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Learning Data Science

Many people have landed jobs as data scientists without any formal training because the internet is abundant in free resources for learning data science. This section includes tutorials for analytical languages such as SQL, Python, and R, career advice, and how-to posts about performing common tasks like A/B testing and

Art from Code

This workshop provides a hands-on introduction to generative art in R. You’ll learn artistic techniques that generative artists use regularly in their work including flow fields, iterative function systems, and more.-Danielle Navarro

The Data Config

A humble YAML file, with ambitions for more.-benn.substack

Python’s super() Considered Super!

If you aren’t wowed by Python’s super() builtin, chances are you don’t really know what it’s capable of doing or how to use it effectively.-Deep Thoughts by Raymond Hettinger

Success Metrics for Product Analytics

Product data scientists are not only there to inform decisions making with data, but also to quantify risks.-The Corner

Critical Dataset Studies Reading List

Datasets powerfully construct model worldviews, so they're important to study.-Knowing Machines

5 Tips for Using pins with R

The pins package makes it easy to share data, models, and other R objects across projects and with your colleagues.-sellorm

A Beginner's Introduction to Mixed Effects Models

For when you need to venture beyond the safe and comfortable land of basic linear regression models.-Meghan Hall

PostgreSQL Lessons We Learned the Hard Way

Investigating, understanding, fixing, and preventing troublesome database locks.-Compass True North

The Guide to Data Versioning

Already familiar with versioning code with git? Here’s how it works to version data using the same abstractions.-Whispering Data

A First Look at PyScript: Python in the Web Browser

This tutorial will get you up to speed with the much-loved PyScript, while the official documentation is still in the making.-Real Python

The Future of Data Science Anthology

“We named this project to intentionally reflect our desire to design for a future in data science: a future with more of a focus on creativity, yes, but also a future with more transparency, inclusiveness, and personal responsibility.”-Data Science by Design

Data Quality and Testing Frameworks

A short introduction to open-source data quality & testing tools — dbt, Deequ, and Great Expectations.-Servian

Software Development Resources for Data Scientists

Version control, automated testing, and other dev skills help create reproducible, production-ready code and tools.-R Studio Blog

Data Is an Art, Not Just a Science—and Storytelling Is the Key

Data science is a balancing act. Math and science have their role to play, but so do art and communication.-Shopify Engineering

Preston’s Paradox

Suppose every woman has fewer children than her mother. Average fertility would decrease and population growth would slow, right? Actually, no. According to Preston's paradox, fertility could increase, decrease, or stay the same.-Probably Overthinking It

Data Types in Arrow and R

Apache Arrow is a powerful multi-language toolbox for data exchange and data analysis. But to use it effectively you do need to learn more low-level concepts that R users like to skim over.-Notes from a Data Witch

Data Tests and the Broken Windows Theory

Despite all their promise, data tests too often end up not living up to their full potential.-Inside Data by Mikkel Dengsøe


This end-to-end real-time event collection, pipelining, and aggregation system allows you to rapidly bootstrap streaming analytics.-Silverton.io

A Better Way to Lie With Statistics

It’s not the data that gets us, but the adjectives that describe it.-benn.substack

Faking It: How to Simulate Complex Data Generation Processes in R, Tidyverse Edition

Data simulation is central to much of a social scientist’s work. Unfortunately, it’s rarely taught in graduate schools. This post attempts to rectify that.-A. Jordan Nafa

Bring Back Scenario Analysis!

Scenario analysis, while often being quantitatively not-that-complex, is different from descriptive and prescriptive statistics in one key way that is culturally very hard for data people: it forces you to assume things you don’t know.-The Analytics Engineering Roundup

IVS 0.1.0

Check out this new R package for working with intervals (like date ranges)!-Davis Vaughan

Transitioning from Academia to Industry

Some thoughts on a strange transformation that a few data folks go through, from the perspective of someone who did it slightly later than most.-Notes from a Data Witch

Lessons from the COVID Data Wizards

Data dashboards have been an important part of pandemic response and planning. What have their developers learned about communicating science in a crisis?-Nature

The Most Important Thing to Understand About Queues

“It’s counterintuitive, but once you understand it, you’ll have deeper insight into the behavior not just of CPUs and database thread pools, but also grocery store checkout lines, ticket queues, highways–really just a mind-blowing collection of systems.”-Dan Slimmon

The Froyo Data Shop

Data democratization doesn’t start at data discovery—it starts at data testing and context building.-Sarah’s Newsletter

