python – 如何将csv字符串转换为pandas中的列表？

我正在使用具有以下格式的csv文件：

"Id","Sequence"
3,"1,3,13,87,1053,28576,2141733,508147108,402135275365,1073376057490373,9700385489355970183,298434346895322960005291,31479360095907908092817694945,11474377948948020660089085281068730"
7,"1,2,1,5,5,1,11,16,7,1,23,44,30,9,1,47,112,104,48,11,1,95,272,320,200,70,13,1,191,640,912,720,340,96,15,1,383,1472,2464,2352,1400,532,126,17,1,767,3328,6400,7168,5152,2464,784,160,19,1,1535,7424"
8,"1,2,4,5,8,10,16,20,32,40,64,80,128,160,256,320,512,640,1024,1280,2048,2560,4096,5120,8192,10240,16384,20480,32768,40960,65536,81920,131072,163840,262144,327680,524288,655360,1048576,1310720,2097152"
11,"1,8,25,83,274,2275,132224,1060067,3312425,10997342,36304451,301432950,17519415551,140456757358,438889687625,1457125820233,4810267148324,39939263006825,2321287521544174,18610239435360217"

我想将其读入数据框,其类型为df [‘Id’]为类似整数,df [‘Sequence’]的类型为list-like.

我目前有以下kludgy代码：

def clean(seq_string):
    return list(map(int, seq_string.split(',')))

# Read data
training_data_file = "data/train.csv"    
train = pd.read_csv(training_data_file)
train['Sequence'] = list(map(clean, train['Sequence'].values))

这似乎有效,但我觉得使用pandas和numpy可以原生地实现.

有人有推荐吗？

解决方法:

您可以为Sequence列指定converter：

converters: dict, default None

Dict of functions for converting
values in certain columns. Keys can either be integers or column
labels

train = pd.read_csv(training_data_file, converters={'Sequence': clean})