编程代写 Data_IO_Lab Key

Data_IO_Lab Key

Data_IO_Lab Key

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In this lab you can use the interactive console to explore or Knit the document. Remember anything you type here can be “sent” to the console with Cmd-Enter (OS-X) or Ctrl-Enter (Windows/Linux) in an R code chunk.

Read in the Youth Tobacco study from data/Youth_Tobacco_Survey_YTS_Data.csv and name it youth

library(readr)
youth = read_csv(“data/Youth_Tobacco_Survey_YTS_Data.csv”)

## Rows: 9794 Columns: 31
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: “,”
## chr (24): LocationAbbr, LocationDesc, TopicType, TopicDesc, MeasureDesc, Dat…
## dbl (7): YEAR, Data_Value, Data_Value_Std_Err, Low_Confidence_Limit, High_C…
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

Check youth for any problems.

problems(youth)

## # A tibble: 0 × 5
## # … with 5 variables: row , col , expected , actual ,
## # file

stop_for_problems(youth)

Load the readxl package with the library command. If it is not installed, install it via: RStudio –> Tools –> Install Packages

library(readxl)

Use the read_excel() function in the readxl package to read the Monuments.xlsx file and call the output mon.

mon = read_excel(“data/Monuments.xlsx”)

Write out the mon object as a CSV file calling it “monuments.csv”, using readr::write_csv:

write_csv(mon, “monuments.csv”)

Write out the mon object as a RDS file calling it “monuments.rds”, using readr::write_rds:

readr::write_rds(mon, “monuments.rds”)

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