﻿Given the following messy CSV data, write a complete pipeline that cleans it, computes statistics, and generates chart-ready output.

`csv
Name,Age,Salary,Department,Start Date
Alice,30,75000,Engineering,2020-01-15
Bob,,85000,Engineering,2019-06-01
Charlie,28,,Marketing,2021-03-10
Diana,35,92000,Engineering,2018-11-20
Eve,42,78000,,2017-05-30
Frank,29,71000,Marketing,invalid-date
Grace,31,88000,Engineering,2020-08-12
Hank,27,65000,Marketing,2022-01-05
Ivy,,95000,Engineering,2019-09-15
Jack,33,82000,Sales,2020-04-22
,25,70000,Sales,2021-07-18
Leo,38,91000,Engineering,2018-03-01
`

Pipeline steps:
1. Load and handle missing/invalid values (fill, drop, or flag each).
2. Compute per-department statistics: count, mean salary, median salary, salary std dev.
3. Compute tenure in years from Start Date to 2026-09-28.
4. Output a clean summary table and the data for a bar chart of average salary by department.
