Pandas (the Python Data Analysis library) provides a powerful and comprehensive toolset for working with data. Fundamentally, Pandas provides a data structure, the DataFrame, that closely matches real world data, such as experimental results, SQL tables, and Excel spreadsheets, that no other mainstream Python package provides. In addition to that, it includes tools for reading and writing diverse files, data cleaning and reshaping, analysis and modeling, and visualization. Using Pandas effectively can give you super powers, regardless of whether you’re working in data science, finance, neuroscience, economics, advertising, web analytics, statistics, social science, or engineering. Continue reading
What: A guided walkthrough and live Q&A about Enthought’s new “Machine Learning Mastery Workshop” training course.
Who Should Watch: If predictive modeling and analytics would be valuable in your work, come to the webinar to find out what all the fuss is about and what there is to know. Whether you are looking to get started with machine learning, interested in refining your machine learning skills, or want to transfer your skills from another toolset to Python, come to the webinar to find out if Enthought’s highly interactive, expertly taught Machine Learning Mastery Workshop might be a good fit for accelerating your development!
2017 will be Enthought’s 11th year at the SEG (Society of Exploration Geophysicists) Annual Meeting, and we couldn’t be more excited to be at the leading edge of the digital transformation in oil & gas being driven by the capabilities provided by machine learning and artificial intelligence.
Now in its 87th year, the Annual SEG (Society of Exploration Geophysicists) Meeting will be held in Houston, Texas on September 24-27, 2017 at the George R. Brown Convention Center. The SEG Annual Meeting will be the first large conference to take place in Houston since Hurricane Harvey and its devastating floods, and we’re so pleased to be a small part of getting Houston back “open for business.”
Pre-Event Kickoff: The Machine Learning Geophysics Hackathon
We had such a great experience at the EAGE Subsurface Hackathon in Paris in June that when we heard our friends at Agile Geoscience were planning a machine learning in geophysics hackathon for the US, we had to join! Brendon Hall, Enthought’s Energy Solutions Group Director will be there as a participant and coach and Enthought CEO Eric Jones will be on the judging panel.
Come Meet Us on the SEG Expo Floor & Learn About Our AI-Enabled Solutions for Oil & Gas
Presentations in Enthought Booth #318 (just to the left from the main entrance before the main aisle):
- Monday, Sept 25, 12-12:45 PM: Lessons Learned From the Front Line: Moving AI From Research to Application
- Tues, Sept 26, 1-1:45 PM: Canopy Geoscience: Building Innovative, AI-Enabled Geoscience Applications
- Wed, Sept 27, 12-12:45 PM: Applying Artificial Intelligence to CT, Photo, and Well Log Analysis with Virtual Core
Hart Energy’s E&P Magazine Features Canopy Geoscience
Canopy Geoscience, Enthought’s cross-domain AI platform for oil & gas, was featured in the September 2017 edition of E&P magazine. See the coverage in the online SEG Technology Showcase, in the September print edition, or in the online E&P Flipbook.
What: A guided walkthrough and Q&A about how to migrate from MATLAB® to Python with Enthought Lead Instructor, Dr. Alexandre Chabot-Leclerc.
Who Should Watch: MATLAB® users who are considering migrating to Python, either partially or completely.
Python has a lot of momentum. Many high profile projects use it and more are migrating to it all the time. Why? One reason is that Python is free, but more importantly, it is because Python has a thriving ecosystem of packages that allow developers to work faster and more efficiently. They can go from prototyping to production to scale on hardware ranging from a Raspberry Pi (or maybe micro controller) to a cluster, all using the same language. A large part of Python’s growth is driven by its excellent support for work in the fields of science, engineering, machine learning, and data science.
You and your organization might be thinking about migrating from MATLAB to Python to get access to the ecosystem and increase your productivity, but you might also have some outstanding questions and concerns, such as: How do I get started? Will any of my knowledge transfer? How different are Python and MATLAB? How long will it take me to become proficient? Is it too big a of a shift? Can I transition gradually or do I have to do it all at once? These are all excellent questions.
We know people put a lot of thought into the tools they select and that changing platforms is a big deal. We created this webinar to help you make the right choice.
