Employees_2.py

# Replace null values with string "no" (i.e., meaning that employee has not left the company)
df['Departure Date'] = df['Departure Date'].fillna("no")

# Get a list of all months from the hiring date of the first employee until current month
all_months = pd.date_range(df["Hiring Date"].unique()[0], datetime.datetime.today().strftime('%m/%d/%Y'), freq='MS').strftime("%Y-%b").tolist()

# Initialize list for cummulative employees
cummulative_employees = []

# Loop through all the months in list
for past_month in all_months:
    
    # Initialize counter of active employees for given month
    current_employees_in_month = 0
    
    # Loop through all the employees
    for i in range(0,len(df)):
        
        # If employee was hired on or before current month and has not departed
        if pd.to_datetime(df["Hiring Date"][i]) <= pd.to_datetime(past_month) and (df["Departure Date"][i] == "no"):
            current_employees_in_month += 1
            
        # If employee has departed and was hired on or before current month and their departure date is greater than current month
        if df["Departure Date"][i] != "no" and pd.to_datetime(df["Hiring Date"][i]) <= pd.to_datetime(past_month) and pd.to_datetime(df["Departure Date"][i]) > pd.to_datetime(past_month):
            current_employees_in_month += 1

    # Append total cummulative employees for given month
    cummulative_employees.append(current_employees_in_month)
    
# Create dataframe with active employees count per month
employees_df = pd.DataFrame({"Date":all_months, "Count Active Employees":cummulative_employees})

# Parse Date column as datetime and set it as index
employees_df["Date"] = pd.to_datetime(employees_df["Date"])
employees_df.set_index("Date", inplace=True)

# Display bottom rows
employees_df.tail()