Kaggle入门课程之Machine Learning

第一讲

• panda库对csv数据的处理

import pandas as pd
# save filepath to variable for easier access
melbourne_file_path = '../input/melbourne-housing-snapshot/melb_data.csv'
# read the data and store data in DataFrame titled melbourne_data
melbourne_data = pd.read_csv(melbourne_file_path) 
# print a summary of the data in Melbourne data
melbourne_data.describe()

melbourne_data.columns
# 效果显示如下

melbourne_data = melbourne_data.dropna(axis=0)
# 清除行缺失值
melbourne_features = ['Rooms', 'Bathroom', 'Landsize', 'Lattitude', 'Longtitude']
X = melbourne_data[melbourne_features]
# 将特征数据放入x中
X.head()
# 返回数据前5行，用来检测数据格式是否正确

• scikit-learn库建立模型
• • 模型的建立

from sklearn.tree import DecisionTreeRegressor
#设定random_st