Planet SciPy
Stock Sentiment Analysis Using Autoencoders
In this notebook, we will use autoencoders to do stock sentiment analysis. Autoencoder consists of encoder and decoder models. Encoders compress the data and decoders decompress it. Once you train an autoencoder neural network, the encoder can be used to train a different machine learning model.
For stock sentiment analysis, we will first use encoder for the feature extraction and then use these features to train a machine learning model to classify the stock tweets. To learn more about Autoencoders check out the following link...
https://www.nbshare.io/notebook/86916405/Understanding-Autoencoders-With-Examples/
Let us import the necessary packages.
# importing necessary lib import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns
# reading tweets data df=pd.read_csv('/content/stocktwits (2).csv')
df.head()
| ticker | message |
|---|
Roles in ML Team and How They Collaborate With Each Other
Developing successful machine learning projects requires a variety of expertise, and hence, it is an extremely collaborative job. Designing a problem statement needs the company to ask critical questions such as: Why build an ML model? How to get the required data? How to design the systems infrastructure? and more. ML has been around for […]
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Top Tools to Run a Computer Vision Project
Computer vision has gained tremendous traction thanks to state-of-the-art tools and technologies that seem to be released every day. This technology is being applied in various fields, including autonomous vehicles, robotics, and medical image analysis. Computer vision is a scientific field that involves using technology to understand images and videos. The goal is to automate […]
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Top 10 Best Tools to Increase Productivity in Machine Learning Teams
Over the past couple of years, the machine learning community has grown a lot. One of the great things to come from it is the abundance of efficient machine learning tools that help us do more with less effort. As a machine learning engineer, you now have less work when building models or pipelines. For […]
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Performance Metrics in Machine Learning [Complete Guide]
Performance metrics are a part of every machine learning pipeline. They tell you if you’re making progress, and put a number on it. All machine learning models, whether it’s linear regression, or a SOTA technique like BERT, need a metric to judge performance. Every machine learning task can be broken down to either Regression or […]
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Implementing the Macro F1 Score in Keras: Do’s and Don’ts
As a part of the TensorFlow 2.0 ecosystem, Keras is among the most powerful, yet easy-to-use deep learning frameworks for training and evaluating neural network models. When we build neural network models, we follow the same steps of a model lifecycle as we would for any other machine learning model: Construct and compile network with […]
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Switching From Spreadsheets to Neptune.ai and How It Pushed My Model Building Process to the Next Level
Many ML projects, including Kaggle competitions, have a similar workflow. You start with a simple pipeline with a benchmark model. Next, you begin incorporating improvements: adding features, augmenting the data, tuning the model… On each iteration, you evaluate your solution and keep changes that improve the target metric. This workflow involves running a lot of […]
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The Life Cycle of a Machine Learning Project: What Are the Stages?
What is machine learning and its life cycle about? You’ll get a different answer from different people. Programmers might say that it’s about programming with Python, and sophisticated mathematical algorithms. Business stakeholders usually associate machine learning with data, and a dash of mystery. Machine learning engineers tend to talk about model training and data wrangling. So […]
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Best Benchmarks for Reinforcement Learning: The Ultimate List
In this post, I’ll share with you my library of environments that support training reinforcement learning (RL) agents. The basis for RL research, or even playing with or learning RL, is the environment. It’s where you run your algorithm to evaluate how good it is. We’re going to explore 23 different benchmarks, so I guarantee […]
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Animations and Transformations with QtQuick — Building an animated analog clock in QML
In the previous tutorial we implemented a basic QML clock application using Python code to get the current time, format it into a string and send that through to our QML layout for display using Qt signals.
That gave us a good overview of the structure of Python/QML applications …
Code and Notebook Versioning for ML Teams [Guide]
As a Data Scientist or Machine Learning engineer, you probably experienced this: You start writing code in your Jupyter Notebook, do your exploration, pre-process your data, build your models and save them… but then you lose track of which code and notebook version was the best. There are conventional tools, like git and other source […]
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Clear.ML Alternatives for Data Scientists and ML Developers
End-to-end MLOps tools are a mixed bag. Some of us engineers like a tool that connects every resource, plugin, integration, ML operation, and automates it all. Others not so much. ClearML is a popular end-to-end platform that connects all data science tools in a unified environment. It’s an open-source suite of tools to automate preparing, […]
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Data Scientists: Bring the Narrative to the Forefront
Charts and graphs can be a valuable tool, as mentioned earlier, but they can also carry a sense of authority that overshadows the reality that data visualizations or non-visual presentations can be manipulative (see the margarine-and-divorce-rates example above). This is because data is often seen as a fixed source of truth, yet the presentation of data is in fact subjective, largely dependent on who’s interpreting it and how. While data visualization can help identify trends, patterns, or outliers in datasets, it can rarely be used for full analysis and interpretation by itself.Spot the differences: what is new in Spyder 5?
In case you missed it, Spyder 5 was released at the beginning of April! This blog post is a conversation attempting to document the long and complex process of improving Spyder's UI with this release. Portions lead by Juanita Gomez are marked as Juanita, and those lead by Isabela Presedo-Floyd are marked as Isabela.
