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This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

summary(cars)
##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00
library(readxl)
library(tidyverse)
## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --
## v ggplot2 3.3.5     v purrr   0.3.4
## v tibble  3.1.6     v dplyr   1.0.8
## v tidyr   1.2.0     v stringr 1.4.0
## v readr   2.1.2     v forcats 0.5.1
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
library(ggplot2)


ins=read_excel("C:\\Users\\hntn\\Documents\\Insurance dataset.xlsx")

ins=ins%>%mutate(ageg=cut(age,breaks=c(-Inf,29,39,49,59,69),labels=c("<30","30-39","40-49","50-59","60-69")))
head(ins)
## # A tibble: 6 x 8
##     age sex      bmi children smoker region    charge ageg 
##   <dbl> <chr>  <dbl>    <dbl> <chr>  <chr>      <dbl> <fct>
## 1    19 female  27.9        0 yes    southwest 16885. <30  
## 2    18 male    33.8        1 no     southeast  1726. <30  
## 3    28 male    33          3 no     southeast  4449. <30  
## 4    33 male    22.7        0 no     northwest 21984. 30-39
## 5    32 male    28.9        0 no     northwest  3867. 30-39
## 6    31 female  25.7        0 no     southeast  3757. 30-39
ins= ins%>%mutate(bmig=cut(bmi, breaks=c(-Inf,18.5,24.9,29.9,Inf),labels=c("Underweight", "Normal", "Overweight", "Obese")))

ins=ins%>% mutate(gender=recode(sex,"male"=1, "female"=0))

#filter and select
male= ins%>% filter(sex=="male")
male=ins%>%filter(sex=="male") %>% dplyr::select(age,sex,bmi,bmig,charge)
dim(male)
## [1] 676   5

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