README.md

Dive into hydrology using Python

Tools you'll need

• Python
• R
• IPython and/or the Jupyter Notebook
• Some scientific computing packages:
  • NumPy: a general-purpose array-processing package
  • matplotlib: a Python 2D plotting library for data visulization
  • pandas: Python's data analysis tools
  • rpy2: an interface between Python and R

For Mac users, we highly recommend installing Anaconda (Python 2.7 version) as you can use its package manager (called "conda") to easily install and update packages 😄. For example, open your terminal window and type the following commands to install the above mentioned packages:

• conda install R
• conda install rpy2

For Windows users, you may need to install these packages separately 😦.

• To install rpy2, download the Windows Binaries for rpy2 [here] (http://www.lfd.uci.edu/~gohlke/pythonlibs/#rpy2) based on your computer architecture. Launch the Command Prompt and type pip install SomePackage-1.0-py2.py3-none-any.whl to install the downloaded .whl files. Please make sure that you have the latest version of pip. You can upgrade pip using python -m pip install --upgrade pip.
• Change Path for R. Go to advanced and system setting -> environment variables
• In the user variable field, add C:\Program Files\R\R-3.0.2\bin\x64 to the path
• In the system variable field, add three new variables:
  • Create a R_HOME system variable with a value similar to C:\Program Files\R\R-3.2.0
  • Create a R_USER system variable with your user name C:\Users\"your user name"
  • Create a R_LIBS_USER system variable with a path to the folder where external R packages are/will be installed. You can find the path through the command .libPaths() in the R environment.

Let's get started!

1. Get the GitHub repository
   • Use the command line: git clone [email protected]:XiaogangHe/Princeton-CEE306.git
   • Or download the repository as a .zip file
2. Run the notebook
   • Open your terminal and type: jupyter notebook

Resources

Learn IPython well

• 5-10 mins guide to learn IPython Notebook. (You can watch the lecture on Youtube instead.)
• A gallery of interesting Jupyter and IPython Notebooks
• Fabian Pedregosa's gallery

Learn Pandas well

• Essential: 10 Minutes to Pandas
• Essential: Things in Pandas I Wish I'd Had Known Earlier (IPython Notebook)
• Useful Pandas Snippets
• Other docs related to pandas:
  • The official cookbook
  • Data Structures
  • Group By: split-apply-combine DataFrames
  • Visulization

Cheat sheets

Bookmark these cheat sheets:

• Matplotlib/Pandas/Python cheat sheets.

Questions, answers, chats

Ask questions related to Python on StackExchange stats.stackexchange.com – python.