[R] Data Frame Construction

This post covers data frame construction in R Studio.

1. Data imputation

This method involves data imputation and employing data.frame() function.

The table below displays fertility rate and unemployment rate of South Korea, Japan, Canada, and United States in 2020.

Country	Fertility rate	Unemployment rate
Korea	0.84	3.94
Japan	1.33	2.77
Canada	1.50	9.56
USA	1.64	8.09

(I used data of OECD DATA from the following links.

https://data.oecd.org/pop/fertility-rates.htm#indicator-chart

https://data.oecd.org/unemp/unemployment-rate.htm )

1) 2 step method

You can generate the variables first and then use data.frame() function.

#step 1 - variable generation
country <- c("Korea", "Japan", "Canada", "USA")
FTR <- c(0.84, 1.33, 1.50, 1.64)
UPR <- c(3.94, 2.77, 9.56, 8.09)
#step 2 - generation and designation of data frame 
df1 <- data.frame(country, FTR, UPR)
df1

You will get results as below.

> df1
  country  FTR  UPR
1   Korea 0.84 3.94
2   Japan 1.33 2.77
3  Canada 1.50 9.56
4     USA 1.64 8.09

2) 1 step method

It is also possible to generate variables within the data.frame() function.

Note that the variables must be separated by ',(comma)'s. 

df1 <- data.frame(country = c("Korea", "Japan", "Canada", "USA"),
                  FTR = c(0.84, 1.33, 1.50, 1.64),
                  UPR = c(3.94, 2.77, 9.56, 8.09))

*However, researchers often simply import data sets from external sources (such as Excel) rather than typing in values (data imputation) in R Studio.

To refer to how to import data sets, please follow the link below.

https://ik-lab.blogspot.com/2022/06/r-studio-data-import.html

2. Loading data

Other than constructing data frame oneself, we can simply load data.

Here, we are going to load 'mpg' from 'ggplot2' package and view it.

install.packages("ggplot2")
library(ggplot2)
mpg <- as.data.frame(ggplot2::mpg)
View(mpg)