- 文章信息
- 作者: kaiwu
- 点击数:70
2个数据文件
https://od.lk/d/178104333_aSUjh/analytics_IMTH.xlsx
https://od.lk/s/178104335_iQ8FY/hotel_revenue_data_RevPAR.xls
任务1:
1.1访问辽宁统计年鉴,下载各城市接待外国游客数据
https://tjj.ln.gov.cn/tjj/tjxx/xxcx/tjnj/otherpages/2021/zk/indexce.htm
1.2使用【liaoning_map】绘制辽宁省接待外国游客情况的地图
https://od.lk/d/178104333_aSUjh/analytics_IMTH.xlsx
(1)转换为万人次,小数点后保留1位有效数字
(2)根据接待游客数,降序排序
(3)绘制地图
--------------
任务2:Excel数据透视表复习
https://od.lk/d/178104333_aSUjh/analytics_IMTH.xlsx
2.1用数据透视表,统计出【区域】变量中【东北】所占百分比,输入微信群
2.2绘制【区域】饼图,粘贴到微信群
任务3:Excel数据透视表复习
https://od.lk/d/178104333_aSUjh/analytics_IMTH.xlsx
3.1用数据透视表,生成列联表(crosstable):行是【地区】,列是【性别】
3.2计算百分比: 总体百分比,行百分比,列百分比
任务4:
https://od.lk/d/178104333_aSUjh/analytics_IMTH.xlsx
worksheet: multi-response
4.1使用countif函数对多选题进行统计
4.2计算【样本百分比】
4.3计算【应答】百分比
任务5:
https://od.lk/s/178104335_iQ8FY/hotel_revenue_data_RevPAR.xls
RevPar
Revenue per available room (RevPAR) is a performance metric used in the hotel industry and is calculated by multiplying a hotel's average daily room rate (ADR) by its occupancy rate. It may also be calculated by dividing a hotel's total room revenue by the total number of available rooms in the period being measured.
每间可用客房收入 (RevPAR) 是酒店行业使用的绩效指标,其计算方法是将酒店的平均每日房价 (ADR) 乘以入住率(occupancy rate)。 它也可以通过将酒店的总客房收入除以测量期间的可用客房总数来计算。
Read more: Revenue Per Available Room - RevPAR Definition | Investopedia http://www.investopedia.com/terms/r/revpar.asp#ixzz4QJ1nJ44Y
Follow us: Investopedia on Facebook
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RevPAR=Rooms Revenue /Rooms Available
RevPAR is rooms revenue per available room (total rooms inventory),
Rooms Revenue is the revenue generated by room sales
房均收入(RevPAR)是每间可用客房的销售收入
客房收入是客房销售产生的收入
可用客房(Room Available )是特定时间点上酒店可用于销售的客房数量
---
TRevPAR=Total Revenue/ Available Rooms
房均总收入(TRevPAR )is 是平均每间可用客房的总收入。
总收入是酒店产生的净收入。
可用客房是特定时间点上酒店可用于销售的客房数量。
total net revenue per available room .
Total Revenue is the net revenue generated by the hotel .
Rooms Available is the number of rooms available for sale in the time period.
5.1计算【客房出租率OR】
5.2计算【日均房费ADR】
5.3计算【日均每间客房收益RevPar】——第1种算法
5.4计算【日均每间客房收益RevPar】——第2种算法
5.5计算【房均总收入(TRevPAR )】
- 文章信息
- 作者: kaiwu
- 点击数:207
lecture
https://od.lk/d/173175613_8VzU4/EN_PHD_data_science_and_tourism2022April15.pdf
R markdown file for yelp data analysis
https://od.lk/d/173175650_RPdXA/yelp_dataset20210914popular_user.Rmd
Cilliers, P. (1998). Complexity and Postmodernism: Understanding Complex Systems. Routledge.