Cohort Analysis: An Introductory Guide for Better Retention

When done right, cohort analysis can unearth valuable information about different user segments that can help go-to-market and product departments focus their efforts with nuanced insights.-Mode Blog

Best (Artistic) Practices in R

Parameter restriction, reproducibility, and documentation are key.-Nicola Rennie

Programming as a Vehicle for Math

Most programs that rely on mathematics have an algorithm or formula at their core that’s indecipherable without learning the math it’s based on. But somehow it’s simple once you understand the math itself.-Halfspace

How I Became a "Not-Beginner" in R

How do you refer to yourself when you’re not a beginner anymore, but not yet an expert?-The Tidy Trekker

Building a Team of Internal R Packages

As your organization builds R packages for internal use, bear in mind that they have unique challenges (such as a smaller developer community) and opportunities (such as an intimate understanding of the problem space and over-arching organizational goals).-Emily Riederer

Low Process Culture, High Process Culture

This is a useful read for literally anyone, not just data folks.-Accidentally in Code

What's in a Name? The Data Scientist Vs. Machine Learning Engineer Title Bore

After almost 10 years of frankly insane hype around artificial intelligence and machine learning it may feel a little strange to have the industry reorienting around a sentiment that 90% of machine learning development is just bog-standard software engineering, but here we are.-Jonathon Belotti

Who’s Behind the Numbers? A Conversation with Dr. Angela Baltes – Data Scientist, Informaticist & Senior Research Analyst

In this interview, Dr. Baltes shares how she made her way to data science as an African-American woman on the autism spectrum.-Mode Blog

startr: A Template for Data Journalism Projects in R

This project structures the data analysis process, reducing the amount of time you'll spend setting up and maintaining a project. Essentially, it's an "opinionated framework" like Django, Ruby on Rails or React, but for data journalism.-The Globe and Mail

The Easiest Way to Create an Interactive Dashboard in Python

It take just a little bit of code to turn Pandas pipelines into a dashboard using hvPlot .interactive.-Towards Data Science

Why I Quit Data Science

It’s always interesting to hear why someone left their field. This author shares their reasons for ditching machine learning in favor of software engineering.-Nirant Kasliwal

PostgreSQL Date Functions: 7 Business Analysis Examples

To separate the useful from the obscure, we're sharing how-tos for the most frequently used Postgres date functions and business scenarios where they come in handy.-Mode Blog

Using Databases with Shiny

Many analysts may be familiar with querying relational databases to retrieve data, but managing a database for use with a web application is slightly more complex. You’ll find yourself needing to define tables, secure data, and manage connections.-The Data Leader’s Survival

Why is “Data Scientist” Such a Controversial Title?

The role of a “scientist” is something that industry has yet to capitalize on, and that if we imprudently get rid of it, we’ll be missing an opportunity to foster a valuable mindset within the product development process.-The Data Leader’s Survival

How to Switch from Excel to SQL

SQL databases can handle enormous amounts of data without suffering the performance issues of Excel and have an orderly structure that protects the integrity of your data.-Mode Blog

Introduction to R

This is for the folks out there who have heard about R or want to learn, but have no idea where to start.-Jenny Sloane

Thinking About Failure in Data Analysis

The traditional notions of success and failure would seem to suggest that we should favor success over failure. But in the data analysis context, what we need to consider is how an analysis can go from success to failure and vice versa.-Simply Statistics

How to Leverage a Data Science Background as a Product Manager

PMs with a data science background are uniquely positioned to push for early investment in a proactive data culture.-Anita Mehrotra

Analyzing JSON Data With SQL

Here’s a detailed, practical example on how to restructure JSON into a tabular format.-Mode Blog

Thinking Outside the Grid - A “Bare Bones” Intro to Rtistry Concepts in R Using ggplot

This is a great intro to creative coding and generative art in R. It’s not as intimidating as you think!-The Tidy Trekker

Data from Images

This R package can help you extract data that’s trapped in images or PDFs.-Lisa DeBruine

Free Resources to Learn Python

A father asked Twitter for recommendations, so he can learn Python alongside his 14-year-old son. And boy, he got a lot of responses!-Michael McGill

Python Packages

Python packages are how you create organized, reusable, and shareable code in Python. This open source book describes modern and efficient workflows for creating those packages.-Tomas Beuzen & Tiffany Timbers

My First API: Which NFL Games Should I Watch?

