入门机器学习时,一些测试数据是网络上的csv文件。这里总结了两种加载csv文件的方式:
1 通过numpy、urllib2加载
import numpy as np import urllib2 url = "http://archive.ics.uci.edu/ml/machine-learning-databases/pima-indians-diabetes/pima-indians-diabetes.data" raw_data = urllib2.urlopen(url) dataset = np.loadtxt(raw_data, delimiter=",") X = dataset[:, 0:7] y = dataset[:, 8]
2 通过pandas加载
import pandas as pd
url = "http://archive.ics.uci.edu/ml/machine-learning-databases/pima-indians-diabetes/pima-indians-diabetes.data" dataFrame = pd.read_csv(url, header=None) dataset = dataFrame.values X = dataset[:, 0:7] y = dataset[:, 8]
3 总结
- np.loadtxt返回的数据类型是:numpy.ndarray
- pd.read_csv返回的数据类型是:pandas.core.frame.DataFrame
- DataFrame.values的类型是:numpy.ndarray
- 所以,本质上,两种方法最后是一样的