lims(
    x = range(0,100000), 
    y=range(0,50))

gf_point(
  CrimeProblem ~ Income, data=Housing) %>%
  gf_labs(x= "Income Bracket ($US per household)/year",
          y = "Fraction of Households",
          main = "Crime Problem") %>%
  gf_lims(x = range(0,130000), y = range(0,800))

LATIHAN !!!

s = read.csv(
  "http://www.mosaic-web.org/go/datasets/stan-data.csv")
gf_point(temp ~ time, data=s)

h = read.csv(
  "http://www.mosaic-web.org/go/datasets/hawaii.csv")
gf_point(water ~ time, data=h)

interactive_plot(
   sin(1*pi*t/8)*exp(-.3*x) ~ t & x, 
   domain(t = 1:90, x = 2:40))
gf_point(height ~ age, data=datasets::Loblolly)