This is a clever idea for figuring out which games will be the most satisfying to watch, when there are just too many games going on in a given week. Importantly, the suggestions stay spoiler-free.-Jenny Sloane

Teaching the tidyverse in 2021

Teaching R and the tidyverse soon? Here's a blog post rounding up the updates to the tidyverse over the year, with tips on how you might incorporate them in your lessons.-Tidyverse

Nine Tools I Wish I Mastered Before My PhD in Machine Learning

Whether you’re building a start up or making scientific breakthroughs, these tools will bring your machine learning pipeline to the next level.-Towards Data Science

Twelve Software Design Tips for Data Scientists

“Since many big programs begin life as small scripts, knowing how to design in the large helps ensure that what's done in the small is pointed in the right direction.”-Greg Wilson

An Old Hacker's Tips On Staying Employed

This advice from an engineer (with a career spanning over three decades) is applicable to anyone. The “Two-and-Done Rule” is particularly insightful.-The Mad Ned Memo

Exploring R² and Regression Variance With Euler/Venn Diagrams

Speaking of R²... here’s how to create diagrams for explaining shared variation in regression models using R.-Andrew Heiss

How We Use Pseudo-R² to Automate Analysis Suggestions at Heap

“[This post] shares the math behind one of my favorite model evaluation metrics, McFadden's pseudo-R², and how we've used it to build a feature that proactively guides an analysis.”-Heap Blog


This package is a one-stop-shop for computing novices (read: no coding experience, period) heading into R and the tidyverse.-Stephanie J. Spielman

Keep Your R Scripts Locally Sourced

A really bad debugging session completely broke this person’s mental model for how one bit of R code should work.-Higher Order Functions

A Survey of Mathy Jobs

What sort of “mathy” jobs there are, beyond the standard of academia and teaching?-Halfspace

Making Shiny Apps Mobile Friendly

Making Shiny apps work on mobile is actually very easy with the Bootstrap framework. You just need to work a little bit with HTML and CSS.-Jacqueline Nolis

We the Purple People

The data world needs more generalists who can navigate both the business context and the modern data stack.-dbt

Statistical Significance, p-Values, and the Reporting of Uncertainty

Statistical significance has been over-emphasized in empirical research. In many cases where decision makers are faced with deciding whether to implement a new policy or not, confidence intervals are a more useful way of communicating uncertainty of point estimates.-American Economic Association

10 Communities for Underrepresented Data Scientists

Some of these groups, which provide resources and host technical and professional meetups, are long-established with large membership numbers. Others are still emerging. Each one is worth a look.-Built In

How to Become a Better R Code Detective?

How do you go from viewing the code as a big messy ball of wool to a logical diagram that you can bend to your will? These tips will help you get better at debugging and reading R code written by someone else (or, you know, you from two years ago).-Maëlle Salmon

Tracking Impact and Measuring Success in Data Education Events

There are so many educational events for training new data scientists these days. If you’re facilitating such an event, how do you know what you’re doing worked?-Code for Science & Society Event Fund

Types of Product Usage Segmentation

Product usage segmentation is a powerful method for developing rich, actionable insights from your product usage data. Done correctly, it can unlock personalized experiences, increase user retention, and inform your product roadmap.-Mode Blog

Regression, Fire, and Dangerous Things (1/3)

Okay, so correlation does not imply causation. What now?-Elements of Evolutionary Anthropology

A Practitioner's Guide for Measuring Movements

The Sunrise Movement’s Data Director shares five potent metrics for assessing people power that anyone with a data warehouse and basic SQL skills can replicate for their own organization.-Brittany Bennett

The Case Against SQL Formatting

Our job as query writers isn’t to be mechanical scribes; it’s to format our work so that it’s easy to interpret.-benn.substack

The Humble Hash Aggregate

“If I had to pick a single programming concept where understanding it is like a superpower, it would probably be the hash map (aka in Python, the humble dictionary) because I've seen the pattern come up in almost every kind of data/programming work I've ever done.”-Vicki Boykis

One Little Thing: Reusing Code Chunks and Chunk Options with knitr

These methods make it more flexible to author and program a knitr document.-Yihui Xie

Understanding the Data (Error) Generating Processes for Data Validation

“But understanding some of the key failure modes faced by data producers can support data validation by helping consumers develop more realistic theories and expectations for the ways data may ‘break’ and how to refine strategies for detection them.”-Emily Riederer

Flat Data

If you’re already sharing and working with data in GitHub, Flat Data is for you. It makes it easy to get your datasets into GitHub repositories and version and share them.-OCTO

