Difference between revisions of "Stock Analysis Log"
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(3 hours) Keith researched data scraping, ran code which successfully scrapped data through both Yahoo and Quandl, and discussed with Brandt on how we can load our data into a cloud SQL server. | (3 hours) Keith researched data scraping, ran code which successfully scrapped data through both Yahoo and Quandl, and discussed with Brandt on how we can load our data into a cloud SQL server. | ||
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| + | (2 hours) Keith setup MySQL and SQLite and worked towards figuring out a way to make data accessible to everyone. | ||
===Oct. 1 -- Oct. 7=== | ===Oct. 1 -- Oct. 7=== | ||
Revision as of 19:39, 21 September 2018
Link to Project Page: Stock Analysis
Contents
- 1 Aug. 27 -- Sept. 2
- 2 Sept. 3 -- Sept 9
- 3 Sept. 10 -- Sept. 16
- 4 Sept. 17 -- Sept. 23
- 5 Sept. 24 -- Sept. 30
- 6 Oct. 1 -- Oct. 7
- 7 Oct. 8 -- Oct. 14
- 8 Oct. 15 -- Oct. 21
- 9 Oct. 22 -- Oct. 28
- 10 Oct. 29 -- Nov. 4
- 11 Nov. 5 -- Nov. 11
- 12 Nov. 12 -- Nov. 18
- 13 Nov. 19 -- Nov. 25
- 14 Nov. 26 -- Dec. 2
- 15 Dec. 3 -- Dec. 9
- 16 Dec. 10 -- Dec. 16
Aug. 27 -- Sept. 2
(1.5 hours) All group members discussed how to target what data we should find and what property of a home we find important.
Sept. 3 -- Sept 9
(1.0 hours) Brandt, Keith, and Jessica met with Prof. Fehr to review the project and receive further guidance.
Sept. 10 -- Sept. 16
(3.0 hours) Brandt and Keith further refined the project: investigated data scraping, how to add data to a database, and sites which are easily scrappable and have the data were looking for. Keith downloaded PyCharm so that we could begin experimenting with our ideas using python.
(9/15 Keith: 2 hrs.) Worked towards scraping data from google finance. Google protects financial information which will be a challenge. Currently working on a work around.
Sept. 17 -- Sept. 23
(2 hours) Brandt, Keith, and Jessica met to discuss and refine the project idea as well as flesh out the wiki.
(2 hours) Jessica created and polished the presentation.
Sept. 24 -- Sept. 30
(3 hours) Brandt compiled data and began to join the data in excel. The result was uploaded to excel. I investigated uploading these tables of data to a SQL server, and created accounts on AWS and Microsoft AZURE, however had issues figuring out how to upload the data.
(3 hours) Keith researched data scraping, ran code which successfully scrapped data through both Yahoo and Quandl, and discussed with Brandt on how we can load our data into a cloud SQL server.
(2 hours) Keith setup MySQL and SQLite and worked towards figuring out a way to make data accessible to everyone.
