pcparts_app
所属分类：数据库系统
开发工具：Jupyter Notebook
文件大小：2521KB
下载次数：0
上传日期：2017-06-28 03:50:50
上 传 者：
sh-1993
说明： 报废PCPartPicker以创建以价值为中心的PC部件推荐引擎
(Scraping PCPartPicker to create value-focused PC part recommendation engine)
文件列表:
pcbuild_app (0, 2017-06-28)
pcbuild_app\.DS_Store (6148, 2017-06-28)
pcbuild_app\.Rhistory (5962, 2017-06-28)
pcbuild_app\.Rproj.user (0, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA (0, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\pcs (0, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\pcs\files-pane.pper (157, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\pcs\source-pane.pper (23, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\pcs\windowlayoutstate.pper (295, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\pcs\workbench-pane.pper (65, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\rmd-outputs (5, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\saved_source_markers (27, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb (0, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop (0, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\10F60F87 (3, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\1A0D832E (3, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\491D0FA8 (3, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\495442FF (3, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\5EEA8333 (3, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\63AD5CA4 (32, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\9E58E434 (3, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\BC2E2AEA (3, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\CFC76BCA (3, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\EAAFD23 (3, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\F55E6B16 (3, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\prop\INDEX (705, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\s-62D0C53D (0, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\s-62D0C53D\292E52CB (22880, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\s-62D0C53D\DB9419AE (7243, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\s-62D0C53D\EA403C91 (1523, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\sdb\s-62D0C53D\lock_file (0, 2017-06-28)
pcbuild_app\.Rproj.user\CC2340DA\session-persistent-state (30, 2017-06-28)
pcbuild_app\.Rproj.user\shared (0, 2017-06-28)
pcbuild_app\.Rproj.user\shared\notebooks (0, 2017-06-28)
pcbuild_app\.Rproj.user\shared\notebooks\paths (599, 2017-06-28)
pcbuild_app\global.R (1919, 2017-06-28)
pcbuild_app\pcbuild_app.Rproj (205, 2017-06-28)
... ...
# pcparts_app:
## Web scraping PCPartpicker.com for value-based recommendations
The finished app can be found [here](https://samomullane.shinyapps.io/pcbuild_app/). A full write up of this project can be accessed via [this link](http://blog.nycdatascience.com/student-works/web-scraping/value-based-pc-part-selection/).
The contents of this main folder are the ipython EDA notebook, the final presentation slides, the webscraping folder and the final part recommendation app.
Altogether 5 programming languages were used for this project (in order of chronology):
1. JavaScript (PhantomJS) - webscraping tool, used to grab all of our required data
2. Bash - command line scripting to automate and coordinate python, PhantomJS scripts
3. Python - BeautifulSoup parsing of scraped data; initial EDA and data preparation in ipython notebook
4. SQL - local database created to store all of the cleaned data; most of the app logic is constructed in SQL
5. R - the final app is constructed with Shiny and hosted on shinyapps.io
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