Master data overview
So far you have combined information from rating and survey datasets with your original dataset.
We added several other employee-related information such as compensation, no_leaves_taken (number of vacation days taken), hiring_source etc. in the dataset org_final. Go ahead and check out this dataset before doing feature engineering in the next chapter.
Este exercício faz parte do curso
HR Analytics: Predicting Employee Churn in R
Instruções do exercício
- Use
glimpse()to view the structure of theorg_finaldataset. - Assign the number of variables in the
org_finaldataset tovariables. - Generate a box plot to visualize the distribution of
distance_from_homeforActiveandInactiveemployees.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# View the structure of the dataset
___
# Number of variables in the dataset
variables <- ___
# Compare the travel distance of Active and Inactive employees
ggplot(org_final, aes(x = ___, y = ___)) +
___