This 5-day class will get your group up to speed quickly on how to optimize your use of the Python standard language and key Python packages for data exploration, modeling, and analysis.
The Python for Data Analysis class will get you up to speed quickly on how to optimize your use of the Python standard language and key Python packages for data exploration, modeling, and analysis. This curriculum provides an excellent survey understanding of the Python language and its capabilities for all things data, while also providing intensive exposure to the core workhorse tools of NumPy and Pandas that are central to data analysis in Python.
Enthought instructors have doctorates in scientific fields such as physics, engineering, computer science, and mathematics, and all have extensive experience through research and consulting in applying Python to solve complex problems across a range of industries, allowing them to bring their real world experience to the classroom every day. Enthought instructors possess professional, first-hand experience with the tools and technologies covered in our courses.
Although I already had an above-average Python background, I learned a lot about the typical development life cycle from a very experienced developer.
It gave a very comprehensive overview of Python. I saw all the tools and features I would likely use and even more. I understood the power of the language and all the libraries that have been created for it.
It was a great course. Loved the small class size (7 students). Facilities and convenience were great. Leah and homemade desserts were an unexpected treat. The instructor was a great teacher - good at explaining things and answering questions as well as working through student suggestions and helping us step through why something would or would not actually work. He was very good at walking through the learning/discovery/trial and error process and understanding how a beginner would approach some of the exercises and the errors in these approaches and explaining the right solution.
Programming experience in some language (such as R, MATLAB, SAS, Mathematica, Java, C, C++, VB, or FORTRAN) is expected. In particular, participants need to be comfortable with general programming concepts like variables, loops, and functions. Previous Python experience is helpful, but not required.
An understanding of how to use the Python standard library to write programs, access various tools, and document and automate analytical processes.
Introduction to NumPy and 2D plotting. The NumPy package is presented as a tool for rapidly manipulating and processing large data sets. 2D plotting is introduced with matplotlib.
Built on top of NumPy arrays, the Python Data Analysis Library (Pandas) is a powerful and convenient package for dealing with tabular datasets. Participants will learn about its powerful data aggregation and reorganization capabilities for data set explorations, including support for labeling data along each dimension, dealing with missing values, and time series manipulations.
An expert instructor will support students as they work through a typical real-world data analysis project step-by-step using Pandas. This course develops the deep knowledge and skills that will enable students to tackle their own projects with Pandas immediately when they get back to work on Monday morning.
Onsite corporate classes are also available. Discounts are available for 3 or more attendees and academics currently at a degree-granting institution. Contact us to learn more.
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The 3 day Pandas Mastery Workshop is an alternative course for those who already have both (1) current working knowledge of programming in the Python standard language (data structures, control flow, assignment, functions, and package access) and (2) familiarity with array programming in NumPy.
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You could tell from the demos, examples and exercises that this course was designed and taught by someone who has first hand experience of using the tools on real world and real life data.
The depth and breadth of this course will provide the foundation to efficient data manipulation and encapsulation.