TL;DR
If I got it right, Voce can do using Dataframe pandas to read the file and then convert the values to type list
python. I created an example to show this, as Voce did not exemplify csv, I simulated one with only 3 columns and 4 rows, I read the file to a DataFrame
and in the end I create 3 'vectors', one with all lines, and the other two alternating one line for each one.
import pandas as pd
import io
s = '''
Nome,Sobrenome,Telefone
Foo,Bar,9-6666-6666
John,Doe,9-7777-7777
Lena,Luthor, 9-8888-8888
Peter,Gabriel, 9-9999-9999
'''
# Lendo o csv
df = pd.read_csv(io.StringIO(s), usecols=['Nome', 'Sobrenome', 'Telefone'])
# Imprimindo o resultado
print('\n',df)
print('','Vetor com todas as linhas:', df.values.tolist(), sep='\n')
print('','Vetor com as linhas nas posicoes pares:',df.values.tolist()[::2], sep='\n')
print('','Vetor com as linhas nas posicoes impares:',df.values.tolist()[1::2], sep='\n')
Exit:
Nome Sobrenome Telefone
0 Foo Bar 9-6666-6666
1 John Doe 9-7777-7777
2 Lena Luthor 9-8888-8888
3 Peter Gabriel 9-9999-9999
Vetor com todas as linhas:
[['Foo', 'Bar', '9-6666-6666'], ['John', 'Doe', '9-7777-7777'], ['Lena', 'Luthor', ' 9-8888-8888'], ['Peter', 'Gabriel', ' 9-9999-9999']]
Vetor com os elementos nas posicoes pares:
[['Foo', 'Bar', '9-6666-6666'], ['Lena', 'Luthor', ' 9-8888-8888']]
Vetor com os elementos nas posicoes impares:
[['John', 'Doe', '9-7777-7777'], ['Peter', 'Gabriel', ' 9-9999-9999']]
See working on repl.it.
Wow, for me to keep trying to help, could you explain why the downvote?
– Sidon