##Python for Exploratory Computing
Lots of books are written on scientific computing, but very few deal with the much more common exploratory computing (a term coined by Fernando Perez), which represents daily tasks of many scientists and engineers that try to solve problems but are not computer scientists. This set of Notebooks is written for scientists and engineers who want to use Python programming for exploratory computing, scipting, data analysis, and visualization. Python makes many of these programmig tasks quick and easy and, probably most importantly, fun.
No prior knowledge of computer programming is assumed.
Each Notebook covers a specific topic and includes a number of exercises.
The exercises should take less than 4 hours to complete for each Notebook.
Download the Notebooks and accompanying data files from the github repositories. These Notebooks contain empty output cells. Running the output
cells is part of learning Python. Notebooks with output cells cells have the addition
_sol and can be
viewed by clicking on the links to the Notebook Viewer below.
The following Notebooks are available (they are under development; more will follow soon):
###Applications to Water Management
Notebook WM1: Time Series Data and Pandas
Notebook WM2: Manning's Equation and Emptying Reservoir
Notebook WM3: Water Distribution Systems
###Applications to Probability and Statistics
Notebook S1: Discrete Random Variables
Notebook S2: Continuous Random Variables
Notebook S3: Distribution of the Mean, Hypothesis Tests, and the Central Limit Theorem
Notebook S4: Linear regression and curve fitting
###Some More Advanced Python Topics
Notebook ADV1: Finding the Zero of a Function
Notebook ADV2: Systems of linear equations
Notebook ADV3: Object oriented programming
Notebook ADV4 : Interactive Graphics with Matplotlib Widgets