The Downfall of the Data Engineer

While there are many positive aspects of data engineering, there are a lot of downsides too: boredom, change management, and not having a seat at the table.-Maxime Beauchemin

A Guide to Marketplace Survival and Growth

Data leaders at Lyft, Domain, and Patreon share how they helped teams make better decisions with real-time data, leading and lagging growth indicators, and data heroes.-Mode

Lessons Learned from Building a Silly Twitter Bot

“Learning new tech skills is difficult. Therefore, you should tackle problems that bring as much joy as possible while also avoiding email entanglements or late-night Slack boondoggles.”-Brad Weiner

Hosting SQLite Databases on Github Pages

This post gets a hearty recommendation: “This is mind-blowing. If your static page needs to run some queries on a large dataset but without having to load the whole dataset with the page, you can statically host the dataset–and query it using SQLite. It uses HTTP range requests to fetch what it needs.”-phiresky

The Difference Between “Prevalence” and “Incidence” and Why We Care

You may have seen these terms in the news lately in relation to COVID-19. They’re important for helping you understand the impact of a disease on your community.-Data Literacy

What I Learned From Attending DataOps Unleashed 2021

Couldn’t make this conference? This excellent post covers talks about establishing data predictability, increasing reliability, and creating economic efficiencies in data pipelines.-James Le

Comprehensive Date-Time Handling for R

clock is a new package providing a comprehensive set of tools for working with date-times, including new date-time types built to reduce the agony of working with time zones.-Tidyverse

How to Avoid Inflated A/B Test Results

For most companies, the process for analyzing A/B tests is based on “null hypothesis significance testing.” But this process often comes up short.-Mode Blog

Time to Switch?

“A controlled randomized experiment is often seen as a gold standard in experimental research. But in many situations ethical considerations make it impossible to conduct such a ‘real’ experiment... The ‘switching-replication’ design can come to the rescue!”-Reproducible Stats in Education Sciences

What’s Missing? Reduce Bias by Addressing Data Gaps in Your Analysis Process

This series covers real world examples of how data can go missing at places like the Oregon Health Authority, Science Magazine, and Spotify—and what you can do about it.-This Is Important

The Data is in the Details

A great R tutorial for how to extract data from difficult Excel files, complete with a public repo for you to test the code on.-Gavin Masterson

Introductory Time Series Forecasting With Torch

“In this post, we build a network that uses a sequence of observations to predict a value for the very next point in time. What if we’d like to forecast a sequence of values, corresponding to, say, a week or a month of measurements?”-RStudio AI Blog

Data Science is Different

Told from the perspective of a naive junior data scientist, this story is way, way too real.-Kenny Ning

Getting More Comfortable with Git and GitHub in RStudio

A super useful tutorial (with video!) for those new to using Github with R.-Lisa Lendway

Too Big a Word

“The ethics of technology looks very different outside the tech industry than it does on the inside, and not simply because of conflicting principles or values between techies and their critics.”-Data & Society: Points

Just Where Is the Minimal Stats Bar for Data Science?

We’re not talking about production model-building roles here. If you’re looking for an entry-level position working on product development problems (which are pretty common!), you might not need to take that advanced stats class.-Counting Stuff

What the F*ck Python!

This fun project attempts to explain what exactly is happening under the hood with some counter-intuitive snippets and lesser-known features in Python.-Satwik Kansal

Sports Analytics 101: Descriptive vs. Predictive

Future performance doesn’t always resemble past performance, and that’s why we need both descriptive and prescriptive metrics.-Brendan Kent

Causal Design Patterns for Data Analysts

Everyone needs to be able to understand the difference between causality and correlation. But because the methods for doing so are scattered across disciplines like epidemiology and economics, there’s a high barrier to entry for those outside such fields. This post aims to break down those barriers.-Emily Riederer

How to Scope Down PRs

Smaller pull request are easier to test, easier to iterate, and easier to review.-Netlify

a gRadual intRoduction to Shiny

This two-hour workshop will get you up and running with the basics of Shiny. You’ll need an intermediate understanding of R.-Ted Laderas & Jessica Minnier

Foundations of Statistics with R

This free ebook uses a simulations-based approach. You’ll need to brush up on your Calculus II before you start.-Darrin Speegle & Bryan Clair

Data Science Portfolios 101

Some tips and tricks for putting together a data science portfolio to help you get hired.-R-Ladies Dallas

