<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/junliucq</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; junliucq]]></copyright><item><title><![CDATA[Dify的安装]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/139333069</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/139333069</guid><author>junliucq</author><pubDate>Fri, 03 Oct 2025 10:02:38 +0800</pubDate><description><![CDATA[Dify安装及换镜像]]></description><category></category></item><item><title><![CDATA[工业化工生产预测案例]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/109007445</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/109007445</guid><author>junliucq</author><pubDate>Sun, 11 Oct 2020 08:20:34 +0800</pubDate><description><![CDATA[2019年天池的一个比赛, 是一个工业化生产预测的项目，任务目标是利用异烟酸生产过程中的各参数， 预测最终异烟酸的收率，从建模的类型来说，这是一个回归问题。数据集包括生产过程中10个步骤的参数， 样本id、A1-A28、B1-B14包括原料，辅料，时间，温度，压强及收率等， 异烟酸的生产过程的流程图如下：





下面介绍一个比赛的冠军解决方案：

https://blog.youkuaiyun.com/wuzhongqiang/article/details/104841251
...]]></description><category></category></item><item><title><![CDATA[pandas加载csv出错：UnicodeDecodeError: ‘utf-8‘ codec can‘t decode byte 0xca in position 0: invalid contin]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/108880156</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/108880156</guid><author>junliucq</author><pubDate>Wed, 30 Sep 2020 09:53:26 +0800</pubDate><description><![CDATA[pandas采用read_csv加载csv文件时出现了编码错误，错误信息如下：

解决方法为，在代码首部加上coding:uft-8的说明，读入csv文件时，采用gbk的编码方式；
全部代码如下：
-- coding : utf-8 --
coding: utf-8
import pandas as pd
#加载时，设置编码格式为encoding=“gbk”
test = pd.read_csv(r’D:\people.csv’, sep=’,’, names=[‘地区’, ‘2016年’, ‘2015年’]]></description><category></category></item><item><title><![CDATA[获取新浪财经股票板块数据的代码]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/103056719</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/103056719</guid><author>junliucq</author><pubDate>Wed, 13 Nov 2019 20:31:14 +0800</pubDate><description><![CDATA[importrequests
res=requests.get('http://vip.stock.finance.sina.com.cn/q/view/newSinaHy.php')
res.encoding='gbk'
res.text
#%%
importre
table_text=re.findall('\{.*\}',res.text)[0]
table_text
#%...]]></description><category></category></item><item><title><![CDATA[mysql5.5 插入中文会报错如何解决？]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/102321104</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/102321104</guid><author>junliucq</author><pubDate>Mon, 07 Oct 2019 19:05:26 +0800</pubDate><description><![CDATA[1)打开安装目录下的my.ini文件

我的是：C:\Program Files\MySQL\MySQL Server 5.5下面，修改如下：



2修改完my.ini文件以后，在cmd窗口下，登录mysql

3）输入命令

mysql &gt; show variables like 'character%';

结果如下：





4）在mysql里面修改对应表的字符集



5）通过...]]></description><category></category></item><item><title><![CDATA[python pip 安装一些包找不到的问题 Could not find a version that satisfies....]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/90760922</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/90760922</guid><author>junliucq</author><pubDate>Mon, 03 Jun 2019 23:21:20 +0800</pubDate><description><![CDATA[https://blog.youkuaiyun.com/csdn_am/article/details/79924744
]]></description><category></category></item><item><title><![CDATA[多维数据仓库建模（使用SQL Server Data Tools）]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/89328784</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/89328784</guid><author>junliucq</author><pubDate>Tue, 16 Apr 2019 10:42:41 +0800</pubDate><description><![CDATA[内容：

如何在 Analysis Services 的 SQL Server Data Tools项目中定义数据源、数据源视图、维度、属性、属性关系、层次结构和多维数据集。
如何通过将 Analysis Services 项目部署到 Analysis Services实例来查看多维数据集和维度数据


制作步骤：

https://blog.youkuaiyun.com/weixin_44071398/a...]]></description><category></category></item><item><title><![CDATA[Excel或者ECharts的可视化实践（sakila数据库）]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/89257227</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/89257227</guid><author>junliucq</author><pubDate>Fri, 12 Apr 2019 20:41:50 +0800</pubDate><description><![CDATA[采用excel或者Echarts对sakila数据库的数据进行可视化。

https://blog.youkuaiyun.com/qq_38967136/article/details/89058177
]]></description><category></category></item><item><title><![CDATA[SQL SERVER BI 入门]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/89226186</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/89226186</guid><author>junliucq</author><pubDate>Fri, 12 Apr 2019 09:59:31 +0800</pubDate><description><![CDATA[https://blog.youkuaiyun.com/maddemon/article/details/8094360



https://blog.youkuaiyun.com/maddemon/article/details/8244000
]]></description><category></category></item><item><title><![CDATA[Tableau实践案例：展示sakila数据库中顾客的城市分布沿时间变化情况]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/89040965</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/89040965</guid><author>junliucq</author><pubDate>Fri, 05 Apr 2019 10:44:17 +0800</pubDate><description><![CDATA[为了形象化的展示sakila数据库中，不同城市客户分布随时间的变化情况，采用tableau实现了该数据的可视化。

