Research
- Crime Categories
- Murder Circumstances
- Charges
- Murder Numbers by SHR
- Definitions of Murder
- Crime Literature
- Other Literature
- Seminars
- Journal Ranking
- Laws
- Changes in Law and Reporting in Michigan
- Citation Guides
- Datasets
Writing
Methods
- BLP
- Econometrics Models
- Econometrics Tests
- Econometrics Resources
- Event Study Plots
- Metrics Literature
- Machine Learning
Python-related
- Python Basic Commands
- Pandas Imports and Exports
- Pandas Basic Commands
- Plotting in Python
- Python web scraping sample page
- Two Sample t Test in Python
- Modeling in Python
R-related
- R Basics
- R Statistics Basics
- RStudio Basics
- R Graphics
- R Programming
- Accessing MySQL Databases from R
Latex-related
Stata-related
SQL
Github
Linux-related
Conda-related
AWS-related
Webscraping
Interview Prep
Other
Python Installation
Installing Anaconda is the best way because it manages packages for my Python application as well as my R application. It comes with the Python Shell as well, just type IDLE into the search bar and voila!
The introductory tutorial has a lot of information on how to set up a package manager, how to create a new environment, etc. It is a good place to get started.
When you want to work on files in a custom folder instead of the default, we could make use of a command window in our environment (Reference).
Managing environments in Anaconda: here.
Installing nbextensions: here.