How to Be a Good Storyteller

One way to increase the likelihood that your analysis will positively change business actions and decisions is by improving how you communicate about your data insights.-Anson Whitmer

Where to Go Next to Level Up Your R Skills

This thread has a lot of great suggestions for R tutorials and courses to build your skillset.-Jenny Richmond

Giving More Tools to Software Engineers: the Reorganization of the Factory

There’s a lot in here that applies to data scientist productivity too.-Erik Bernhardsson

rjs: R in JavaScript

A package for inserting R code directly into websites!-Karandeep Singh

The Four Jobs of the Data Scientist

A good data scientist is required to be four different people: a scientist, statistician, systems engineer, and politician.-Simply Statistics

Save Your Hands and Save Your Time: Rethinking How to Use a Keyboard

This video tutorial gets high praise from the Lead Data Scientist at OnlineMedEd (https://twitter.com/beeonaposy/status/1329560582765342720): “If you want to learn more about setting up powerful keyboard shortcuts, this is absolutely worth 19 minutes of your time. Chock-full of practical examples.”-egghead.io

Communicating Data is About Handling Egos and Emotions

Having a bit of emotional intelligence and being prepared for scenarios where people may be openly rude and hostile goes a long way toward your analysis landing.-Evergreen Data

The Best Parts of Data Science Isn't Even the Tech

If you’re feeling like a “data lackey” that never gets to work on “sexy technical problems,” remember this: true impact is measured by the mark it leaves on the world, not the tool used to make it.-Counting Stuff

A Review of Spatial Causal Inference Methods for Environmental and Epidemiological Applications

“Spatial casual inference poses analytic challenges due to complex correlation structures and interference between the treatment at one location and the outcomes at others.”-DeepAI

I Got 7 Job Offers During the Worst Job Market in History. Here’s the Data.

This data scientist hand-tracked all his interview and application data and came away with some interesting insights you might apply to your next job search.-Jeff Li

Imposter Syndrome in Data Science

Why is imposter syndrome is so prevalent in data science? How can you deal with it personally and encourage others who also feel like imposters?-Caitlin Hudon

How Eugenics Shaped Statistics

“The various upheavals happening in statistics today—methodological and symbolic—should properly be understood as parts of a larger story, a reinvention of the discipline and a reckoning with its origins. The buildings and lectures are the monuments to eugenics we can see. The less visible ones are embedded in the language, logic, and philosophy of statistics itself.”-Nautilus

linne: Write CSS in R

Are you an R user wary of CSS? This package is a great way to get your feet wet.-John Coene

Teaching Python to Beginners

When you can teach a skill to others, you’ve mastered it. But how do you teach what you’ve forgotten?-Data for Breakfast

Why Have a Data Science Portfolio and What It Shows

Most articles on data science portfolios focus on how to build one and get a job. This post focuses on the “what” and the “why.”-Eugene Yan

Bayes Rules! An Introduction to Bayesian Modeling with R

The first five chapters of this book are available for free. Says Max Kuhn of RStudio (https://twitter.com/topepos/status/1315953559071084545): “This is one of the most clearly written books on Bayesian analysis that I’ve seen. Lots of practical advice and intuition.”-Bayes Rules!

S, R, and Data Science

R’s data analysis roots run deep. Did you know R was written to replicate a software called S, written by researchers data analysis researchers at Bell Labs?-The R Journal

Happy Git and GitHub for the useR

How to integrate Git and GitHub into your daily work with R and R Markdown.-Jenny Bryan

A Tale of Query Optimization

A query took 24 minutes to run. This post details the steps taken to optimize it to run in two seconds.-Plumbers of Data Science

Understanding Entanglement With SVD

“Entanglement” is full of meaning in physics, but the linear algebra behind it is quite simple. Ever used singular value decomposition? Then you're nearly there!-Math3ma

Data Organization in Spreadsheets

Get some practical tips for organizing spreadsheet data to reduce errors and make later analyses easier.-The American Statistician

Array Programming with NumPy

NumPy is one of the oldest Python packages around, and it still plays a central and leading role today in scientific computing across a ton of fields.-Nature

Debunking Narrative Fallacies with Empirically-Justified Explanations

Stitch Fix’s Chief Algorithms Officer Emeritus says it best (https://twitter.com/ericcolson/status/1306384818314178564?s=20): “When observing trends in metrics, beware of the narrative fallacy. We are wired to find explanation even when there is none. We make up stories to match the data.”-MultiThreaded

Pycon Africa Talks

Expand your Python knowledge! There are nearly 50 talks in this Youtube playlist to choose from.-Pycon Africa

What Can Data Scientists Learn From DevOps?

