我是nympy的新手,我正在尝试使用以下代码将tab(\ t)分隔的文本文件读入numpy数组矩阵:
train_data = np.genfromtxt('training.txt', dtype=None, delimiter='\t')
文件内容:
38 Private 215646 HS-grad 9 Divorced Handlers-cleaners Not-in-family White Male 0 0 40 United-States <=50K
53 Private 234721 11th 7 Married-civ-spouse Handlers-cleaners Husband Black Male 0 0 40 United-States <=50K
30 State-gov 141297 Bachelors 13 Married-civ-spouse Prof-specialty Husband Asian-Pac-Islander Male 0 0 40 India >50K
我期待的是形状的二维阵列矩阵(3,15)
但是我的上面的代码我只得到一个单行数组(3,)
我不确定为什么每行的15个字段都没有分配一列.
我也尝试使用numpy的loadtxt(),但是它无法处理我的数据的类型转换,即使我给了dtype = None,它试图将字符串转换为默认浮点类型并且失败了.
试过的代码:
train_data = np.loadtxt('try.txt', dtype=None, delimiter='\t')
Error:
ValueError: could not convert string to float: State-gov
有什么指针吗？
谢谢
我对scikit-learn很新,我正在尝试使用这个包来预测收入数据.这可能是一个重复的问题,因为我看到了另一篇文章,但我正在寻找一个简单的例子来理解scikit-learn估算器的预期.
我拥有的数据具有以下结构,其中许多功能是分类的(例如:工作类,教育..)
age: continuous.
workclass: Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked.
fnlwgt: continuous.
education: Bachelors, Some-college, 11th, HS-grad, Prof-school, Assoc-acdm, Assoc-voc, 9th, 7th-8th, 12th, Masters, 1st-4th, 10th, Doctorate, 5th-6th, Preschool.
education-num: continuous.
marital-status: Married-civ-spouse, Divorced, Never-married, Separated, Widowed, Married-spouse-absent, Married-AF-spouse.
occupation: Tech-support, Craft-repair, Other-service, Sales, Exec-managerial, Prof-specialty, Handlers-cleaners, Machine-op-inspct, Adm-clerical, Farming-fishing, Transport-moving, Priv-house-serv, Protective-serv, Armed-Forces.
relationship: Wife, Own-child, Husband, Not-in-family, Other-relative, Unmarried.
race: White, Asian-Pac-Islander, Amer-Indian-Eskimo, Other, Black.
sex: Female, Male.
capital-gain: continuous.
capital-loss: continuous.
hours-per-week: continuous.
native-country: …