| 资料 |
时长( 15:48:52) |
播放量(4119) |
[1.1.1]搭建python环境 |
00:10:19
|
40 |
|
[1.1.2]第一个python程序 |
00:06:21
|
42 |
|
[1.1.3]python的输入和输出 |
00:14:24
|
38 |
|
[1.2.1]python固定语法 |
00:08:57
|
40 |
|
[1.2.2]了解python变量 |
00:11:21
|
35 |
|
[1.2.3]字符串操作 |
00:12:14
|
40 |
|
[1.2.4]常用的操作运算符 |
00:19:24
|
35 |
|
[1.3.1]顺序语句 |
00:09:25
|
50 |
|
[1.3.2]选择语句 |
00:11:07
|
38 |
|
[1.3.3]for循环语句 |
00:12:41
|
36 |
|
[1.3.4]while循环语句 |
00:08:17
|
35 |
|
[1.4.1]python数据结构的组成 |
00:07:39
|
38 |
|
[1.4.2]列表的概念、索引和切片 |
00:10:34
|
38 |
|
[1.4.3]列表的增加和删除 |
00:08:50
|
40 |
|
[1.4.4]列表的修改和副本创建 |
00:07:46
|
41 |
|
[1.4.5列表的其他操作] |
00:07:09
|
47 |
|
[1.4.6]元组的概念和操作 |
00:15:58
|
38 |
|
[1.4.7]字典的创建 |
00:11:01
|
43 |
|
[1.4.8]字典元素的提取 |
00:09:47
|
40 |
|
[1.4.9]字典的增加、删除、修改 |
00:17:49
|
36 |
|
[1.4.10]字典元素的查询和获取 |
00:10:43
|
39 |
|
[1.5.1]自定义函数 |
00:15:16
|
49 |
|
[1.5.2]局部变量和全局变量 |
00:09:12
|
47 |
|
[1.5.3]存储并导入函数模块 |
00:11:35
|
39 |
|
[2.3.3]数组排序 |
00:10:36
|
41 |
|
[2.1.1]创建数组及其属性 |
00:12:40
|
34 |
|
[2.1.2]创建常用数组 |
00:09:13
|
42 |
|
[2.1.3]创建随机数组 |
00:08:26
|
40 |
|
[2.2.1]访问数组 |
00:13:57
|
36 |
|
[2.2.2]改变数组形态 |
00:10:00
|
39 |
|
[2.2.3]数组的组合和分割 |
00:12:24
|
35 |
|
[2.3.1]创建矩阵 |
00:08:38
|
41 |
|
[2.3.2]矩阵计算 |
00:06:43
|
45 |
|
[2.3.3]数组排序 |
00:10:36
|
35 |
|
[3.1.1]Matplotlib可视化入门 |
00:06:00
|
42 |
|
[3.1.2]基础图形绘制 |
00:09:02
|
36 |
|
[3.1.3]多子图布局及绘图流程 |
00:07:16
|
38 |
|
[3.2.1]散点图的绘制 |
00:13:03
|
44 |
|
[3.2.2]折线图的绘制 |
00:11:43
|
33 |
|
[3.2.3]柱形图的绘制 |
00:11:19
|
38 |
|
[3.2.4]饼图及圆环图的绘制 |
00:08:22
|
41 |
|
[4.1.1]Pandas及其文件读写 |
00:13:40
|
37 |
|
[4.1.2]DataFrame数据框的属性及切片 |
00:15:31
|
33 |
|
[4.1.3]DataFrame数据框的修改和删除 |
00:12:59
|
29 |
|
[4.2.1]日期时间型数据 |
00:10:43
|
35 |
|
[4.2.2]时间切片 |
00:07:19
|
39 |
|
[4.2.3]统计及应用 |
00:07:27
|
35 |
|
[4.3.1]分组聚合 |
00:15:08
|
36 |
|
[4.3.2]数据透视表 |
00:06:15