This article may be eight years old, but it still holds good advice for data scientists today: think about ways to make your analytical work easy to replicate, build upon, and scale.-RedMonk

D3 to R to D3

This is a great tutorial for R users looking to use D3. It breaks down the key differences between creating a plot in both languages.-Maya Gans

Big Book of R

This collection of over 100 R books might be the last bookmark you’ll ever need!-Oscar Baruffa

Preventing SQL Injection Attacks in Postgres

Last month’s “Meow” attack wiped out thousands of unsecured databases. These hackers used SQL injection, a technique for gaining access to business data and personal information and changing or deleting database content.-Crunchy Data

Python Typosquatting for Fun not Profit

Because packages in popular languages like Python are used as software dependencies, they can be susceptible to supply chain attacks. This analysis examines which packages are most vulnerable to typosquatting—an attack that relies on typo mistakes—to identify which packages have been compromised already and how to prevent these attacks.-William Bengtson

“Playing the Whole Game”: A Data Collection and Analysis Exercise With Google Calendar

There are many teaching resources focused on data analysis, but not data collection. This exercise tackles both and is suitable for an early introduction in an undergraduate statistics or data science course.-Taylor & Francis Online

The Top 5 Most Popular Window Functions and How to Use Them

We were curious to understand which window functions are most commonly used, so we built a window (pun intended) into our customer’s usage of these types of calculations.-Mode Blog

7 Questions You Should Ask Yourself Before Starting Any Data Science Project

Learning the technical skills is only part of becoming a data scientist. You need to think like data scientist, which means always questioning… basically everything.-Towards Data Science

Adventures in R

All you need is a basic knowledge of stats and programming to jump into this online, 8-week, college-level course.-Adventures in R

[Whitepaper] How to do Linear Regression in SQL

One of our Senior Data Scientists shares a guide for getting mileage out of doing regression analyses directly in SQL. If your measurements are clean and meaningful, if your A/B tests are well designed and powerful, you might rarely need anything more than the “basics.”-Mode

Decision-Making in a Time of Crisis

A bad outcome doesn’t mean a bad decision. This essay provides conceptual and cognitive tools for the process of making decisions under uncertainty.-O’Reilly Radar

Use Common Table Expressions (CTE) to Keep Your SQL Clean [with example]

Using common table expressions makes it easier for your teammates to debug and collaborate with you.-Mode Blog

Getting in to a Causal Flow

Most, if not all, business analytics questions, are inquiries of cause and effect. Which is why you should dive into this excellent explainer series about causal inference.-Causal Flows

Data as Protest: Data for Black Lives with Yeshi Milner

How can we claim agency over data systems to fight for racial justice? Learn more about the movement of scientists and activists who are trying to make data a tool for social change instead of a weapon of political oppression.-The Radical AI Podcast

Exploring Missing Values in naniar

“Exploring and thinking critically about missing data is an important and often overlooked part of exploratory data analysis that can help us to understand what data are missing and why, so that we choose an appropriate method for handling them.”-Allison Horst

What Can We Learn From a Country's Diplomatic Gifts?

It’s a two-for-one! Learn how to do text analysis in R and who gives the best gifts.-Alex Cookson

Data Scientists in Academia

As he transitions from a tenure track to an industry role, this data scientist shares some parting thoughts about the situation data scientists face in academia right now.-Travis Gerke

Prediction is Hard

What exactly does “cubic fit” mean?-Stats Chat

Sentiment Analysis with tidymodels and TidyTuesday Animal Crossing Reviews

If you can pull yourself away from your Animal Crossing island, this fun and straightforward tutorial is a great way to try out some text analysis techniques in R.-Julia Silge

Boosting A/B Test Power With Panel Data Models

Depending on the characteristics of your data, some basic tools from econometrics can improve your A/B tests.-Kyle Carlson

10 Tips for Making Sense of COVID-19 Models for Decision-Making

Since our lives are livelihoods are impact by the results of COVID-19 models, now’s a good time to learn what makes a model, and what they can and can’t do.-Johns Hopkins

Using Python to Cheat at Scrabble

What do you do when you get sick of losing Scrabble to your mother? Turn to Python, of course!-Ari Lamstein

Things I Wished More Developers Knew About Databases

“Even though it is impossible to ignore how databases work, the problems that application developers foresee and experience will often be just the tip of the iceberg.”-Jaana B. Dogan

When Plotting Epidemic Curves or Death Totals, Should We Divide by Population Size?