http://libgen.st/book/index.php?md5=CDFE4CD61962B65EA2DE564B7D943E79
https://zh.book4you.org/book/905438/ace21e
https://www.bibliometrix.org/vignettes/Introduction_to_bibliometrix.html
bibliometric data : big data studies in tourism and hospitality
https://od.lk/d/172672725_Ma5xJ/M699.rda
if(!isTRUE(require("bibliometrix"))){install.packages("bibliometrix")}
if(!isTRUE(require("httpuv"))){install.packages("httpuv")}
if(!isTRUE(require("shinycssloaders"))){install.packages("shinycssloaders")}# load bibliometrix and biblioshiny
library(bibliometrix)
library(shinycssloaders)
biblioshiny()
https://www.sciencedirect.com/science/article/abs/pii/S1567422316300503?via%3Dihub
https://sci-hub.se/10.1016/j.elerap.2016.09.005
yelp data (in R format) 2022 March 29
https://od.lk/d/173175614_j5pvi/cafe_business.rda
https://od.lk/d/173175647_0KK6t/cafe_reviews.rda
- 文章信息
- 作者: kaiwu
- 点击数:198
1.下载安装zotero
https://www.zotero.org/download/
1.1 zotero standalone
https://www.zotero.org/download/client/dl?channel=release&platform=win32&version=5.0.96.3
或者
https://drfs.ctcontents.com/file/20727931/555470602/16d70d/opensoftware/Zotero-5.0.96.3_setup.exe
1.2 zotero connector
1.2edge1 微软edge网页浏览器下载
https://www.microsoft.com/zh-cn/edge
或者
https://dl.pconline.com.cn/download/372423.html
1.2edge2 微软edge网页浏览器的zotero connector
https://microsoftedge.microsoft.com/addons/detail/zotero-connector/nmhdhpibnnopknkmonacoephklnflpho
-----
1.2firefox1 火狐浏览器下载
https://drfs.ctcontents.com/file/20727931/555470615/a6a1fc/opensoftware/Firefox-latest%20%281%29.exe
1.2firefox2火狐浏览器的zotero connector
https://drfs.ctcontents.com/file/20727931/555470652/a23fd8/opensoftware/Zotero_Connector-5.0.92.xpi
任务1 导入书籍the pratice of social research的信息到zotero数据库
http://kaiwu.city/index.php/10-book-the-practice-of-socia-research
https://book.douban.com/subject/26894285/
任务2:导入书籍:使用isbn
http://kaiwu.city/index.php/11-book-service-management
Service Management: Operations, Strategy, Information Technology
9th Edition
ISBN10: 1259784630
ISBN13: 9781259784637
Copyright: 2019
任务3:导入一本中文书籍的信息
http://kaiwu.city/index.php/1-tdoulie
中国旅游出版社:西方休闲研究经典译丛
http://book.douban.com/series/12463
任务4:导入一本中文书籍的信息
桑杰夫·波多洛伊, 詹姆斯·A.菲茨西蒙斯, & 莫娜·J.菲茨西蒙斯. (2020). 服务管理:运作、战略与信息技术 (张金成、范秀成、杨坤,翻译; 原书第9版). 机械工业出版社
任务5:导入多本书籍信息
https://www.amazon.com/或者https://z.cn/
输入Aspects of Tourism进行检索
https://www.multilingual-matters.com/page/series-results/aspects-of-tourism/
Aspects of Tourism
Chris Cooper (Leeds Beckett University, UK)
C. Michael Hall (University of Canterbury, New Zealand)
Dallen J. Timothy (Arizona State University, USA)
Aspects of Tourism is an innovative, multifaceted series, which comprises authoritative reference handbooks on global tourism regions, research volumes, texts and monographs. It is designed to provide readers with the latest thinking on tourism world-wide and in so doing will push back the frontiers of tourism knowledge. The series also introduces a new generation of international tourism authors writing on leading edge topics.
