Page 310 - Touhpad Ai

print(df)

# Step 2: Convert Joining_Date format to YYYY-MM-DD
df['Joining_Date'] = pd.to_datetime(df['Joining_Date'], format='%m/%d/%Y').
dt.strftime('%Y-%m-%d')

# Step 3: Calculate Monthly Salary
df['Monthly_Salary'] = df['Annual_Salary'] / 12

# Step 4: Encode Department
dept_mapping = {'HR': 1, 'IT': 2, 'Sales': 3}
df['Department_Code'] = df['Department'].map(dept_mapping)

# Step 5: Replace missing Bonus values with 0
df['Bonus'] = df['Bonus'].fillna(0)

# Step 6 (Bonus): Calculate Experience in Years
df['Experience_Years'] = datetime.now().year - pd.to_datetime(df['Joining_Date']).
dt.year
print("\nTransformed DataFrame:")
print(df)
Output:
Original DataFrame:
Employee Joining_Date Annual_Salary Department Bonus
0 Aarav 05/14/2020 480400 HR 20000.0
1 Elena 11/20/2018 602070 IT NaN
2 Kashish 07/03/2019 550040 Sales 15000.0
3 Manish 01/15/2021 725006 IT NaN
4 Ishaan 12/05/2017 505006 HR 10000.0

Transformed DataFrame:
Employee Joining_Date ... Department_Code Experience_Years
0 Aarav 2020-05-14 ... 1 5
1 Elena 2018-11-20 ... 2 7
2 Kashish 2019-07-03 ... 3 6
3 Manish 2021-01-15 ... 2 4
4 Ishaan 2017-12-05 ... 1 8

[5 rows x 8 columns]

308 Touchpad Artificial Intelligence - XI