动漫评分数据分析与可视化 与 IT行业招聘数据分析与可视化

数据可视化课设

1，动漫评分数据分析与可视化

可视化地址预览

2，IT行业招聘数据分析与可视化

可视化地址预览

1，动漫评分数据分析与可视化

1.1 数据抓取

BilibiliSpider

将抓取文件上传到${HIVE_HOME}/mydata目录下

1.2 Hive表创建与导入

Hive表字段信息

1.2.1 创建cartoon_info表并导入数据

CREATE EXTERNAL TABLE Json(
 data string
)

加载数据到Json表中备用

load data local inpath 'mydata/infos_total.json' overwrite into table Json;

创建cartoon_info表

drop table if exists cartoon_info;
CREATE EXTERNAL TABLE cartoon_info(
`ssid` string,
`cartoon` string,
`views` bigint,
`coins` int,
`follow` int,
`series_follow` int,
`danmakus` int,
`likes` int,
`favorite` int,
`favorites` int,
`reply` int,
`share` int,
`cover` string,
`url` string,
`episodes` int,
`count` int,
`is_finish` int,
`pub_time` TIMESTAMP,
`media_tags` string,
`voice_actor` string,
`score` float
)
stored as parquet
location '/warehouse/cartoon_info';

使用Json解析插入数据，详情请看: Hive之Json解析(普通Json和Json数组)

insert overwrite table cartoon_info

select json_tuple(json,'ssid' ,'cartoon' ,'views' ,'coins' ,'follow' ,'series_follow' ,'danmakus' ,'likes' ,'favorite' ,'favorites' ,'reply' ,'share' ,'cover' ,'url','episodes' ,'count' ,'is_finish' ,'pub_time','media_tags','voice_actor','score') from (
select explode(split(regexp_replace(regexp_replace(data,'\\[|\\]',''),'\\}\\, \\{','\\}\\;\\{' )  ,'\\;'))  as json from Json
)a;

1.2.2 创建cartoon_comments表

CREATE EXTERNAL TABLE Json2(
 data string
);

加载数据到Json2表中备用

load data local inpath 'mydata/comments_total.json' overwrite into table Json2;

创建cartoon_comments表并导入数据

drop table if exists cartoon_comments;
CREATE EXTERNAL TABLE cartoon_comments(
`mid` string,
`uname` string,
`ssid` string,
`message` string,
`like` int,
`dt` timestamp
)
stored as parquet
location '/warehouse/cartoon_comments';

使用Json解析插入数据，详情请看: Hive之Json解析(普通Json和Json数组)

insert overwrite table cartoon_comments

select json_tuple(json,'mid' ,'uname' ,'ssid' ,'message' ,'like' ,'dt' ) from (select explode(split(regexp_replace(regexp_replace(data,'\\[|\\]',''),'\\}\\, \\{','\\}\\;\\;\\;\\{' )  ,'\\;\\;\\;')) as json from Json2)a;

二 IT行业招聘数据分析与可视化

1.1 数据抓取

ITJobSpider

1，需要登录拉勾网！！请注意替换个人Cookie且Cookie中不要有中文，否则会报错；如果Cookie不生效，请打开拉勾网其他页面获取Cookie.

2，若报错请打开拉勾网查看是否需要验证

将抓取文件上传到${HIVE_HOME}/mydata目录下

2.1 Hive表创建与导入

Hive表字段信息

CREATE EXTERNAL TABLE Json3(
 data string
)

加载数据到Json3表中备用

load data local inpath 'mydata/jobsInfo.json' overwrite into table Json3;

2.1.1 创建jobs_info表并导入数据

drop table if exists jobs_info;
CREATE EXTERNAL TABLE jobs_info(
`job` string,
`keyword` string,
`place` string,
`requirement` string,
`salary` string,
`tags` string,
`welfare` string,
`pubtime` date
)
stored as parquet
location '/warehouse/jobs_info';

使用Json解析插入数据，详情请看: Hive之Json解析(普通Json和Json数组)

insert overwrite table jobs_info

select json_tuple(json,'job' ,'keyword' ,'place' ,'requirement' ,'salary' ,'tags' ,'welfare' ,'pubtime') from (
select explode(split(regexp_replace(regexp_replace(data,'\\[|\\]',''),'\\}\\, \\{','\\}\\;\\{' )  ,'\\;'))  as json from Json3
)a;

3，数据分析与可视化

3.1 Pyhive连接Hive教程:

Python安装sasl,thrift,thrift-sasl 并连接PyHive

连接代码: Pyhive

3.2 数据分析与可视化

安装必要的包

pip install pandas==0.23.4
pip install pyecharts==1.9.1
pip install matplotlib==3.5.1
pip install numpy==1.18.5
pip install jieba==0.42.1
pip install squarify==0.4.3

1，动漫评分数据分析与可视化 数据分析代码：bilibili

代码包含了["玫瑰图","词云图","雷达图","散点图","漏斗图","环图","条形图","树形图","火柴杆图","子图"]共10个类型的图，包含了4个matplotlib图以及6个pyecharts图的简单分析。

2，IT行业招聘数据分析与可视化 数据分析代码：IT

代码包含了["玫瑰图","词云图","象形图","散点图","漏斗图","环图","条形图","树形图","火柴杆图","子图"]共10个类型的图，包含了4个matplotlib图以及6个pyecharts图的简单分析。