|
34 |
|
[5.1.1]堆叠合并、主键合并、重叠合并 |
00:15:25
|
39 |
|
[5.2.1]检测与处理重复值 |
00:04:29
|
38 |
|
[5.2.2]检测与处理缺失值 |
00:17:59
|
43 |
|
[5.2.3]检测与处理异常值-3s原则 |
00:14:42
|
34 |
|
[5.2.4]检测与处理异常值-箱型图分析 |
00:10:10
|
42 |
|
[5.3.1]离差标准化 |
00:09:48
|
32 |
|
[5.3.2]标准差标准化、小数定标标准化 |
00:12:15
|
38 |
|
[5.4.1]哑变量处理类别型数据 |
00:06:45
|
37 |
|
[5.4.2]离散化连续型数据 |
00:13:50
|
36 |
|
[6.1.1]加载划分数据 |
00:14:47
|
42 |
|
[6.1.2]数据预处理与降维 |
00:11:58
|
48 |
|
[6.2.1]使用skilearn估计器构建聚类模型 |
00:14:27
|
54 |
|
[6.2.2]评价聚类模型 |
00:08:05
|
46 |
|
[6.3.1]使用skilearn估计器构建分类模型 |
00:09:29
|
36 |
|
[6.3.2]评价分类模型 |
00:09:53
|
45 |
|
[6.4.1]使用skilearn估计器构建回归模型 |
00:13:30
|
42 |
|
[6.4.2]评价回归模型 |
00:05:53
|
38 |
|
[7.1]背景介绍 |
00:11:20
|
35 |
|
[7.2]分析目标 |
00:10:00
|
42 |
|
[7.3.1]打开工程&读取数据 |
00:10:06
|
45 |
|
[7.3.2]数据预处理 |
00:08:06
|
37 |
|
[7.3.3]了解数据基础情况 |
00:03:49
|
34 |
|
[7.3.4]统计年度销量和环比增长率 |
00:12:12
|
36 |
|
[7.3.5]年度销量和环比增长数据可视化 |
00:07:52
|
43 |
|
[7.3.6]构建不同车类销量透视表 |
00:07:00
|
33 |
|
[7.3.7]不同车类销量数据可视化 |
00:05:13
|
39 |
|
[7.3.8]不同车类&级别数据可视化结果解读 |
00:04:25
|
59 |
|
[7.3.9]统计年度销售规模和环比增长率 |
00:05:29
|
58 |
|
[7.3.10]年度销售规模和环比增长率数据可视化 |
00:03:14
|
60 |
|
[7.3.11]不同价位车辆销售数据可视化 |
00:04:40
|
60 |
|
[7.3.12]不同价位车辆销量占比分析 |
00:03:56
|
58 |
|
[7.3.13]不同车系销量可视化分析 |
00:05:58
|
57 |
|
[7.3.14]热销品牌top5统计 |
00:08:28
|
52 |
|
[7.4]汽车销售数据可视化分析小结 |
00:04:17
|
61 |
|
[8.1.1]拓展学习资料&Python环境介绍 |
00:14:45
|
56 |
|
[8.1.2]读取数据&修改列名称 |
00:11:15
|
62 |
|
[8.1.3]以PythonConsole方式执行代码 |
00:06:05
|
54 |
|
[8.1.4]缺失值处理 |
00:11:25
|
59 |
|
[8.1.5]重置索引 |
00:11:37
|
69 |
|
[8.2.1]chipotle数据读取及介绍 |
00:06:50
|
54 |
|
[8.2.2]分组聚合 |
00:08:13
|
65 |
|
[8.2.3]数据类型转化 |
00:08:53
|
55 |
|
[8.2.4]求客单价 |
00:07:24
|
71 |
|
[8.3.1]Apple公司股价数据读取及介绍 |
00:07:46
|
65 |
|
[8.3.2]找到最后一个交易日 |
00:11:43
|
50 |
|
[8.3.3]日期探索及可视化 |
00:06:37
|
58 |
