一：数据收集
| 变量名 | 含义 |
| fixed acidity | 固定酸度 |
| volatile acidity | 挥发性酸度 |
| citric acidity | 柠檬酸 |
| residual sugar | 剩余糖 |
| chlorides | 氧化物 |
| free sulfur dioxide | 游离的二氧化碳 |
| total sulfur dioxide | 总二氧化硫 |
| density | 密度 |
| PH | 值 |
| sulphates | 酸碱盐 |
| alcohol | 酒精 |
| quality | 品质 |
实训之前我们需要先下载数据，我这里是下载完之后文件名是：white_wine.csv
二：读取数据
1：显示前5行数据
import csv f = open("white_wine.csv",'r') reader = csv.reader(f) data = [] for row in reader: data.append(row) for i in range(5): print(data[i]) f.close()
三：数据处理
1：查看白葡萄酒总共分为几种品质等级
import csv f = open("white_wine.csv",'r') reader = csv.reader(f) data = [] for row in reader: data.append(row) quality_list = [] for row in data[1:]: quality_list.append(int(row[ -1])) quality_count = set(quality_list) print("白葡萄酒共有%s种等级, 分别为：%r" %(len(quality_count), quality_count))
白葡萄酒共有7种等级, 分别为：{3, 4, 5, 6, 7, 8, 9}
2：统计等级及其数量
import csv f = open("white_wine.csv",'r') reader = csv.reader(f) data = [] for row in reader: data.append(row) content_dict = {} for row in data[1:]: quality = int(row[-1]) if quality not in content_dict.keys(): content_dict[quality] = [row] else: content_dict[quality].append(row) for key in content_dict: print('等级为%d， 数量为%d' %(key, len(content_dict[key]))) f.close()
等级为6， 数量为1539 等级为5， 数量为1020 等级为7， 数量为616 等级为8， 数量为123 等级为4， 数量为115 等级为3， 数量为14 等级为9， 数量为4
条形图展示
import csv import numpy as np import matplotlib.pyplot as plt f = open("white_wine.csv",'r') reader = csv.reader(f) data = [] for row in reader: data.append(row) content_dict = {} for row in data[1:]: quality = int(row[-1]) if quality not in content_dict.keys(): content_dict[quality] = [row] else: content_dict[quality].append(row) x = [] y = [] for key in content_dict: x.append(key) y.append(len(content_dict[key])) plt.bar(x, y) plt.show()
3：计算每个数据集中fixed acidity的均值
import csv f = open("white_wine.csv",'r') reader = csv.reader(f) data = [] for row in reader: data.append(row) content_dict = {} for row in data[1:]: quality = int(row[-1]) if quality not in content_dict.keys(): content_dict[quality] = [row] else: content_dict[quality].append(row) mean_list = [] for key,value in content_dict.items(): sum = 0 for row in value: sum += float(row[0]) mean_list.append((key, sum / len(value))) for item in mean_list: print(item[0],",", item[1])
6 : 6.812085769980511 5 : 6.907843137254891 7 : 6.755844155844158 8 : 6.708130081300811 4 : 7.052173913043476 3 : 7.535714285714286 9 : 7.5
