[Python] Backfilling and Forwardfilling NaNs and Zeros

I am trying to back/forward fill the work experience (years) of employees. What I am trying to achieve is:

Employee 200

2019 - 3 yrs, 2018 - 2 yrs, 2017 - 1 yr

Employee 300

Keep as Nan

Employee 400

2018 - 3 yrs, 2017 - 2 yrs

Employee 500

2018 - 6 yrs, 2017 - 5 yrs, 2016 - 4 yrs

I am really struggling to get it to backfill (forwardfill) by increments of -1 (+1). Even trickier if the non-NaN/zero value is in the middle as in the case of employee 500.

df_test = pd.DataFrame({'DeptID':[0,0,0,1,1,1,2,2,2],
'Employee':[200, 200, 200, 300, 400, 400, 500, 500, 500],
'Year':[2017, 2018, 2019, 2016, 2017, 2018, 2016, 2017, 2018],
'Experience':[np.nan , np.nan, 3, np.nan, 2, np.nan, 0, 5, 0]
})

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