Should you use per-capita or absolute measures when plotting epidemic curves? This Twitter thread proposes that you can do either—so long as you do so properly.-Carl T. Bergstrom

Let's Talk Rice Measurements

No metric is perfect, not even something we take for granted like the meter, or a ‘cup’ of rice.-Counting Stuff

The Landscape of R Packages for Automated Exploratory Data Analysis

What R packages help automate analysis in large and noisy datasets? And what are the areas of opportunity for improving automated data exploration?-GroundAI

You Can’t Avoid Problems You Can’t See

This is good illustration of the problems that come up when you don’t truly know the ins and outs of the data itself… but you think you do.-BI Polar

Understanding Data and Statistics in the Medical Literature

If you’ve been going deep on COVID-19 research, this four-hour class will be well worth your time.-Leanpub

Keeping Data Inclusivity Without Diluting your Results

How can we be inclusive without making minority categories so small that only the majority data has statistical relevance?-We All Count

Exponential Growth and Epidemics

Time for a math refresher. Exponential growth is a common phrase in our society but it's shocking how bad our intuitions can be at recognizing what it actually means.-3Blue1Brown

Data Science Learning Resources

Another day, another nicely curated list of books and articles you should read.-Bradley Boehmke

Ten Research Challenge Areas in Data Science

These are some good discussion starters for considering what a broad research agenda for data science might look like.-Columbia University

Twitter for R Programmers

Twitter is a real-time pulse of the R community. You can learn a lot about the R language, about new approaches to problems, make friends, and even land your next job.-Twitter for R Programmers

How to Collect User Data About Gender Identity — and When Not to

Gender data can be valuable for a variety of reasons. But before you ask, consider why you’re asking, and how you frame the question.-Built In

Comparing Apples, Oranges, and Bananas

How do you know if your recommender model is doing a good job? Check out these tips for defining metrics and evaluation criteria.-Ssense Tech

The Challenge of Identifying UX Success Metrics

Start by identifying the outcome, and work from there.-Jared Spool

Data Science is Different Now

“For the past couple years, I've been telling people who ask me for advice not to go into data science. Here's why: The data science job market is way oversaturated. Here's what they should do instead.”-Vicki Boykis

The Missing Semester of Your CS Education

This course digs into a rarely-covered (but essential!) topic: using tools like the command-line, text editors, version control systems, and more.-MIT Computer Science & Artificial Intelligence Lab

The Big List of Data Science Interview Resources

Interviews are hard, but the silver lining is: they serve as a forcing function for learning.-Conor Dewey

The Rise and Fall of the OLAP Cube

If you’ve had a data analytics career over the last 30 years, you might be skeptical of the shift to columnar data warehouses. Is it just a fad, or is it here to stay?-Holistics Blog

How I Became a Data Analyst by Optimizing the Right Place and Time

Here’s what you can do to make the most of opportunities that come your way.-Towards Data Science

Falsehoods Programmers Believe About Names

“I have never seen a computer system which handles names properly and doubt one exists, anywhere.”-Kalzumeus Software

Are Your Coding Skills Good Enough for a Data Science Job?

Here are five things to check to make sure your code is... up to code.-Towards Data Science

A Cool SQL Problem: Avoiding For-Loops

This is a perfect screening or whiteboarding question for many quant finance jobs, and it’s still a great problem for many roles that have nothing to do with finance.-r x y, r

R Cookbook

A great, free resource (for new R users especially) that's full of several how-to recipes, each solving a specific problem.-R Cookbook

Getting Help In R: Do As I Say, Not As I've Done

The next time you get stuck in R, run through this list of tips. You’ll become a more self-sufficient R user because of it.-Sam Tyner

Using Docker to Deploy an R plumber API

As a data scientist, you sometimes want to have code running in places that are not your computer. The good news: setting up a virtual machine isn’t as scary as you think!-T-Mobile Product and Technology

The User-Agent — That Crazy String Underpinning a Bunch of Analytics

How did this one piece of data become so vital to pretty much all web analytics? How is it used? And what caveats does it come with?-Randy Au

Emails from R: Blastula 0.3

This new R package makes it easy for you to send coworkers emails showcasing beautiful plots (and emoji subject lines!).-R Studio Blog