What did we do?[Juanita] Spyder was created more than 10 years ago and it has had the contributions of a great number of developers who have written code, proposed ideas, opened issues and tested PRs in order to build a piece of Spyder on their own. We (the Spyder team) have been lucky to have such a great community of people contributing throughout the years, but this is the first time that we decided to ask for help from an UX/UI expert! Why? You might wonder. Having the contributions of this great amount of people has resulted in inconsistencies around Spyder’s interface which we didn’t stop
On the Link Between Optimization and Polynomials, Part 4
While the most common accelerated methods like Polyak and Nesterov incorporate a momentum term, a little known fact is that simple gradient descent –no momentum– can achieve the same rate through only a well-chosen sequence of step-sizes. In this post we'll derive this method and through simulations discuss its practical …
A step towards educating with Spyder
As a community manager in the Spyder team, I have been looking for ways of involving more users in the community and making Spyder useful for a larger number of people. With this, a new idea came: Education.
For the past months, we have been wondering with the team whether Spyder could also serve as a teaching-learning platform, especially in this era where remote instruction has become necessary. We submitted a proposal to the Essential Open Source Software for Science (EOSS) program of the Chan Zuckerberg Initiative, during its third cycle, with the idea of providing a simple way inside Spyder to create and share interactive tutorials on topics relevant to scientific research. Unfortunately, we didn’t get this funding, but we didn’t let this great idea die.
We submitted a second proposal to the Python Software Foundation from which we were awarded $4000. For me, this is the perfect opportunity for us to take the first step towards using Spyder for education.
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NumFOCUS Welcomes Tesco Technology to Corporate Sponsors
NumFOCUS is pleased to announce our new partnership with Tesco Technology. A long-time PyData event sponsor, Tesco Technology joined NumFOCUS as a Silver Corporate Sponsor in December 2020. “We are very excited to formalize our partnership with Tesco Technology,” said Leah Silen, NumFOCUS Executive Director. “Tesco Technology has partnered with NumFOCUS for the past several […]
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PyQt6 Book now available: Create GUI Applications with Python & Qt6 — The hands-on guide to making apps with Python
Hello! Today I have released the first PyQt6 edition of my book Create GUI Applications, with Python & Qt6.
This update follows the 4th Edition of the PyQt5 book updating all the code examples and adding additional PyQt6-specific detail. The book contains 600+ pages and 200+ complete code examples taking you …
PyTorch TensorIterator Internals - 2021 Update
For contributors to the PyTorch codebase, one of the most commonly encountered
C++ classes is
TensorIterator.
TensorIterator offers a standardized way to iterate over elements of
a tensor, automatically parallelizing operations, while abstracting device and
data type details.
In April 2020, Sameer Deshmukh wrote a blog article discussing PyTorch TensorIterator Internals. Recently, however, the interface has changed significantly. This post describes how to use the current interface as of April 2021. Much of the information from the previous article is directly copied here, but with updated API calls and some extra details.
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Job Posting | Communications and Marketing Manager
Job Title: Communications and Marketing Manager Position Overview The primary role of the Communications & Marketing Manager is to manage the NumFOCUS brand by overseeing all outgoing communications between NumFOCUS and our stakeholders. You will serve the project communities by playing a key role in their event marketing management and assist with project promotional and […]
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There Is No Data – Only Frozen Models
For a deeper look at this topic, check out this episode from The a16z Podcast, featuring a conversation between Peter and Martin Casado.Create applications with QtQuick — Build modern applications with declarative QML
In previous tutorials we've used the Qt Widgets API for building our applications. This has been the standard method for building applications since Qt was first developed. However, Qt provides another API for building user interfaces: Qt Quick. This is a modern mobile-focused API for app development, with which you …
Why Organizations Should Invest in a Chief Data Officer
Not every company may be ready for a dedicated Chief Data Scientist; some may need to roll these particular responsibilities into a broader CDO position, while others might need to set aside a percentage of a CIO or CTO’s time to devote to data issues. But every company should have at least one senior leader who is accountable for ensuring the organization gets strategic value from its data and stewards it ethically and legally. Data science and ML can unlock vast benefits for organizations, but only if these initiatives are handled responsibly and thoughtfully. This is why the trend toward an increasing number of C-level data roles will continue.Accessibility: Who's Responsible?
For the past few months, I've been part of a group of people in the JupyterLab community who've committed to start chipping away at the many accessibility failings of JupyterLab. I find this work is critical, fascinating, and a learning experience for everyone involved. So I'm going to document my personal experience and lessons I've learned in a series of blog posts. Welcome!
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PySide6 Book now available: Create GUI Applications with Python & Qt6 — The hands-on guide to making apps with Python
Hello! This morning I released the first Qt6 edition of my PySide book Create GUI Applications, with Python & Qt6.
This update follows the 4th Edition of the PySide2 book updating all the code examples and adding additional PySide6-specific detail. The book contains 600+ pages and 200+ complete code examples taking …
Q&A With Anaconda Experts: How Do You Become a Data Scientist?
Want to have a career in data science? Good news: many roads lead to your goal.Giving Visibility to Renewable Energy
The EnergizAIR Infrastructure framework and key interfaces, with the Enthought responsibility on the project shown in the central, grey box. The ultimate project goal was to raise individual awareness of the contribution of renewable energy sources, and ultimately change behaviors. Now ten years later, with orders of magnitude more data, AI/machine learning, cloud, and smartphones …Continue Reading
Recognizing International Women’s Day and Diversity in Tech
This year has provided some exciting and positive milestones for women. Bumble's founder, and fellow Austin woman in tech, Whitney Wolfe Herd, made history for being the 22nd female founder and the youngest to take a company public. Chloe Zhao recently won the Golden Globe for Best Director for the movie "Nomadland," being the second woman ever to win this award and the first Asian woman. And the first female vice president Kamala Harris is the highest-ranking female official in U.S. history and represents the first Black and first Asian-American in the position.sourmash 4.0 is now available! Low low cost if you buy now!
sourmash v4.0.0 is here!
