数据挖掘(第四周)
# 代码8-1 查看数据特征 import numpy as np import pandas as pd inputfile = r'C:\Users\86138\Downloads\data\数据挖掘与分析\GoodsOrder.csv' # 输入的数据文件 data = pd.read_csv(inputfile,encoding = 'gbk') # 读取数据 data .info() # 查看数据属性 data = data['id'] description = [data.count(),data.min(), data.max()] # 依次计算总数、最小值、最大值 description = pd.DataFrame(description, index = ['Count','Min', 'Max']).T # 将结果存入数据框 print('描述性统计结果_3039:\n',np.round(description)) # 输出结果
![](https://img2023.cnblogs.com/blog/2530755/202303/2530755-20230315145921141-124112907.png)
# 代码8-2 分析热销商品 # 销量排行前10商品的销量及其占比 import pandas as pd inputfile = r'C:\Users\86138\Downloads\data\数据挖掘与分析\GoodsOrder.csv' # 输入的数据文件 data = pd.read_csv(inputfile,encoding = 'gbk') # 读取数据 group = data.groupby(['Goods']).count().reset_index() # 对商品进行分类汇总 sorted=group.sort_values('id',ascending=False) print('销量排行前10商品的销量_3039:\n', sorted[:10]) # 排序并查看前10位热销商品 # 画条形图展示出销量排行前10商品的销量 import matplotlib.pyplot as plt x=sorted[:10]['Goods'] y=sorted[:10]['id'] plt.figure(figsize = (8, 4)) # 设置画布大小 plt.barh(x,y) plt.rcParams['font.sans-serif'] = 'SimHei' plt.xlabel('销量') # 设置x轴标题 plt.ylabel('商品类别') # 设置y轴标题 plt.title('商品的销量TOP10_3039') # 设置标题 plt.savefig(r'C:\Users\86138\Downloads\data\数据挖掘与分析\top10_3039.png') # 把图片以.png格式保存 plt.show() # 展示图片 # 销量排行前10商品的销量占比 data_nums = data.shape[0] for idnex, row in sorted[:10].iterrows(): print(row['Goods'],row['id'],row['id']/data_nums)
![](https://img2023.cnblogs.com/blog/2530755/202303/2530755-20230315150044121-1357253828.png)
条形图如下:
# 代码8-3 各类别商品的销量及其占比 import pandas as pd inputfile1 = r'C:\Users\86138\Downloads\data\数据挖掘与分析\GoodsOrder.csv' inputfile2 = r'C:\Users\86138\Downloads\data\数据挖掘与分析\GoodsTypes.csv' data = pd.read_csv(inputfile1,encoding = 'gbk') types = pd.read_csv(inputfile2,encoding = 'gbk') # 读入数据 group = data.groupby(['Goods']).count().reset_index() sort = group.sort_values('id',ascending = False).reset_index() data_nums = data.shape[0] # 总量 del sort['index'] sort_links = pd.merge(sort,types) # 合并两个datafreame 根据type # 根据类别求和,每个商品类别的总量,并排序 sort_link = sort_links.groupby(['Types']).sum().reset_index() sort_link = sort_link.sort_values('id',ascending = False).reset_index() del sort_link['index'] # 删除“index”列 # 求百分比,然后更换列名,最后输出到文件 sort_link['count'] = sort_link.apply(lambda line: line['id']/data_nums,axis=1) sort_link.rename(columns = {'count':'percent'},inplace = True) print('各类别商品的销量及其占比_3039:\n',sort_link) outfile1 = r'C:\Users\86138\Downloads\data\数据挖掘与分析\percent.csv' sort_link.to_csv(outfile1,index = False,header = True,encoding='gbk') # 保存结果 # 画饼图展示每类商品销量占比 import matplotlib.pyplot as plt data = sort_link['percent'] labels = sort_link['Types'] plt.figure(figsize=(8, 6)) # 设置画布大小 plt.pie(data,labels=labels,autopct='%1.2f%%') plt.rcParams['font.sans-serif'] = 'SimHei' plt.title('每类商品销量占比_3039') # 设置标题 plt.savefig(r'C:\Users\86138\Downloads\data\数据挖掘与分析\persent_3039.png') # 把图片以.png格式保存 plt.show()
![](https://img2023.cnblogs.com/blog/2530755/202303/2530755-20230315150319413-565729889.png)
饼状图如下:
