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Python

Pandas DataFrame Visualization Tools pbpython.com

Published January 14, 2021 under Python

Pandas DataFrame Visualization Tools

One of Excel’s benefits is that it offers an intuitive and powerful graphical interface for viewing your data. In contrast, pandas + a Jupyter notebook offers a lot of programmatic power but limited abilities to graphically display and manipulate a DataFrame view.

There are several tools in the Python ecosystem that are designed to fill this gap. They range in complexity from simple JavaScript libraries to complex, full-featured data analysis engines. The one common denominator is that they all provide a way to view and selectively filter your data in a graphical format. From this point of commonality they diverge quite a bit in design and functionality.

This article will review several of these DataFrame visualization options in order to give you an idea of the landscape and evaluate which ones might be useful for your analysis process.

Excel, Pandas

NumPy Illustrated: The Visual Guide to NumPy medium.com

Published January 13, 2021 under Python

NumPy Illustrated: The Visual Guide to NumPy

NumPy is a fundamental library that most of the widely used Python data processing libraries are built upon (pandas, OpenCV), inspired by (PyTorch), or can efficiently share data with (TensorFlow, Keras, etc). Understanding how NumPy works gives a boost to your skills in those libraries as well. It is also possible to run NumPy code with no or minimal changes on GPU.

Numpy

Automate Excel with Python Tutorial youtube.com

Published October 1, 2020 under Python

Excel, Pandas

Array programming with NumPy nature.com

Published September 20, 2020 under Python

Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. 

Numerical Methods, Numpy

NumPy Fundamentals for Data Science and Machine Learning github.io

Published July 28, 2020 under Python

NumPy Fundamentals for Data Science and Machine Learning

This post reviews NumPy main components and functionality, with attention to the needs of Data Science and Machine Learning practitioners, and people who aspire to become a data professional. 

Data Science, Machine Learning, Numpy

Designing an energy arbitrage strategy with linear programming https://www.steveklosterman.com

Published May 12, 2020 under Python

Designing an energy arbitrage strategy with linear programming

The price of energy changes hourly, which opens up the possibility of temporal arbitrage: buying energy at a low price, storing it, and selling it later at a higher price. To successfully execute any temporal arbitrage strategy, some amount of confidence in future prices is required, to be able to expect to make a profit. In the case of energy arbitrage, the constraints of the energy storage system must also be considered. For example, batteries have limited capacity, limited rate of charging, and are not 100% efficient in that not all of the energy used to charge a battery will be available later for discharge.

Quant Trading, Trading

How to Download Stock Fundamentals Data with Python theautomatic.net

Published May 6, 2020 under Python

How to Download Stock Fundamentals Data with Python

In this post we will explore how to download fundamentals data with Python. We’ll be extracting fundamentals data from Yahoo Finance using the yahoo_fin package. For more on yahoo_fin, including installation instructions, check out its full documentation here.

Investing, Trading

Free foreign exchange rates API exchangerate.host

Published May 3, 2020 under Python

Exchange rates API is a simple and lightweight free service for current and historical foreign exchange rates.

API

Automating an Insider Trading Dashboard with Python and Tableau | Part 2: Collecting Live Stock Data youtube.com

Published January 8, 2020 under Python

Algorithmic Trading

Automating an Insider Trading Dashboard with Python and Tableau: Part 1 youtube.com

Published January 8, 2020 under Python

Algorithmic Trading

Tips for Selecting Columns in a DataFrame pbpython.com

Published December 8, 2019 under Python

This article will discuss several tips and shortcuts for using iloc to work with a data set that has a large number of columns. Even if you have some experience with using iloc you should learn a couple of helpful tricks to speed up your own analysis and avoid typing lots of column names in your code.

Data Science, Pandas

Cleaning Up Currency Data with Pandas pbpython.com

Published November 25, 2019 under Python

This article summarizes how to clean up messy currency fields and convert them into a numeric value for further analysis. The concepts illustrated here can also apply to other types of pandas data cleanup tasks.

Data Science, Pandas, Trading

Algorithmic trading based on Technical Analysis in Python medium.com

Published October 25, 2019 under Python

Investing was always associated with large amounts of money, both in terms of the invested amount as well as costs associated with it. Here at BUX, we want to make investing accessible to everyone. That is why we recently launched BUX Zero in the Netherlands and other European countries will follow soon! BUX Zero is a zero-commission stock trading app, which makes investing not only accessible but also easy to do directly from your phone.

Algorithmic Trading, Technical Analysis

Tutorial: Transforming Data with Python Scripts and the Command Line dataquest.io

Published October 5, 2019 under Python

In this tutorial, we’re going to dig into how to transform data using Python scripts and the command line.

But first, it’s worth asking the question you may be thinking: “How does Python fit into the command line and why would I ever want to interact with Python using the command line when I know I can do all my data science work using IPython notebooks or Jupyter lab?”

Notebooks are great for quick data visualization and exploration, but Python scripts are the way to put anything we learn into production. Let’s say you want to make a website to help people make Hacker News posts with ideal headlines and submission times. To do this, you’ll need scripts.

Data Science

Turbo-Charging Data Science with AutoML brighttalk.com

Published September 27, 2019 under Python

Although there are an increasing number of commercial AutoML products, the open-source ecosystem has been innovating here as well. In the early days of the AutoML movement, the focus was on those looking to leverage the power of ML models without a background in data science – citizen data scientists. Today, however, AutoML tools have a lot to offer experts too. 