Why Data Preparation Should Never Be Fully Automated
Want more tips for efficient data preparation? Check out this guide that shares tools and tricks to make each step of the process more effective.On the Link Between Optimization and Polynomials, Part 3
I've seen things you people wouldn't believe.
Valleys sculpted by trigonometric functions.
Rates on fire off the shoulder of divergence.
Beams glitter in the dark near the Polyak gate.
All those landscapes will be lost in time, like tears in rain.
Time to halt.
A momentum optimizer *
How Can Higher Education Better Prepare Students to Enter the Data Science Field?
The skills and experience needed to succeed as a data scientist today will not be the same as those required in five or ten years. The worlds of education and business must collaborate to best prepare students to enter the data science workforce.Enhancements to Numba's guvectorize decorator
Starting from Numba 0.53, Numba will ship with an enhanced version of the @guvectorize decorator. Similar to the @vectorize decorator, @guvectorize now has two modes of operation:
- Eager, or decoration-time compilation and
- Lazy, or call-time compilation
Before, only the eager approach was supported. In this mode, users are required to provide a list of concrete supported types beforehand as its first argument. Now, this list can be omitted if desired and as one calls it, Numba dynamically generates new kernels for previously unsupported types.
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Introducing PyMC Labs: Saving the World with Bayesian Modeling
After I left Quantopian in 2020, something interesting happened: various companies contacted me inquiring about consulting to help them with their PyMC3 models.
Usually, I don't hear how people are using PyMC3 -- they mostly show up on GitHub or Discourse when something isn't working right. So, hearing about all these …
Using MicroPython and uploading libraries on Raspberry Pi Pico — Using rshell to upload custom code
MicroPython is an implementation of the Python 3 programming language, optimized to run microcontrollers. It's one of the options available for programming your Raspberry Pi Pico and a nice friendly way to get started with microcontrollers.
MicroPython can be installed easily on your Pico, by following the instructions on the …
sourmash v4.0.0 release candidate 1 is now available for comment!
sourmash v4.0.0 is coming!
SciPy 2021
As in 2020, this year’s SciPy Conference will be virtual, offering increased opportunities for attendance. 2020 set an attendance record of over 1,500, almost double the 2019 Austin, Texas conference. The event brings together attendees from industry, academia, national labs and more – showcasing projects, sharing knowledge and collaborating on code development. Author: Kristen Leiser, …Continue Reading
Job Posting | Events and Digital Marketing Coordinator
Job Title: Events and Digital Marketing Coordinator Position Overview The primary role of the Events and Digital Marketing Coordinator is to support and assist the Events Manager and the Community Communications and Marketing Manager to advance one of NumFOCUS’s primary missions of educating and building the community of users and developers of open source scientific […]
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Strategy, Digitalization and Global Trends – C Suite Reflections
Key points are presented from the first of a series of LinkedIn articles where JSR Board Chairman Mitsunobu Koshiba (‘Nobu’) provides thought provoking insights on business strategy in the context of trends in three time horizons. The short term is dominated by an increased acceptance of Modern Monetary Theory. The mid-term is a shift in …Continue Reading
Transition your Python project to use pyproject.toml and setup.cfg! (An example.)
Updating old Python packages, in this year of the PSF 2021!
SAM Coupé SCREEN$ Converter — Interrupt optimizing image converter
The SAM Coupé was a British 8 bit home computer that was pitched as a successor to the ZX Spectrum, featuring improved graphics and sound and higher processor speed.
The SAM Coupé's high-color MODE4 could manage 256x192 resolution graphics, with 16 colors from a choice of 128. Each pixel …
New Year’s resolutions for data scientists in 2021
The start of a new year is a popular time to recalibrate habits and set goals for improvement, both personally and professionally. First, it’s helpful to take stock of where things stand, in order to hone in on potential areas for betterment. In data science, the past year represented another step forward in the maturation of the discipline, especially with the onset of the COVID-19 pandemic. We saw researchers come together to harness the power of data and open-source software for public health, and concepts of statistical modeling become mainstream as we looked to curb the disease’s spread. At the same time, we had a glimpse into a future of division if we don’t pay heed to issues of bias in data and explainability in algorithms.A snakemake hack for checkpoints
snakemake checkpoints r awesome
Python packaging in 2021 - pain points and bright spots
At Quansight we have a weekly "Q-share" session on Fridays where everyone can share/demo things they have worked on, recently learned, or that simply seem interesting to share with their colleagues. This can be about anything, from new utilities to low-level performance, from building inclusive communities to how to write better documentation, from UX design to what legal & accounting does to support the business. This week I decided to try something different: hold a brainstorm on the state of Python packaging today.
The ~30 participants were mostly from the PyData world, but not exclusively - it included people with backgrounds and preferences ranging from C, C++ and Fortran to JavaScript, R and DevOps - and with experience as end-users, packagers, library authors, and educators. This blog post contains the raw output of the 30-minute brainstorm (only cleaned up for textual issues) and my annotations on it (in italics) which capture some of the discussion during the session and links and context that may be helpful. I think it sketches a decent picture of
SAM Coupé Reader — Preserving FRED retro disk magazine text, by decoding the Entropy Reader
FRED was the most popular disk magazine for the SAM Coupé 8 bit home computer.Published by Colin MacDonald out of sunny Monifieth, Scotland, the magazine ran from it's first issue in 1990 through to it's last (82) in 1998.