# 代码8-4 酒精饮料内部商品的销量及其占比 # 先筛选“酒精饮料”类型的商品,然后求百分比,然后输出结果到文件。 selected = sort_links.loc[sort_links['Types'] == '酒精饮料'] # 挑选商品类别为“非酒精饮料”并排序 child_nums = selected['id'].sum() # 对所有的“酒精饮料”求和 selected['child_percent'] = selected.apply(lambda line: line['id']/child_nums,axis = 1) # 求百分比 selected.rename(columns = {'id':'count'},inplace = True) print('酒精饮料内部商品的销量及其占比_3039:\n',selected) outfile2 = r'C:\Users\86138\Downloads\data\数据挖掘与分析\child_percent.csv' sort_link.to_csv(outfile2,index = False,header = True,encoding='gbk') # 输出结果 # 画饼图展示酒精饮品内部各商品的销量占比 import matplotlib.pyplot as plt data = selected['child_percent'] labels = selected['Goods'] plt.figure(figsize = (8,6)) # 设置画布大小 explode = (0.02,0.03,0.04,0.05,0.06,0.07,0.08,0.08,0.3,0.1,0.3) # 设置每一块分割出的间隙大小 plt.pie(data,explode = explode,labels = labels,autopct = '%1.2f%%', pctdistance = 1.1,labeldistance = 1.2) plt.rcParams['font.sans-serif'] = 'SimHei' plt.title("酒精饮料内部各商品的销量占比_3039") # 设置标题 plt.axis('equal') plt.savefig( r'C:\Users\86138\Downloads\data\数据挖掘与分析\child_percent_3039.png') # 保存图形 plt.show() # 展示图形
![](https://img2023.cnblogs.com/blog/2530755/202303/2530755-20230315151050522-1666384292.png)
饼图如下:
![](https://img2023.cnblogs.com/blog/2530755/202303/2530755-20230315150930835-1944927973.png)
# 代码8-4 非酒精饮料内部商品的销量及其占比 # 先筛选“非酒精饮料”类型的商品,然后求百分比,然后输出结果到文件。 selected = sort_links.loc[sort_links['Types'] == '非酒精饮料'] # 挑选商品类别为“非酒精饮料”并排序 child_nums = selected['id'].sum() # 对所有的“非酒精饮料”求和 selected['child_percent'] = selected.apply(lambda line: line['id']/child_nums,axis = 1) # 求百分比 selected.rename(columns = {'id':'count'},inplace = True) print('非酒精饮料内部商品的销量及其占比_3039:\n',selected) outfile2 = r'C:\Users\86138\Downloads\data\数据挖掘与分析\child_percent.csv' sort_link.to_csv(outfile2,index = False,header = True,encoding='gbk') # 输出结果 # 画饼图展示非酒精饮品内部各商品的销量占比 import matplotlib.pyplot as plt data = selected['child_percent'] labels = selected['Goods'] plt.figure(figsize = (8,6)) # 设置画布大小 explode = (0.02,0.03,0.04,0.05,0.06,0.07,0.08,0.08,0.3,0.1,0.3) # 设置每一块分割出的间隙大小 plt.pie(data,explode = explode,labels = labels,autopct = '%1.2f%%', pctdistance = 1.1,labeldistance = 1.2) plt.rcParams['font.sans-serif'] = 'SimHei' plt.title("非酒精饮料内部各商品的销量占比_3039") # 设置标题 plt.axis('equal') plt.savefig( r'C:\Users\86138\Downloads\data\数据挖掘与分析\child_percent_3039.png') # 保存图形 plt.show() # 展示图形
![](https://img2023.cnblogs.com/blog/2530755/202303/2530755-20230315151328058-431788435.png)
饼图如下:
![](https://img2023.cnblogs.com/blog/2530755/202303/2530755-20230315151243416-1287861933.png)
# 代码8-5 数据转换 import pandas as pd inputfile=r'C:\Users\86138\Downloads\data\数据挖掘与分析\GoodsOrder.csv' data = pd.read_csv(inputfile,encoding = 'gbk') # 根据id对“Goods”列合并,并使用“,”将各商品隔开 data['Goods'] = data['Goods'].apply(lambda x:','+x) data = data.groupby('id').sum().reset_index() # 对合并的商品列转换数据格式 data['Goods'] = data['Goods'].apply(lambda x :[x[1:]]) data_list = list(data['Goods']) # 分割商品名为每个元素 data_translation = [] for i in data_list: p = i[0].split(',') data_translation.append(p) print('数据转换结果的前5个元素_3039:\n', data_translation[0:5])
![](https://img2023.cnblogs.com/blog/2530755/202303/2530755-20230315151443947-317156684.png)
posted on 2023-03-15 15:15 蓝螃蟹Karry0921 阅读(22) 评论(0) 编辑 收藏 举报