Read in the data (a csv file) from https://goo.gl/dWrc9m to a data frame called gapminder (data is also in data/gapminder5.csv if you don’t have an internet connection). Do you need to make any adjustments to the defaults? Note: you can specify a url instead of a filename/file path when using read.csv.
Look at the type of each column in the data you read in.
View the observations for Belgium.
gapminder<-read.csv("https://goo.gl/dWrc9m") ## defaults OK here
str(gapminder)
View(gapminder[gapminder$country=="Belgium",])Or, with readr:
library(readr)
gapminder<-read_csv("https://goo.gl/dWrc9m")Read in the tab-delimited file (states.txt) at https://goo.gl/AwnS4R (data is also at data/states.txt). What changes do you need to make to read in tab-delimited data? Are any other adjustments to the defaults warranted?
Change the column names to state, lat, and lon.
Does anything look strange to you about this data?
statedata<-read.csv("https://goo.gl/AwnS4R", sep='\t', col.names=c("state", "lat","lon"))
dim(statedata)## [1] 55 3There are more than 50 observations. Take a look at the data, and you’ll see some unfamiliar codes. These correspond to US territories. It’s always good to check to make sure your data looks like you expect.
Above, with readr:
library(readr)
statedata<-read_tsv("https://goo.gl/AwnS4R", col_names=c("state", "lat","lon"))You read in the state data above. Now write it to file as a CSV file, with sensible options.
# data read into a data frame called statedata above
write.csv(statedata, "statedatacopy.csv", row.names=FALSE)Above, with readr:
library(readr)
statedata<-write_csv(statedata, "statedatacopy.csv")Create an Excel file. Read it into Excel with the readxl package. How would you read in the second sheet?
Create your own file. Let’s pretend it’s called mydata.xlsx. Then
library(readxl)
mydata <- read_excel("mydata.xlsx")To read in the second sheet, use the sheet argument to read_excel.