For the SAM networking project I was hoping there might …
Making SciPy's Image Interpolation Consistent and Well Documented
SciPy's ndimage module provides a powerful set of general, n-dimensional image processing operations, categorized into areas such as filtering, interpolation and morphology. Traditional image processing deals with 2D arrays of pixels, possibly with an additional array dimension of size 3 or 4 to represent color channel and transparency information. However, there are many scientific applications where we may want to work with more general arrays such as the 3D volumetric images produced by medical imaging methods like computed tomography (CT) or magnetic resonance imaging (MRI) or biological imaging approaches such as light sheet microscopy. Aside from spatial axes, such data may have additional axes representing other quantities such as time, color, spectral frequency or different contrasts. Functions in ndimage have been implemented in a general n-dimensional manner so that they can be applied across 2D, 3D or more dimensions. A more detailed overview of the module is available in the SciPy ndimage tutorial. SciPy's image functions are
micro:bit Space Invaders — MicroPython retro game in just 25 pixels
How much game can you fit into 25 pixels? Quite a bit it turns out.
This is a mini clone of arcade classic Space Invaders for the BBC micro:bit microcomputer. Using the accelerometer and two buttons for input, to can beat off wave after wave of aliens that advance …
What’s to come in 2021: 5 predictions for the future of data science and AI/ML
Since our founding in 2012, we’ve set out to create a movement that brings together data science practitioners, enterprises, and the open-source community. Data science has gone from a “nice-to-have” to a requisite for most businesses, and we’re proud to have witnessed its growth and expansion in recent years. But we also know there’s still much more to come.Run SAS in Python without Installation
Do you wish
(continued...)Welcoming Tania Allard as Quansight Labs co-director
Today I'm incredibly excited to welcome Tania Allard to Quansight as Co-Director of Quansight Labs. Tania (GitHub, Twitter, personal site) is a well-known and prolific PyData community member. In the past few years she has been involved as a conference organizer (JupyterCon, SciPy, PyJamas, PyCon UK, PyCon LatAm, JuliaCon and more), as a community builder (PyLadies, NumFOCUS, RForwards), as a contributor to Matplotlib and Jupyter, and as a regular speaker and mentor. She also brings relevant experience in both industry and academia - she joins us from Microsoft where she was a senior developer advocate, and has a PhD in computational modelling.
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Disnatia X/Potências de X
Nenhuma equipe de heróis me é tão querida quanto X-Men. Lá pelo final dos anos 90 comecei a colecionar por alguns anos, mas em seguida veio o fatídico aumento de preço com as Super-Heróis Premium, o que me acabou desmotivando a comprar. De lá para cá, acompanho esporadicamente, lendo notícias sobre, comprando uma ou outra… Continue a ler »Disnatia X/Potências de XDevelop a JupyterLab Winter Theme
JupyterLab 3.0 is about to be released and provides many improvements to the extension system. Theming is a way to extend JupyterLab and benefits from those improvements.
While theming is often disregarded as a purely cosmetic endeavour, it can greatly improve software. Theming can be great help for accessibility, and the Jupyter team pays attention to making the default appearance accessibility-aware by using sufficient contrast. For users with a high visual acuity you may also choose to increase the information density.
Theming can also be a great way to improve communication by increasing or decreasing emphasis of the user interface, which can be of use for teaching or presenting. Theming may also help with security, for example, by having a clear distinction between staging and production.
Finally Theming can be a great way to express oneself, for example, by using a branded version of software that fits well into a context, or expressing one's artistic preferences or opinions.
In the following blog post, we will show you step-by-step how you
Wish Christmas with Python and R
This post is dedicated to all the Python and R Programming Lovers...Flaunt your knowledge in your peer group with the following programs. As a data science professional, you want your wish to be special on eve of christmas. If you observe the code, you may also learn 1-2 tricks which you can use later in your daily tasks.
Method 1 : Run the following program and see what I mean
R Code
paste(intToUtf8(acos(log(1))*180/pi-13),
toupper(substr(month.name[2],2,2)),
paste(rep(intToUtf8(acos(exp(0)/2)*180/pi+2^4+3*2),2), collapse = intToUtf8(0)),
LETTERS[5^(3-1)], intToUtf8(atan(1/sqrt(3))*180/pi+2),
toupper(substr(month.abb[10],2,2)),
intToUtf8(acos(log(1))*180/pi-(2*3^2)),
toupper(substr(month.name[4],3,4)),
intToUtf8(acos(exp(0)/2)*180/pi+2^4+3*2+1),
intToUtf8(acos(exp(0)/2)*180/pi+2^4+2*4),
intToUtf8(acos(log(1))*180/pi-13),
LETTERS[median(0:2)],
intToUtf8(atan(1/sqrt(3))*180/pi*3-7),
sep = intToUtf8(0)
)
Python Code
import math
import datetime
(chr(int(math.acos(math.log(1))*180/math.pi-13)) \
+ datetime.date(1900, 2, 1).strftime('%B')[1] \
+ 2 * datetime.date(1900, 2, 1).strftime('%B')[3] \
+ datetime.date(1900, 2, 1).strftime('%B')[7] \
+ chr(int(math.atan(1/math.sqrt(3))*180/math.pi+2)) \
+ datetime.date(1900, 10, 1).strftime('%B')[1] \
+ chr(int(math.acos(math.log(1))*180/math.pi-18)) \
+ datetime.date(1900, 4, 1).strftime('%B')[2:4] \
+ chr(int(math.acos(math.exp(0)/2)*180/math.pi+2**4+3*2+1)) \
+ chr(int(math.acos(math.exp(0)/2)*180/math.pi+2**4+2*4)) \
+ chr(int(math.acos(math.log(1))*180/math.pi-13)) \
+ "{:c}".format(97) \
+ chr(int(math.atan(1/math.sqrt(3))*180/math.pi*3-7))).upper()
Turn on computer speakers before running the code.
