Difference between revisions of "Data Science"
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(Broke out some R resources) |
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'''General Purpose Resources''' | '''General Purpose Resources''' | ||
* Coding collaboration (think Google Docs for code) - http://codr.io/ | * Coding collaboration (think Google Docs for code) - http://codr.io/ | ||
| + | * [https://speakerdeck.com/rmcelreath/statistical-rethinking-fall-2017-lecture-01?slide=6 Flowchart showing which statistical method applies based on the variable type and question type] | ||
| + | * [http://scikit-learn.org/stable/tutorial/machine_learning_map/index.html Choosing the right estimator] (similar idea as above) | ||
'''R Resources''' | '''R Resources''' | ||
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This isn't an exhaustive list of R packages (obviously), but is a list of packages that are specifically of interest to digital analysts: | This isn't an exhaustive list of R packages (obviously), but is a list of packages that are specifically of interest to digital analysts: | ||
* [http://code.markedmondson.me/googleAnalyticsR/ googleAnalyticsR] - package for pulling data from Google Analytics using the v4 API | * [http://code.markedmondson.me/googleAnalyticsR/ googleAnalyticsR] - package for pulling data from Google Analytics using the v4 API | ||
| − | * [http://code.markedmondson.me/bigQueryR/] - package for pulling data from Google BigQuery | + | * [http://code.markedmondson.me/bigQueryR/ bigQueryR] - package for pulling data from Google BigQuery |
* [http://randyzwitch.com/rsitecatalyst/ RSiteCatalyst] - package for pulling data from Adobe Analytics | * [http://randyzwitch.com/rsitecatalyst/ RSiteCatalyst] - package for pulling data from Adobe Analytics | ||
'''Python Resources''' | '''Python Resources''' | ||
Revision as of 13:18, 25 January 2018
This page is a repository of links/resources that were originally published or may be of interest to the #data-science channel in the Measure Slack team. As it grows, we can spin off separate pages such that this becomes more of a shell page linking to those pages.
General Purpose Resources
- Coding collaboration (think Google Docs for code) - http://codr.io/
- Flowchart showing which statistical method applies based on the variable type and question type
- Choosing the right estimator (similar idea as above)
R Resources
- Dartistics
- Mark Edmondson's Code Blog
- R for Data Science by Hadley Wickham - full book online
- Tidy Text Mining by Julia Silge
R Packages
This isn't an exhaustive list of R packages (obviously), but is a list of packages that are specifically of interest to digital analysts:
- googleAnalyticsR - package for pulling data from Google Analytics using the v4 API
- bigQueryR - package for pulling data from Google BigQuery
- RSiteCatalyst - package for pulling data from Adobe Analytics
Python Resources
