R Markdown

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

Including Plots

You can also embed plots, for example:

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.

Leer datasets

#Archivos .csv .txt .tsv

library(readr)

read.csv() #Archivos .csv separados por coma read.table() #Archivos .txt separado por espacio read.csv2() #Archivos .csv separados por ; read_tsv() # tab

#Archivo Excel install.packages(“readxl”) library(readxl) read_excel() #.xls .xlsx read_xls() read_xlsx()

url<-“https://raw.githubusercontent.com/rafalab/dslabs/master/inst/extdata/murders.csv” murders<-read.csv(url) download.file(url,“murders.csv”)

#Resumen

library(dplyr) library(dslabs)

data(“heights”) head(heights,10) #Calcular el promedio y la desviación estándar por genero # Male sm<-heights %>% filter(sex==“Male”) %>% summarise(mean=mean(height),sd=sd(height)) sm

Interpretar los resultados

mean y sd

#Acceder a los elementos sm$mean

#Female sf<-heights %>% filter(sex==“Female”) %>% summarise(mean=mean(height),sd=sd(height)) sf

data(“murders”)

head(murders)

max_total <- murders\(state[which.max(murders\)total)] max_total

max_population <- murders\(state[which.max(murders\)population)] max_population #Tasa de asesinatos por cada 100000 habitantes #Crear columna murders <- murders %>% mutate(rate=total*100000/population)

head(murders) meanrate <- murders %>% select(rate) %>% summarise(mean(rate)) meanrate

murders <- murders %>% mutate(dif=meanrate$mean(rate)-rate) head(murders)

#Analizar cuáles son los estados que están por encima # del promedio de la tasa de asesinatos

quantile(murders$rate,c(0.5,0,1))