Python has become the language of choice for most fields in the scientific community, and this is expanding to businesses investing in analytics resources. Fundamentals of Data Analytics in Python LiveLessons is a coherent, narrative tutorial that strikes the right balance between teaching the "how" and the "why" of data analytics in Python. This video begins with an abbreviated primer on Python, and then proceeds to cover open source Python tools relevant to solving day-to-day scientific and engineering programming problems.
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About the Authors:
Peter Wang is co-founder and president of Continuum Analytics. Peter holds a B.A. in Physics from Cornell University and has been developing applications professionally using Python since 2001. Before co-founding Continuum Analytics in 2011, Peter spent seven years at Enthought designing and developing applications for a variety of companies, including investment bankers, high-frequency trading firms, oil companies, and others. In 2007, Peter was named Director of Technical Architecture and served as client liaison on high-profile projects. Peter also developed Chaco, an open-source, Python-based toolkit for interactive data visualization. Peter's roles at Continuum Analytics include product design and development, software management, business strategy, and training.
Aron Ahmadia is a research scientist at Continuum Analytics. Aron holds a Ph.D. in Applied Mathematics from Columbia University and has been working with Python for technical computing since 2003. Aron is one of the lead developers of PyClaw, an open-source, Python-based toolkit for modeling wave propagation at large scale. His software is used in academia, industry, and government, and runs on workstations, the cloud, and 65,536-core supercomputers. Aron has extensive experience teaching Python to industrial, academic, and government users, and has taught it as part of the curriculum for Software Carpentry courses across four continents.
Table of contents
Lesson 1: Getting Set Up with the Analytical Python Ecosystem
- Learning objectives 00:00:55
- 1.1 Obtain the software 00:03:25
- 1.2 Explore the Python command line from IPython 00:03:22
- 1.3 Experiment and chronicle in the IPython Notebook 00:04:56
- Lesson 2: Basic Data Analysis with Python
- Lesson 3: Numerical Analysis with NumPy
Lesson 4: Advanced Analytics with SciPy and sci-kit learn
- Learning objectives 00:00:36
- 4.1 Understand SciPy 00:00:59
- 4.2 Compute means, medians, quartiles, and other statistics 00:03:22
- 4.3 Fit data and interpolate 00:08:40
- 4.4 Understand sci-kit learn 00:03:44
- Lesson 5: Tabular Data Analysis with Pandas
- Lesson 6: Overview of Python Visualization Tools
- Title: Fundamentals of Data Analytics in Python
- Release date: August 2013
- Publisher(s): Addison-Wesley Professional
- ISBN: 0133740005
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