R Code
install.packages("audio")
library(audio)
christmas_file <- tempfile()
download.file("https://sites.google.com/site/pocketecoworld/merrychristmas1.wav", christmas_file, mode = "wb")
xmas
On the Link Between Optimization and Polynomials, Part 2
An analysis of momentum can be tightened using a combination Chebyshev polynomials of the first and second kind. Through this connection we'll derive one of the most iconic methods in optimization: Polyak momentum.
How to use variable in a query in pandas
Suppose you want to reference a variable in a query in pandas package in Python. This seems to be a straightforward task but it becomes daunting sometimes. Let's discuss it with examples in the article below.Let's create a sample dataframe having 3 columns and 4 rows. This dataframe is used for demonstration purpose.
import pandas as pd
df = pd.DataFrame({"col1" : range(1,5),
"col2" : ['A A','B B','A A','B B'],
"col3" : ['A A','A A','B B','B B']
})
A A in column col2@. NumFOCUS hires Open Source Developer Advocate!
NumFOCUS is pleased to announce that Arliss Collins has been hired as our organization’s first Open Source Developer Advocate. Founded in 2012, NumFOCUS has finally grown beyond just providing non-technical needs for our 40+ sponsored projects! As our first technical hire, Arliss will work to help understand our projects from a technical perspective and […]
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Digital Transformation in Practice
Taken from the webinar, the frequent strategy of digitalization-layering digital tools and technology onto existing processes-provides incremental value, which soon flattens out. At the other end, companies born with digital DNA (for example an Amazon) are capable of incredible innovation and adaptation. The reality is, most companies must transform to develop digital DNA. Applied digital …Continue Reading
A Pivotal Time in NumFOCUS’s Project Aimed DEI Efforts
NumFOCUS is pleased to announce the launch of our Contributor Diversification & Retention Research Project funded by a grant from the Gordon and Betty Moore Foundation. “We were eager to support NumFOCUS’s diversity initiative because it aims to get to the heart of what is preventing greater participation in data science. We are hopeful that […]
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Data literacy is for everyone - not just data scientists
Today more than ever before, businesses around the world are embracing data and data-driven decisions as key aspects of operating a modern, successful organization. Yet, despite the surface-level recognition of the importance of data and the insights it can provide, the process of harnessing data and mining those insights is often perceived as abstract and mysterious—a domain that solely belongs to experts with PhDs.Up the ‘Digital Level’ of Your R+D Lab
Image: A key role of materials and chemistry R&D researchers is to invert the primary function of their labs – that of creating materials from chemical structures, formulations and processes – to one of determining the inputs that will produce materials with the desired properties with minimal iteration. This process can be significantly accelerated by …Continue Reading
The Challenges of Scaling Digital Advances in Life Sciences
An illustration by Michelle Macroni evokes the complex web of ingredients to possibilities in life sciences through applied digital innovation in R&D. Author: Robyn Cardwell, Ph.D., Director, Life Sciences Solutions Incremental Advances Versus Created Possibilities Many of the improvements in life sciences R&D labs today come through introducing digital technologies to existing processes, with an …Continue Reading
Enthought at the 2020 Materials Research Society Conference
Machine learning classification model learns complex printability window for inkjet printed polymer films using data from automated formulation and printing system. Authors: Michael Heiber, Ph.D., Applications Engineer and Frank Longford, Ph.D., Scientific Software Developer The Materials Research Society (MRS) is a global community of materials researchers, built to promote the advancement of interdisciplinary materials research and …Continue Reading
Anaconda Announces Multi-Year Partnership with NumFOCUS
A key stakeholder in the open source scientific computing ecosystem has further formalized their long-standing partnership with NumFOCUS. Anaconda, the Austin, Texas-based software development and consulting company which provides global distribution of Python and R software packages, last month introduced their Anaconda Dividend Program. Through this initiative, Anaconda plans to direct a portion of their […]
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A second CZI grant for NumPy and OpenBLAS
I am happy to announce that NumPy and OpenBLAS have once again been awarded a grant from the Chan Zuckerberg Initiative through Cycle 3 of the Essential Open Source Software for Science (EOSS) program. This new grant totaling $140,000 will fund part of our efforts to improve usability and sustainability in both projects and is excellent news for the scientific computing community, which will certainly benefit from this work downstream.
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NumFOCUS Receives Support from Heising-Simons
NumFOCUS is grateful to announce that we received a grant award of $50,000 in October from the Heising-Simons Foundation. This generous grant funding will provide general support resources to NumFOCUS and will benefit all of our Sponsored and Affiliated Projects as well as our organization’s several programs and initiatives. “This grant award from Heising-Simons will […]
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Digital-centric R+D Laboratories
To have a transformative impact, labs must reinvent workflows through digital technologies and skills, adopting a strong data culture. A figure from the white paper captures Level 5, where innovation through digital-centric systems confidently produces new materials that meet customer specifications orders of magnitude faster than before, enabling broader business transformation. Authors: Chris Farrow, Ph.D., …Continue Reading
Bate-papo com Vivi Reis sobre tecnologia e política
Hoje à noite (5 de novembro) às 20h conversarei com Vivi Reis, candidata a vereadora pelo PSOL em Belém. No bate-papo vamos focar bastante sobre temas que entrelaçam tecnologia e política. Entre os pontos, teremos o Escritório de Dados, dados e políticas públicas, software livre na administração pública, conectividade em Belém, inclusão digital, aplicativos cidadãos,… Continue a ler »Bate-papo com Vivi Reis sobre tecnologia e políticaNew features in Spyder 4's new debugger!
