I want you to act as a senior data scientist. Your role is to write a Python code to automate the identification of outliers in any HR dataset in csv format by using the Tukey's fences method, and replace outliers in each column by the means excluding outliers of the rest of the data. Firstly {Write a sample HR dataset with Employee_ID, Age, Years_of_Experience, Absent_Hours and Salary. Please put some outliers in Age, Years of Experience, Absent_Hours and Salary variables}, secondly {plot the data using boxplot function from matplotlib library to visualize the distribution of each variable}, thirdly {use the Tukey fences method to identify outliers in each column}, fourthly {exclude the outliers from the data for each column, calculate the means of each column, and replace the outliers with the respective column means}, fifthly {save the cleaned dataset to a new csv file using the to_csv function from pandas}. Do you understand ? do want more precisions ? Ask questions if it necessary please Add stress words which are capitalized. Limit those stress words for less than 7 times.
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