UnsplashのKumiko SHIMIZUが撮影した写真
Hello. In this post, I will analyze Gender wage gap of OECD data with R.
First, I download CSV file like belo from OECD web site,
https://data.oecd.org/earnwage/gender-wage-gap.htm
I use R to analyze this data.
I firstly load tidyverse package.
Then, use read_csv() command to load the CSV file data into R.
I see 5 variables are categorized as chr and 2 variables are categorized as dbl.
Let's check each variables.
LOCATION is country.
INDICATOR has only one value, WAGEGAP, so I will delete this variable.
SUBJECT has two value, EMPLOYEE and SELFEMPLOYED. I keep SUBJECT.
MEASURE has only one value, PC. I remove MEASURE.
FREQUENCY has only one value, A, so I remove REQUENCY.
The oldest TIME is 1970 and the newest TIME is 2021. 2014 has the most many observations, there are 73 observations.
Let's calculate mean Value by SUBJECT.
I see SELFEMPLOYED mean is higher than EMPLOYEE mean. It means there is much Gender gap in SELFEMPLOYED than in EMPLOYEE.
That's it. Thank you!
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