Группируйте элементы в фрейме данных и отображайте их в хронологическом порядке

# Sort by Date and Time
df['DateTime'] = pd.to_datetime(df['Date'] + ' ' + df['Time'], format='%d-%m-%Y %H:%M:%S')
df_sorted = df.sort_values('DateTime')

# Find the first occurrence of each Table group
first_occurrences = df_sorted.groupby('Table', as_index=False).first()

# Sort Table groups according to the Date and Time of their first occurrence
table_order = first_occurrences.sort_values('DateTime')['Table']

# Create categorical version of 'Table' specifying the order of the categories
df_sorted['Table_cat'] = pd.Categorical(df_sorted['Table'], categories=table_order, ordered=True)

# Sort the dataframe
result = df_sorted.sort_values(['Table_cat', 'DateTime'])
result = result.reset_index(drop=True).drop('Table_cat', axis=1)

Используйте groupby.transform и numpy.lexsort:

date = pd.to_datetime(df['Date']+' '+df['Time'])

out = df.iloc[np.lexsort([
    date,
    df['Table'],
    date.groupby(df['Table']).transform('min')
])]

Альтернативно, используя промежуточный столбец:

date = pd.to_datetime(df['Date']+' '+df['Time'])

out = (df.assign(date=date, min_date=date.groupby(df['Table']).transform('min'))
         .sort_values(by=['min_date', 'Table', 'date'])
         .drop(columns=['date', 'min_date'])
     )

Выход:

         Date      Time Table
0  01-10-2000  13:00:03     B
2  01-10-2000  13:00:05     B
4  01-10-2000  13:00:07     B
1  01-10-2000  13:00:04     A
3  01-10-2000  13:00:06     A
5  01-10-2000  13:00:08     A

import pandas as pd
import numpy as np

data = {
    'Date': ['01-10-2000', '01-10-2000', '01-10-2000', '01-10-2000', '01-10-2000', '01-10-2000'],
    'Time': ['13:00:03', '13:00:04', '13:00:05', '13:00:06', '13:00:07', '13:00:08'],
    'Table': ['B', 'A', 'B', 'A', 'B', 'A']
}
df = pd.DataFrame(data)
'''
         Date      Time Table
0  01-10-2000  13:00:03     B
1  01-10-2000  13:00:04     A
2  01-10-2000  13:00:05     B
3  01-10-2000  13:00:06     A
4  01-10-2000  13:00:07     B
5  01-10-2000  13:00:08     A
'''

res = df.iloc[np.lexsort(df['Table'].values + 
        pd.to_datetime(df['Date'] + ' ' + df['Time']).astype(str))
        ].reset_index(drop=True)

print(res)
'''
         Date      Time Table
0  01-10-2000  13:00:04     A
1  01-10-2000  13:00:06     A
2  01-10-2000  13:00:08     A
3  01-10-2000  13:00:03     B
4  01-10-2000  13:00:05     B
5  01-10-2000  13:00:07     B
'''