[TL; DR]
There are several ways to do this, an easy one would be to use the pandas:
import pandas as pd
import io
# Simulando um CSV
s = '''
Mesa,Entrada,Saida,Conta
01,16:00,18:00,95.00
02,14:00,18:00,195.00
03,18:00,21:00,75.00
04,16:30,18:30,75.00
05,16:00,18:45,178.00
'''
# Lendo o csv
df = pd.read_csv(io.StringIO(s), usecols=['Mesa', 'Entrada', 'Saida', 'Conta'])
# Imprimindo o resultado
print(df)
Mesa Entrada Saida Conta
0 1 16:00 18:00 95.0
1 2 14:00 18:00 195.0
2 3 18:00 21:00 75.0
3 4 16:30 18:30 75.0
4 5 16:00 18:45 178.0
# Imprimindo coluna específica
print(df['Entrada'])
0 16:00
1 14:00
2 18:00
3 16:30
4 16:00
Name: Entrada, dtype: object
To iterate through the dataframe rows:
for index, row in df.iterrows():
print (row['Entrada'], row['Conta'])
Exit:
16:00 95.0
14:00 195.0
18:00 75.0
16:30 75.0
16:00 178.0
See working on repl.it *
* Have patience, no repl.it, or pandas it seems to freeze. : -)