CSV в многомерный массив

s="a;b;c;d;e;\na2;b2;c2;d2;e2;\na3;b3;c3;d3;e3;"

arr=s.split("\n").map(function(s){return s.split(";").filter(function(x){return x !== ""})})
//[ [ 'a', 'b', 'c', 'd', 'e' ],
//  [ 'a2', 'b2', 'c2', 'd2', 'e2' ],
//  [ 'a3', 'b3', 'c3', 'd3', 'e3' ] ]

s="a;b;c;d;e;\na2;b2;c2;d2;e2;\na3;b3;c3;d3;e3;"

arr=s.split("\n").map(function(s){return s.match(/[^;]+/g)})

import csv 
import sys
file_name = sys.argv[1]
with open(file_name,"rU") as f:
    my_super_array = list(csv.reader(f,delimiter=";"))

>>> import pandas as pd
>>> names = ['0.10', '0.15', '0.20', '0.25', '0.30', '0.35', '0.40']
>>> i = pd.read_csv('test.csv', delim_whitespace=True, names=names)
>>> i
     0.10    0.15    0.20    0.25    0.30    0.35    0.40
0 -0.0011  0.0008  0.0019  0.0034  0.0067  0.0047 -0.0026
1  0.0134 -0.3042 -0.2531 -0.2138 -1.2345 -0.2380  2.0402
2  0.0546  0.2708  0.1738  0.0810  0.8451 -0.0034 -1.4961
3 -0.0226 -0.0052 -0.0021 -0.0024 -0.0023 -0.0745  0.0563
4 -0.0101  0.0108  0.0153  0.0263  0.0491  0.0327 -0.0691
>>> i['0.10'][0]
-0.0011000000000000001

numpy.loadtxt(open("test.csv","rb"),delimiter=",",skiprows=1)

import csv
import numpy
reader=csv.reader(open("test.csv","rb"),delimiter=';')
x=list(reader)
result=numpy.array(x).astype('float')
print result

пример CSV
1;2;3
3;4;5
5;6;7

% ./load.py
[[ 1.  2.  3.]
 [ 3.  4.  5.]
 [ 5.  6.  7.]]