Machine Learning

Lectures in Quantitative Economics with Python quantecon.org

Published September 27, 2019 under Python

Economics, Statistics

Building a Parallel Task API with Celery medium.com

Published September 7, 2019 under Python

An introduction to running parallel tasks with Celery, plus how and why we built an API on top of Celery’s Canvas task primitives.

One of the technology goals of Zymergen is to empower biologists to explore genetic edits of microbes in a high throughput and highly automated manner. The Computational Biology team at Zymergen is responsible for building software to help scientists design and execute these genetic edits. (For a brief overview, see our Zymergen 101 tutorial).

Celery

How to Use Binder and Python for Reproducible Research marsja.se

Published July 28, 2019 under Python

In this post we will learn how to create a binder so that our data analysis, for instance, can be fully reproduced by other researchers. That is, in this post we will learn how to use binder for reproducible research.

Data, Research

A Visual Intro to NumPy and Data Representation github.io

Published July 1, 2019 under Python

Numpy

Python at Netflix medium.com

Published May 3, 2019 under Python

As many of us prepare to go to PyCon, we wanted to share a sampling of how Python is used at Netflix. We use Python through the full content lifecycle, from deciding which content to fund all the way to operating the CDN that serves the final video to 148 million members. We use and contribute to many open-source Python packages, some of which are mentioned below. If any of this interests you, check out the jobs site or find us at PyCon. We have donated a few Netflix Originals posters to the PyLadies Auction and look forward to seeing you all there.

Programming

Awesome Data Science with Python github.com

Published April 19, 2019 under Python

A curated list of awesome resources for practicing data science using Python, including not only libraries, but also links to tutorials, code snippets, blog posts and talks. So. Much. Python.

Awesome, Data Science

Introduction to Anomaly Detection in Python floydhub.com

Published April 19, 2019 under Python

The very basic idea of anomalies is really centered around two values – extremely high values and extremely low values. Then why are they given importance? In this article, we will try to investigate questions like this. We will see how they are created/generated, why they are important to consider while developing machine learning models, how they can be detected.

Anomaly Detection, Time Series Analysis

Pyodide: Bringing the scientific Python stack to the browser mozilla.org

Published April 18, 2019 under Python

Pyodide is an experimental project from Mozilla to create a full Python data science stack that runs entirely in the browser.

Programming

Comprehensive Python Cheatsheet github.io

Published April 9, 2019 under Python

Programming

How to Version Control Jupyter Notebooks nextjournal.com

Published April 9, 2019 under Python

Jupyter

Monte Carlo Simulation with Python pbpython.com

Published March 3, 2019 under Python

Monte Carlo, Numerical Methods

Python and Finance – Power up Your Spreadsheets toptal.com

Published February 2, 2019 under Python

Excel, Tutorial

Time Series Analysis with Pandas dataquest.io

Published February 2, 2019 under Python

Quant Trading, Time Series Analysis

Getting Started with the NAG Library for Python youtube.com

Published February 2, 2019 under Python

NAG, Numerical Methods, Tutorial

Matplotlib Tutorial – A Complete Guide to Python Plot machinelearningplus.com

Published February 2, 2019 under Python

Data Visualization, Matplotlib

A Friendly Introduction to Linear Regression youtube.com

Published December 31, 2018 under Python

Linear Regression, Statistics

Monte Carlo Power Analysis deliveroo.engineering

Published December 31, 2018 under Python

Monte Carlo, Simulation

Tutorial to set up TensorFlow Object Detection API on the Raspberry Pi github.om

Published December 31, 2018 under Python

Computer Vision, Raspberry Pi, TensorFlow

Problem Solving with Algorithms and Data Structures using Python interactivepython.org

Published December 20, 2018 under Python

Algorithms

Top 50 matplotlib Visualizations machinelearningplus.com

Published December 6, 2018 under Python

Data Visualization, Matplotlib

Running Flask on Kubernetes testdriven.io

Published September 25, 2018 under Python

Devops, Flask, Kubernetes

An A-Z of useful Python tricks freecodecamp.org

Published September 5, 2018 under Python

Python MySQL Tutorial pynative.com

Published August 10, 2018 under Python

MySQL, Tutorial

Crypto portfolio optimization with Python and Tensorflow medium.com

Published August 10, 2018 under Python

Cryptocurrency, Optimization, TensorFlow

An End-to-End Project on Time Series Analysis and Forecasting with Python towardsdatascience.com

Published July 13, 2018 under Python

Forecasting, Time Series Analysis

Cleaning Up Debt: A pandas Approach medium.com

Published July 4, 2018 under Python

Data, Pandas

Test-Driven Web Development with Python (free) obeythetestinggoat.com

Published June 28, 2018 under Python

TDD, Testing

Download Intraday Stock Data with IEX and Parquet blackarbs.com

Published June 18, 2018 under Python

Data, IEX, Parquet

Getting started with Apache Kafka in Python adnansiddiqi.me

Published June 16, 2018 under Python

Big Data, Kafka

Monte Carlo method in Python harderchoices.com

Published June 13, 2018 under Python

Numerical Methods

Temporal Difference Learning in Python harderchoices.com

Published June 13, 2018 under Python

Reinforcement Learning

Forecasting Time-Series Data at Scale speakerdeck.com

Published June 8, 2018 under Python

Time Series

TensorFlow Python Interoperability with Swift github.com

Published May 4, 2018 under Python

Swift, TensorFlow

Visualizing Pandas’ Pivoting and Reshaping Functions github.io

Published May 4, 2018 under Python

Pandas

Developing an Asynchronous Task Queue in Python testdriven.io

Published May 4, 2018 under Python

Task Queue

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