IPython is a great improvement over the standard Python interpreter, bringing many enhancements such as autocompletion and "magic" commands. When debugging, however, many of these features become inaccessible. With Spyder, we aim to bring back these capabilities and more for a truly premium debugging experience! (And believe me, I use this debugger a lot, and not only because I write code that might contain bugs :p).
In this post, I will describe the debugger improvements we've already made in Spyder 4, as well as those that are already implemented or under review for Spyder 4.2 and beyond.
Make the debugger more like IPythonIPython improves on the stock Python interpreter by adding syntax highlighting, completion, and history. We have done the same for the debugger!
The output is prettier (and easier to read) than plain black text, as it was in Spyder 3!
Code completion and history for the debugger use the same functionality as the IPython console, so you should not notice any difference in behaviour. Just press
(continued...)JupyterCon 2020: Code of Conduct Reports
Following the reports to the NumFOCUS Code-of-Conduct committee on Jeremy Howard’s keynote at JupyterCon 2020, and the controversy that followed, the NumFOCUS Code of Conduct Committee issued a public apology to Jeremy Howard and escalated the case to the board of directors. The context In his keynote at JupyterCon 2020, Jeremy Howard gave a point-by-point rebuttal of […]
The post JupyterCon 2020: Code of Conduct Reports appeared first on NumFOCUS.
Public Apology to Jeremy Howard
We, the NumFOCUS Code of Conduct Enforcement Committee, issue a public apology to Jeremy Howard for our handling of the JupyterCon 2020 reports. We should have done better. We thank you for sharing your experience and we will use it to improve our policies going forward. We acknowledge that it was an extremely stressful experience, […]
The post Public Apology to Jeremy Howard appeared first on NumFOCUS.
Money and California Propositions (2020)
Ten years ago, I made some plots for how much money was contributed to and spent by the various proposition campaigns in California.
I decided to update these for this election, and here's the result:
Just in case you didn't get the full picture, here is the same data plotted on a common scale:
So, whereas 10 years ago, we had a total of ~$58 million on the election, the overwhelming amount of in support, this time, we had ~$662 million, an 11 fold increase!
The Cal-Access Campaign Finance Activity: Propositions & Ballot Measures source I used last time was still there, but there are way more propositions this time (12 vs 5), and the money details are broken out by committee, with some propositions have a dozen committees. Another wrinkle is that website has protected by some fancy scraping protection. I could browse it just fine in Firefox, even with Javascript turned off, but couldn't download it using wget, curl,
(continued...)TARDIS Joins NumFOCUS as a Sponsored Project
NumFOCUS is pleased to announce the newest addition to our fiscally sponsored projects: TARDIS TARDIS is an open-source, Monte Carlo based radiation transport simulator for supernovae ejecta. TARDIS simulates photons traveling through the outer layers of an exploded star including relevant physics like atomic interactions between the photons and the expanding gas. The TARDIS collaboration […]
The post TARDIS Joins NumFOCUS as a Sponsored Project appeared first on NumFOCUS.
Por um Escritório de Dados para Políticas Públicas em Belém
Dados sempre foram determinantes para a concepção e implementação de políticas públicas nas mais diferentes esferas governamentais. Acompanhamentos de indicadores econômicos, de saúde, de violência, de deslocamentos urbanos, de distribuição espacial da população, de áreas de cobertura de locais de lazer, entre outros, são apenas alguns dos dados que podem embasar o desenho de políticas… Continue a ler »Por um Escritório de Dados para Políticas Públicas em BelémTranslating Web Page while Scraping
Suppose you need to scrape data from a website after translating the web page in R and Python. In google chrome, there is an option (or functionality) to translate any foreign language. If you are an english speaker and don't know any other foreign language and you want to extract data from the website which does not have option to convert language to English, this article would help you how to perform translation of a webpage.
NumFOCUS Earns Transparency Recognition from GuideStar
Earlier this week, NumFOCUS earned our first-ever Silver Seal of Transparency from GuideStar, an independent organization which classifies nonprofit organizations based on multiple metrics pertaining to transparency and accountability. Fewer than 5% of US-based nonprofits have received this type of recognition. “This respected acknowledgment comes as we prepare to enter our year-end fundraising season,” said […]
The post NumFOCUS Earns Transparency Recognition from GuideStar appeared first on NumFOCUS.
SEG 2020 Attendees Asked. We Answered.
