QueueLength3.py

# Initialize date ranges list
date_ranges_list = []

# Loop through all the orders placed on the source file
for i, row in df.iterrows():

    # Get Start/End Time
    enter_t = row["OrderCreatedLocalDateTime"].replace(second=0, microsecond=0)
    exit_t = row["TimeOutOfQueue"].replace(second=0, microsecond=0)

    # Skip orders served within the same minute
    if enter_t == exit_t:
        continue

    # Get the date ranges in minutes between Enter/Exit
    date_range = pd.date_range(
        start=enter_t,
        end=exit_t,
        freq="1min",
        inclusive="right",
    ).tz_localize(None)

    # Append the list of date ranges
    date_ranges_list.append(pd.Series(date_range))

# Accumulate all date ranges
all_date_ranges = pd.concat(date_ranges_list)

# Count the number of occurences for a date/time
orders_counts = all_date_ranges.value_counts().sort_index().to_frame(name="Orders")

# Merge the orders count into the minutes table
minutes_df = pd.merge(
    minutes_df, 
    orders_counts, 
    how="left", 
    left_on="Business Date", 
    right_index=True
)

# Clear empty cells
minutes_df.fillna(0, inplace=True)

# Convert Orders column to int type
minutes_df['Orders'] = minutes_df['Orders'].astype('int')

# Visualize top rows
minutes_df.head()