任务6:导入中文论文信息
工业旅游具身体验模型:具身障碍、障碍移除和具身实现
任务7:导入多篇中文论文
任务7:导入1篇英文论文
https://www.sciencedirect.com/
检索
Rethinking Authenticity in Tourism Experience
任务8:使用sci-hub下载论文全文
Sci-hub
https://sci-hub.se/
https://sci-hub.st/
https://sci-hub.ru/
Severt, D. E., Tesone, D. V., Bottorff, T. J., & Carpenter, M. L. (2009). A World Ranking of the Top 100 Hospitality and Tourism Programs. Journal of Hospitality & Tourism Research, 33(4), 451–470. https://doi.org/10.1177/1096348009344210
- 文章信息
- 作者: kaiwu
- 点击数:197
2021年江苏省高职旅游类专业教师研修班
时间: | 2021年8月7日 14.00-17.00 |
主题: | 基于大数据分析的体验化设计 |
主讲: | 吴凯 |
1.课件下载
{pdf=images/openfiles/experience_design_based_on_big_data_analytics2021.pdf|100%|1300|native}
2.python相关文件
2.1下载anaconda
https://www.anaconda.com/products/individual
2.2示例的juputer notebook文件
2.2.1奇数与偶数
https://od.lk/d/165592120_7Y8oc/python_odd_numbers.ipynb
2.2.2用python控制excel
https://od.lk/d/165234034_E6cXT/hotel50python.xlsx
https://od.lk/d/165703667_3jtvt/python_excel50hotel.ipynb
2.2.3python抓取豆瓣网的电影信息
https://od.lk/d/165592124_vkZkQ/webscraping_douban_top150.ipynb
https://od.lk/d/165592122_b5z4S/analysis_douban_top150.ipynb
https://od.lk/d/165592123_05AFt/wordcloud_douban_top150.ipynb
2.3 可以检索python代码的网站
2.4 python参考书籍
python很火,但是跟python类似的软件很多,例如R、Julia等,参见编程语言的历史。
就数据科学而言(data science),统计出身的数据科学家偏爱R一点,程序设计出身的数据科学家偏爱python一点;其实多数数据科学家是python、R并用的——发挥各自的优势;很多数据科学还同时使用tableau、Excel、google spreadsheet。
python是通用的编程语言,是开源软件(open source)。简言之python类似安卓系统或苹果iso系统,python的活力在于有很多拓展功能包或功能库(library),类似手机操作系统上的app。所以从这个意义上讲,重点不是python,而是要做哪个方向的研究,选择响应的功能库(library)。例如常见的数据分析库是pandas、numpy,常见的数据可视化用matplotlib,常见的网页数据抓取是BeautifulSoup、scapy。
python的书非常多,通用的、针对特定的领域的,都是如此。
建议通过http://libgen.rs/免费下载英文电子书。
我推荐3本通用性强、有中译本的书(估计不同人的推荐会非常不同)
2.4.1 Automate the Boring Stuff with Python
英文版
Sweigart, A. (2020). Automate the Boring Stuff with Python: Practical Programming for Total Beginners (2nd). No Starch Press.
http://libgen.rs/book/index.php?md5=BFE1E2B65DA651477404660AE468D148
https://automatetheboringstuff.com/
https://www.amazon.cn/dp/B07VSXS4NK/
https://www.amazon.com/-/zh/dp/1593279922
http://kaiwu.city/index.php/80-automate-the-boring-stuff
中文翻译版(原书第1版)
Sweigart, A.(2016). Python编程快速上手——让繁琐工作自动化 编程快速上手——让繁琐工作自动化 (1st ). 人民邮电出版社. https://www.amazon.cn/dp/B01M68PABD
http://libgen.rs/book/index.php?md5=5EA4E155C46104B393AFF7366772476C
原书第2版对应视频文件
https://www.udemy.com/course/automate/
2.4.2 learn python in hard way
Shaw, Z. (2018). Learn More Python 3 the Hard Way: The Next Step for New Python Programmers. Addison-Wesley. http://libgen.rs/book/index.php?md5=5C39D11E8BDEE52F84E0F4A55B55F30D
Shaw, Z. (2018). “笨办法”学Python 3笨办法”学Python 3 (2nd). 人民邮电出版社有限公司. https://www.amazon.cn/dp/B07Y525WFQ
2.4.3 python for data analysis
McKinney, W. (2017). Python for Data Analysis: Data Wrangling with Pandas, Numpy, and Ipython (2nd). O’Reilly Media, Inc. http://libgen.rs/book/index.php?md5=518B01712FF35354C5CF30B4913900FB
McKinney, W. (2018). 利用Python进行数据分析 (2nd). 机械工业出版社. https://www.amazon.cn/dp/B07FW12FVC/
- 文章信息
- 作者: kaiwu
- 点击数:139
课件下载
https://od.lk/d/165712640_W04po/beta_quantitative_analysis_methods_in_hospitality2021.pdf
1.下载anaconda
https://www.anaconda.com/products/individual
2.示例的juputer notebook文件
2.1奇数与偶数
https://od.lk/d/165592120_7Y8oc/python_odd_numbers.ipynb
2.2用python控制excel
https://od.lk/d/165234034_E6cXT/hotel50python.xlsx
https://od.lk/d/165703667_3jtvt/python_excel50hotel.ipynb
2.3python抓取豆瓣网的电影信息
https://od.lk/d/165592124_vkZkQ/webscraping_douban_top150.ipynb
https://od.lk/d/165592122_b5z4S/analysis_douban_top150.ipynb
https://od.lk/d/165592123_05AFt/wordcloud_douban_top150.ipynb
3.reference
4.参考书籍