In an example away from seismic, this shows a thin section, where machine learning techniques can be applied across multiple images, ones previously unused due to the significant demands of expert time, and difficulties in organizing and sharing data. See a demo at: https://www.enthought.com/industries/oil-and-gas/core-analysis/ Author: Brendon Hall, Ph.D., Director, Energy Solutions The SEG 2020 …Continue Reading
Deep Learning Can Now Interpret Seismic the Way Experts Do
The SubsurfaceAI custom deep learning application for seismic allows experts to annotate data, identify sequences and, in this example, define a fault complex. This forms the basis of a workflow that allows a seismic expert to apply deep learning to ‘interpret the way experts do,’ creating bespoke models for seismic interpretation. Author: Ben Lasscock, Ph.D., …Continue Reading
Learn Python for Data Science
 |
| Data Science with Python Tutorial |
aka: also known as
I was chatting with Anthony Scopatz last week, and one of the things we covered
was how it'd be cool to have a subcommand launcher, kind of like git, where
the subcommands were swappable. If you're not familiar, git automatically
calls out to git-something (note the dash) whenever you run
$ git something
and something is not one of the builtin git commands. For me, ~/bin is in my PATH, so
$ git lost git: 'lost' is not a git command. See 'git --help'. $ echo "echo how rude!" > ~/bin/git-lost; chmod +x ~/bin/git-lost $ git lost how rude!
And so what Anthony was talking about was having two commands that are supposed
to do the same thing, and being able to switch between them. For example: maybe
we have git-away and git-gone and both
of them perform a similar function, and we wish call our preferred one when we run git lost.
One way to do this would be to copy or symlink our chosen version as git-lost,
and replace that file whenever
How to rename columns in Pandas Dataframe
pandas which simplifies doing these kind of data operations. 
First step is to install pandas package if it is not already installed. You can check if the package is installed on your machine by running
Seqtembro de eventos virtuais e gratuitos sobre Qt e KDE
(Ok a piada com seqtembro funciona melhor na versão em inglês, seqtember, mas simbora) Por uma grande coincidência, obra do destino, ou nada disso, teremos um Setembro de 2020 repleto de eventos virtuais e gratuitos de alta qualidade sobre Qt e KDE. Começando de 4 à 11 do referido mês teremos o Akademy 2020, o… Continue a ler »Seqtembro de eventos virtuais e gratuitos sobre Qt e KDECARLsim5 Released!
IntroductionCARLsim5 is an efficient, easy-to-use, GPU-accelerated library for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail. It allows execution of networks of Izhikevich spiking neurons with realistic synaptic dynamics using multiple off-the-shelf GPUs and x86 CPUs. The simulator provides a PyNN-like programming interface in C/C++, which allows for details and parameters to be specified at the synapse, neuron, and network level.
The present release, CARLsim 5, builds on the efficiency and scalability of earlier releases (Nageswaran et al., 2009; Richert et al., 2011, and Beyeler et al., 2015; Chou et al., 2018). The functionality of the simulator has been greatly expanded by the addition of a number of features that enable and simplify the creation, tuning, and simulation of complex networks with spatial structure.
New Features
pyCARL is a interface between the simulator-independent language PyNN and a CARLsim5 based back-end. In other words, you can write the code for a SNN model once, using the
(continued...)Improved workflows-as-applications: tips and tricks for building applications on top of snakemake
Writing applications around workflow systems, take 2.
O que será do Lev com o “fim” da Saraiva?
Disclaimer: apesar do sobrenome, não tenho qualquer relação com a Saraiva. E também não tenho respostas para a pergunta do título. Como usuário do Lev acompanho com interesse a agonia da Saraiva. A rede de livrarias, uma das maiores do Brasil, está há anos em um imbróglio judicial devendo diversas editoras, em um processo que… Continue a ler »O que será do Lev com o “fim” da Saraiva?Dask Life Sciences Fellow [Open Job]
Dask is an open-source library for parallel computing in Python that interoperates with existing Python data science libraries like Numpy, Pandas, Scikit-Learn, and Jupyter. Dask is used today across many different scientific domains. Recently, we’ve observed an increase in use in a few life sciences applications: Large scale imaging in microscopy Single cell analysis Genomics […]
The post Dask Life Sciences Fellow [Open Job] appeared first on NumFOCUS.
STX Next, Python development company, uses Spyder to improve their workflow
STX Next, one of Europe's largest Python development companies, has shared with us how Spyder has been a powerful tool for them when performing data analysis. It is a pleasure for us on the Spyder team to work every day to improve the workflow of developers, scientists, engineers and data analysts. We are very glad to receive and share a STX Next testimonial about Spyder, along with an interview with one of their developers, Michael Wiśniewski, who has found Spyder very useful in his job.
In an era of a continuously growing demand for analysis of vast amounts of data, we are facing increasingly complex tasks to perform. Sure, we are not alone—there are many great tools designed for scientists and data analysts. We have NumPy, SciPy, Matplotlib, Pandas, and others. But, wouldn't it be nice to have one extra tool that could combine all the required packages into one compact working environment? Asking this question is precisely how
(continued...)Educação Vigiada
Essa época de pandemia tem sido de produção em muitas frentes, o que infelizmente implica na redução de tempo para divulgação das mesmas aqui no blog. Nesse post quero me redimir dessa falta falando de um dos projetos que acho dos mais importantes que contribui recentemente, o Educação Vigiada. Há alguns meses o projeto Educação… Continue a ler »Educação VigiadaEngrenagem Ep. 04 – Aplicações KDE favoritas dos KDErs brasileiros
Nesse sábado dia 11/07 às 10h o KDE Brasil vai voltar com episódios do Engrenagem, o videocast da comunidade brasileira (que está há 4 anos sem episódios inéditos 🙂 ). Para retomar os trabalhos, o episódio trará 6 colaboradores brasileiros (Ângela, Aracele, Caio, Filipe (eu), Fred e Tomaz) falando de suas aplicações KDE favoritas –… Continue a ler »Engrenagem Ep. 04 – Aplicações KDE favoritas dos KDErs brasileirosWriting docs is not just writing docs
This blogpost was originally published on the Quansight Labs website.