最后的情况如下

sakila顾客变化具体实现步骤如下：

https://blog.youkuaiyun.com/qq_43533400/article/details/89007216

https://blog.youkuaiyun.com/qq_43533400/article/details/89...]]></description><category></category></item><item><title><![CDATA[Arby’s 使用 Tableau 绘制零售成功案例]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/88983545</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/88983545</guid><author>junliucq</author><pubDate>Tue, 02 Apr 2019 22:49:22 +0800</pubDate><description><![CDATA[https://www.tableau.com/zh-cn/solutions/customer/renovating-retail-success-arbys-restaurant-group
]]></description><category></category></item><item><title><![CDATA[BI领军者之一Tableau试用浅谈]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/88983500</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/88983500</guid><author>junliucq</author><pubDate>Tue, 02 Apr 2019 22:47:29 +0800</pubDate><description><![CDATA[下图是最新的Gartner BI Magic Quadrant，其中领军者之一的Tableau表现的异常突出，执行力象限上直接甩开其它产品一条街，前瞻性象限上略微超越了MSBI，怀着无比的好奇心，特意去Tableau官网下载了Desktop试用版体验一把，从种种细节中能够感受到浓浓的情怀，产品的确极具人性化，甚至官网的教学视频都是略带播音腔的中文语音，但为了客观分析这款产品的用户体验，我没有跟着视...]]></description><category></category></item><item><title><![CDATA[Tableau 可视化十大案例，原来数据还能长得这么好看]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/88983335</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/88983335</guid><author>junliucq</author><pubDate>Tue, 02 Apr 2019 22:39:14 +0800</pubDate><description><![CDATA[早在2015年就与Mapbox 进行了整合的Tableau，一直都是数据可视化领域的佼佼者。Mapbox的很多工程师们，也都在使用Tableau 进行数据可视化处理。

几天前，我们的工程师Allan Walker在官方博客Point of Interest上发布了自己近几年来最喜欢的10个数据可视化案例，不看不知道，原来数据还能这么美！一起来观赏下，扶好下巴。




作者：Mapbox
链接...]]></description><category></category></item><item><title><![CDATA[可视化交互技术案例：MapView监听地图平移和缩放]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/88883813</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/88883813</guid><author>junliucq</author><pubDate>Fri, 29 Mar 2019 09:02:39 +0800</pubDate><description><![CDATA[https://blog.youkuaiyun.com/123bobo/article/details/7274618

http://visualdataweb.de/webvowl/#
]]></description><category></category></item><item><title><![CDATA[可视化交互技术案例：高德JS API——改变地图中心点及缩放级别]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/88883796</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/88883796</guid><author>junliucq</author><pubDate>Fri, 29 Mar 2019 09:01:25 +0800</pubDate><description><![CDATA[https://blog.youkuaiyun.com/brook_/article/details/80793740
]]></description><category></category></item><item><title><![CDATA[Echarts dataZoom，开发全解+完美注释]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/88883775</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/88883775</guid><author>junliucq</author><pubDate>Fri, 29 Mar 2019 08:59:52 +0800</pubDate><description><![CDATA[https://blog.youkuaiyun.com/liq816/article/details/78027333
]]></description><category></category></item><item><title><![CDATA[Python画二维图和三维图]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/88883748</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/88883748</guid><author>junliucq</author><pubDate>Fri, 29 Mar 2019 08:57:22 +0800</pubDate><description><![CDATA[https://blog.youkuaiyun.com/u010916338/article/details/84969807
]]></description><category></category></item><item><title><![CDATA[30 个最好的数据可视化工具推荐]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/88883727</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/88883727</guid><author>junliucq</author><pubDate>Fri, 29 Mar 2019 08:55:51 +0800</pubDate><description><![CDATA[https://blog.youkuaiyun.com/gdp12315_gu/article/details/44080655
]]></description><category></category></item><item><title><![CDATA[Tableau学习（二）：系统教程]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/88883572</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/88883572</guid><author>junliucq</author><pubDate>Fri, 29 Mar 2019 08:39:36 +0800</pubDate><description><![CDATA[https://www.w3cschool.cn/tableau/tableau_get_started.html
]]></description><category></category></item><item><title><![CDATA[ETL示例解决方案 —— Sakila示例之load_fact_rental转换（笔记九）]]></title><link>https://blog.youkuaiyun.com/junliucq/article/details/88836329</link><guid>https://blog.youkuaiyun.com/junliucq/article/details/88836329</guid><author>junliucq</author><pubDate>Wed, 27 Mar 2019 09:13:42 +0800</pubDate><description><![CDATA[load_fact_rental转换

load_fact_rental转换是作业load_rentals最后的转换。

https://blog.youkuaiyun.com/qq_38241583/article/details/88831406
]]></description><category></category></item></channel></rss>