In this webinar, we’ll give you the key information and insight you need to quickly evaluate whether Python is the right choice for you, your team, and your organization, including:
- How to get started
- What you need in order to replicate the MATLAB experience
- Important conceptual differences between MATLAB and Python
- Important similarities between MATLAB and Python: What MATLAB knowledge will transfer
- Strategies for converting existing MATLAB code to Python
- How to accelerate your transition
Presenter: Dr. Alexandre Chabot-Leclerc, Enthought Lead Instructor
Ph.D, Electrical Engineering, Technical University of Denmark
Python for Scientists & Engineers Training: The Quick Start Approach to Turbocharging Your Work
If you are tired of running repeatable processes manually and want to (semi-) automate them to increase your throughput and decrease pilot error, or you want to spend less time debugging code and more time writing clean code in the first place, or you are simply tired of using a multitude of tools and languages for different parts of a task and want to replace them with one comprehensive language, then Enthought’s Python for Scientists and Engineers is definitely for you!
This class has been particularly appealing to people who have been using other tools like MATLAB or even Excel for their computational work and want to start applying their skills using the Python toolset. And it’s no wonder — Python has been identified as the most popular coding language for five years in a row for good reason.
One reason for its broad popularity is its efficiency and ease-of-use. Many people consider Python more fun to work in than other languages (and we agree!). Another reason for its popularity among scientists, engineers, and analysts in particular is Python’s support for rapid application development and extensive (and growing) open source library of powerful tools for preparing, visualizing, analyzing, and modeling data as well as simulation.
Python is also an extraordinarily comprehensive toolset – it supports everything from interactive analysis to automation to software engineering to web app development within a single language and plays very well with other languages like C/C++ or FORTRAN so you can continue leveraging your existing code libraries written in those other languages.
Many organizations are moving to Python so they can consolidate all of their technical work streams under a single comprehensive toolset. In the first part of this class we’ll give you the fundamentals you need to switch from another language to Python and then we cover the core tools that will enable you to do in Python what you were doing with other tools, only faster and better!
|Upcoming Open Python for Scientists & Engineers Sessions:
Washington, DC, Sept 25-29
Have a group interested in training? We specialize in group and corporate training. Contact us or call 512.536.1057.
|Download Enthought’s MATLAB to Python White Paper|
|Additional Webinars in the Training Series:||Download Enthought’s Machine Learning with Python’s Scikit-Learn Cheat Sheets|
When: Thursday, July 20, 2017, 11-11:45 AM CT (Live webcast)
What: A comprehensive overview and live demonstration of Enthought’s latest tools for Python for the enterprise with Enthought’s Chief Technical & Engineering Officer, Didrik Pinte
Who Should Attend: Python users (or those supporting Python users) who are looking for a universal solution set that is reliable and “just works”; scientists, engineers, and data science teams trying to answer the question “how can I more easily build and deploy my applications”; organizations looking for an alternative to MATLAB that is cost-effective, robust, and powerful
REGISTER (if you can’t attend we’ll send all registrants a recording)
For over 15 years, Enthought has been empowering scientists, engineers, analysts, and data scientists to create amazing new technologies, to make new discoveries, and to do so faster and more effectively than they dreamed possible. Along the way, hand in hand with our customers in aerospace, biotechnology, finance, oil and gas, manufacturing, national laboratories, and more, we’ve continued to “build the science tools we wished we had,” and share them with the world.
For 2017, we’re pleased to announce the release of several major new products and tools, specifically designed to make Python more powerful and accessible for users like you who are building the future of science, engineering, artificial intelligence, and data analysis.
WHAT YOU’LL SEE IN THE WEBINAR
In this webinar, Enthought’s Chief Technical & Engineering Officer will share a comprehensive overview and live demonstration of Enthought’s latest products and how they provide the foundation for scientific computing and artificial intelligence applications with Python, including:
- Enthought Python Distribution (EPD): 450+ commercially supported Python 2 and Python 3 packages, now free for all users
- Enthought Canopy 2.0: a graphical package manager and integrated analysis environment that provides a universal analysis and development tool, now with Python 3! (NOTE: we recommend all Canopy users upgrade to this major release version ASAP)
- Enthought Deployment Server: provides reproducible, secure, onsite management of Python package and application development and deployment across groups and organizations
We’ll also walk through specific use cases so you can quickly see how Enthought’s Enterprise Python tools can impact your workflows and productivity.
