Python 从文件加载数据集，与 sklearn/numpy 一起使用，包括标签
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Loading a dataset from file, to use with sklearn/numpy, including labels
提问by shn
I saw that with sklearn we can use some predefined datasets, for example mydataset = datasets.load_digits()the we can get an array (a numpy array?) of the dataset mydataset.dataand an array of the corresponding labels mydataset.target. However I want to load my own dataset to be able to use it with sklearn. How and in which format should I load my data ? My file have the following format (each line is a data-point):
我看到使用 sklearn 我们可以使用一些预定义的数据集，例如mydataset = datasets.load_digits()我们可以获得数据集的数组（numpy 数组？）mydataset.data和相应标签的数组mydataset.target。但是我想加载我自己的数据集以便能够将它与 sklearn 一起使用。我应该如何以及以哪种格式加载我的数据？我的文件具有以下格式（每一行都是一个数据点）：
-0.2080,0.3480,0.3280,0.5040,0.9320,1.0000,label1
-0.2864,0.1992,0.2822,0.4398,0.7012,0.7800,label3
...
...
-0.2348,0.3826,0.6142,0.7492,0.0546,-0.4020,label2
-0.1856,0.3592,0.7126,0.7366,0.3414,0.1018,label1
采纳答案by Ando Saabas
You can use numpy's genfromtxt function to retrieve data from the file(http://docs.scipy.org/doc/numpy/reference/generated/numpy.genfromtxt.html)
您可以使用 numpy 的 genfromtxt 函数从文件中检索数据（http://docs.scipy.org/doc/numpy/reference/generated/numpy.genfromtxt.html）
import numpy as np
mydata = np.genfromtxt(filename, delimiter=",")
However, if you have textual columns, using genfromtxt is trickier, since you need to specify the data types.
但是，如果您有文本列，则使用 genfromtxt 会更棘手，因为您需要指定数据类型。
It will be much easier with the excellent Pandas library (http://pandas.pydata.org/)
使用优秀的 Pandas 库（http://pandas.pydata.org/）会容易得多
import pandas as pd
mydata = pd.read_csv(filename)
target = mydata["Label"] #provided your csv has header row, and the label column is named "Label"
#select all but the last column as data
data = mydata.ix[:,:-1]