I joined the Spyder team almost two years ago, and I never thought I was going to end up working on docs. Six months ago I started a project with CAM Gerlach and Carlos Cordoba to improve Spyder’s documentation. At first, I didn’t actually understand how important docs are for software, especially for open source projects. However, during all this time I’ve learned how documentation has a huge impact on the open-source community and I’ve been thankful to have been able to do this. But, from the beginning, I asked myself “why am I the ‘right person’ for this?”
Improving Spyder’s documentation started as part of a NumFOCUS Small Development Grant awarded at the end of last year. The goal of the project was not only to update the documentation for Spyder 4, but also to make it more user-friendly, so users can understand Spyder’s key concepts and get started with it more
(continued...)Sobre o livro “Uma História de Desigualdade”
Finalizei a leitura do premiado livro do Pedro de Souza, “Uma História de Desigualdade – A Concentração de Renda entre os Ricos no Brasil 1926 – 2013“, baseado na tese que defendeu no programa de sociologia da UnB. É um livro de fôlego e que faz jus a todos os elogios que recebeu desde o… Continue a ler »Sobre o livro “Uma História de Desigualdade”Thanking the people behind Spyder 4
This blogpost was originally published on the Quansight Labs website.
After more than three years in development and more than 5000 commits from 60 authors around the world, Spyder 4 finally saw the light on December 5, 2019! I decided to wait until now to write a blogpost about it because shortly after the initial release, we found several critical performance issues and some regressions with respect to Spyder 3, most of which are fixed now in version 4.1.3, released on May 8th 2020.
This new release comes with a lengthy list of user-requested features aimed at providing an enhanced development experience at the level of top general-purpose editors and IDEs, while strengthening Spyder's specialized focus on scientific programming in Python. The interested reader can take a look at some of them in previous blog posts, and in detail in our Changelog. However, this post is not meant to describe those improvements, but to acknowledge all people that contributed
(continued...)Technical discussions are hard; a few tips
Note
This post discuss the difficulties of communicating while developing open-source projects and tries to gives some simple advice.
A large software project is above all a social exercise in which technical experts try to reach good decisions together, for instance on github pull requests. But communication is difficult, in …
Lazy River of Curious Content 0
This is the first post of what I'm calling a Lazy
River of Curious Content.
This is a way to review stuff that I've been doing, dealing with, or find
interesting during the week recently (This was
originally written two weeks ago, May 3rd, my shoddy internet connectivity kept
me from posting it.). I'm loosely following the format that Justin Sherrill
uses with great effect over at
https://dragonflydigest.com
Learn NixOS by turning a Raspberry Pi into a Wireless Router Friend of the show, Anthony Scopatz, tried NixOS for the first time and provides a detailed report:
"While I had read the NixOS pamphlets, and listened politely when the faithful came knocking on my door at inconvenient times, I had never walked the path of functional Linux enlightenment myself"
Reading through that made me file away a todo of writing up how I use propellor (and why). But those todo sometimes just pile up for a while...
An interview of one of my long time nerd-crushes, Rob Pike. The questions focus on the Go programming
(continued...)sourmash databases as zip files, in sourmash v3.3.0
Use compressed databases directly!
LaKademy 2019
Em novembro passado, colaboradores latinoamericanos do KDE desembarcaram em Salvador/Brasil para participarem de mais uma edição do LaKademy – o Latin American Akademy. Aquela foi a sétima edição do evento (ou oitava, se você contar o Akademy-BR como o primeiro LaKademy) e a segunda com Salvador como a cidade que hospedou o evento. Sem problemas… Continue a ler »LaKademy 2019Akademy 2019
Em setembro de 2019 a cidade italiana de Milão sediou o principal encontro mundial dos colaboradores do KDE – o Akademy, onde membros de diferentes áreas como tradutores, desenvolvedores, artistas, pessoal de promo e mais se reúnem por alguns dias para pensar e construir o futuro dos projetos e comunidade(s) do KDE Antes de chegar… Continue a ler »Akademy 2019Creating the ultimate terminal experience in Spyder 4 with Spyder-Terminal
This blogpost was originally published on the Quansight Labs website.
The Spyder-Terminal project is revitalized! The new 0.3.0 version adds numerous features that improve the user experience, and enhances compatibility with the latest Spyder 4 release, in part thanks to the improvements made in the xterm.js project.
First, we were able to update all the old JavaScript files to use ES6/JSX syntax and the tests for the client terminal. This change simplified the code base and maintenance and allows us to easily extend the project to new functionalities that the xterm.js API offers. In order to compile this code and run it inside Spyder, we migrated our deployment to Webpack.
Multiple shells per operating systemIn the new release, you now have the ability to configure which shell to use in the terminal. On Linux and UNIX systems, bash, sh, ksh, zsh, csh, pwsh, tcsh, screen, tmux, dash and rbash are supported, while cmd and powershell are the
Software and workflow development practices (April 2020 update)
How we develop software and workflows in the DIB Lab, in 2020.
Is it getting better yet? — An optimistic visual guide to the Coronavirus pandemic
As the apocalypse rumbles on, I found myself wondering "Is it getting any better?"
Daily updates of spiralling case numbers (and worse, deaths) does little to give a sense of whether we're getting to, or already past, the worst of it.
To answer that question for myself and you, I …