REGISTER (if you can’t attend we’ll send all registrants a recording)
Presenter: Didrik Pinte, Chief Technical & Engineering Officer, Enthought
Blog: New Year, New Enthought Products (Jan 2017)
New features in the Canopy Data Import Tool Version 1.1:
Support for Pandas v. 20, Excel / CSV export capabilities, and more
We’re pleased to announce a significant new feature release of the Canopy Data Import Tool, version 1.1. The Data Import Tool allows users to quickly and easily import CSVs and other structured text files into Pandas DataFrames through a graphical interface, manipulate the data, and create reusable Python scripts to speed future data wrangling. Here are some of the notable updates in version 1.1:
1. Support for PyQt
The Data Import Tool now supports both PyQt and PySide backends. Python 3 support will also be available shortly.
2. Exporting DataFrames to csv/xlsx file formats
We understand that data exploration and manipulation are only one part of your data analysis process, which is why the Data Import Tool now provides a way for you to save the DataFrame as a CSV/XLSX file. This way, you can share processed data with your colleagues or feed this processed file to the next step in your data analysis pipeline.
3. Column Sort Indicators
In earlier versions of the Data Import Tool, it was not obvious that clicking on the right-end of the column header sorted the columns. With this release, we added sort indicators on every column, which can be pressed to sort the column in an ascending or descending fashion. And given the complex nature of the data we get, we know sorting the data based on single column is never enough, so we also made sorting columns using the Data Import Tool stable (ie, sorting preserves any existing order in the DataFrame).
Renowned scientists, engineers and researchers from around the world to gather July 10-16, 2017 in Austin, TX to share and collaborate to advance scientific computing tool
AUSTIN, TX – June 6, 2017 – Enthought, as Institutional Sponsor, today announced the SciPy 2017 Conference will be held July 10-16, 2017 in Austin, Texas. At this 16th annual installment of the conference, scientists, engineers, data scientists and researchers will participate in tutorials, talks and developer sprints designed to foster the continued rapid growth of the scientific Python ecosystem. This year’s attendees hail from over 25 countries and represent academia, government, national research laboratories, and industries such as aerospace, biotechnology, finance, oil and gas and more.
“Since 2001, the SciPy Conference has been a highly anticipated annual event for the scientific and analytic computing community,” states Dr. Eric Jones, CEO at Enthought and SciPy Conference co-founder. “Over the last 16 years we’ve witnessed Python emerge as the de facto open source programming language for science, engineering and analytics with widespread adoption in research and industry. The powerful tools and libraries the SciPy community has developed are used by millions of people to advance scientific inquest and innovation every day.”
Special topical themes for this year’s conference are “Artificial Intelligence and Machine Learning Applications” and the “Scientific Python (SciPy) Tool Stack.” Keynote speakers include:
- Kathryn Huff, Assistant Professor in the Department of Nuclear, Plasma, and Radiological Engineering at the University of Illinois at Urbana-Champaign
- Sean Gulick, Research Professor at the Institute for Geophysics at the University of Texas at Austin
- Gaël Varoquaux, faculty researcher in the Neurospin brain research institute at INRIA (French Institute for Research in Computer Science and Automation)
In addition to the special conference themes, there will also be over 100 talk and poster paper speakers/presenters covering eight mini-symposia tracks including: Astronomy; Biology, Biophysics, and Biostatistics; Computational Science and Numerical Techniques; Data Science; Earth, Ocean, and Geo Sciences; Materials Science and Engineering; Neuroscience; and Open Data and Reproducibility.
Python Integration Toolkit for LabVIEW recognized for extending LabVIEW connectivity and bringing the power of Python to applications in Test, Measurement and the Industrial Internet of Things (IIoT)
AUSTIN, TX – May 24, 2017 – Enthought, a global leader in scientific and analytic computing solutions, was honored this week by National Instruments with the LabVIEW Tools Network Platform Connectivity 2017 Product of the Year Award for its Python Integration Toolkit for LabVIEW.
First released at NIWeek 2016, the Python Integration Toolkit enables fast, two-way communication between LabVIEW and Python. With seamless access to the Python ecosystem of tools, LabVIEW users are able to do more with their data than ever before. For example, using the Toolkit, a user can acquire data from test and measurement tools with LabVIEW, perform signal processing or apply machine learning algorithms in Python, display it in LabVIEW, then share results using a Python-enabled web dashboard.
“Python is ideally suited for scientists and engineers due to its simple, yet powerful syntax and the availability of an extensive array of open source tools contributed by a user community from industry and R&D,” said Dr. Tim Diller, Director, IIoT Solutions Group at Enthought. “The Python Integration Toolkit for LabVIEW unites the best elements of two major tools in the science and engineering world and we are honored to receive this award.”