Calculating New and Returning Customers in R

This step-by-step tutorial sets you up with a simple and clean calculation for new and returning customers.-Towards Data Science

A New palette() for R

R got a glow up! Here’s how to take the new color palette for a spin.-R Developer Blog

The Problem with “Biased Data”

If you asked one hundred people what “biased data” means to them, you might just get back one hundred different answers. To make progress, we need an agreed-upon language and framework for understanding bias in machine learning.-Harini Suresh

Data Science Foundations: Know Your Data. Really, Really, Know It

Really knowing your data means more than just understanding the data layout or organization. You need to go all the way down to get a look at how the data is collected and generated, too.-Towards Data Science

Data Science Archetypes

Are you a Generalist? A Detective? An Oracle? A Maker?-End-to-End Machine Learning Library

Character Encodings — The Pain That Won’t Go Away

Go deep with this series on how character encoding quirks can thwart your analyses.-Better Programming

We’ll Do It Live: Updating Machine Learning Models on Flask/uWSGI with No Downtime

It’s trickier than you may think. This tutorial with code examples will walk you through the nitty gritty.-WW Tech Blog

Questions to Ask About Your Data

Print this comic out and keep it handy for anytime you’re doing exploratory analysis.-Julia Evans

What Data Patterns Can Lie Behind a Correlation Coefficient?

To interpret a correlation coefficient, you're gonna need the corresponding scatterplot.-Jan Vanhove

List of Time Series Databases

If you’re building a product to support many large-scale time-series users, you’ll need to shop around for the right database. This list will get you started, with open-source and proprietary options.-Misframe


This new package allows R users to do things like construct a business calendar, which they can then use to shift dates forward and skip over weekends and holidays.-Davis Vaughan

How Much Have You Spent on Amazon? Analyzing Amazon Data

The Director of Data Science at HelioCampus gives this tutorial gets a hearty recommendation: “This is the kind of project I mean when I talk about project-driven learning—it has relevance to you, so there's motivation to find out the answers beyond just learning a technical skill. And plenty of variations of Qs to ask.”-Dataquest

How to Spot Red Flags in a Data Science Job Opportunity

What signs should you look for to detect work-life balance problems, a lack of data science understanding, or a wimpy manager?-Towards Data Science

Data Integrity in Survey Collection

This thread recounts how one research study was infiltrated by bots (it happens more often than you might think!) and suggests tips for ensuring better data quality in online surveys.-Melissa Simone


janitor has simple functions for Examine and clean dirty data faster and save your thinking for the fun stuff. Built with beginning and intermediate R users in mind!-Sam Firke

loadtest: an R Package for Load Testing

“As APIs become more accessible to the data science community, so should engineering best practices around those APIs. However, most load testing tools are crafted for engineers or testing specialists–so we fixed that.”-T-Mobile Tech

How Much Do Data Scientists Make?

Who knew Walmart and Ancestry.com paid so well?-Towards Data Science

Where to Learn Statistics

Pick a handful of these resources to try out, and get started!-End-to-End Machine Learning

Best Practices for Analyzing Large-scale Health Data From Wearables and Smartphone Apps

If you’re working with health data, you need to be mindful of the privacy, selection bias, and policy implications.-Nature

Teacups, Giraffes, and Statistics

Whether you’re starting from scratch or want to deepen your familiarity with statistics, this tutorial is worth checking out for the playful approach and delightful illustrations.-Teacups, Giraffes, and Statistics

Mastering Shiny

If you’ve been wanting to try out Shiny, a framework for creating web applications using R code, here’s your chance! From academia to big pharma to Silicon Valley, Shiny is now used in almost as many niches and industries as R itself.-Hadley Wickham

Reproducible Data Workflows With Drake

Learn how to use drake, an R package that provides a powerful, flexible workflow management tool for reproducible data analysis pipelines.-Garrick Aden-Buie

Pandas Tricks

New tips every weekday morning that will help you to work faster, write better code, and impress your friends!-Kevin Markham

Introducing the Funneljoin Package

Do you work with data consisting of events with their time and associated user? Often find yourself asking “first this then that” questions? You probably have a problem funneljoin can help with.-Hooked on Data

Tidylo: Tidy log odds ratio weighted by uninformative prior

Use this R package in your everyday workflow when you want to compare how the frequency of some feature differs across some set or group.-Julia Silge

Practical Psychology for Data Scientists

How to recognize and sidestep eight common cognitive biases.-Towards Data Science

Data Helpers

Check out this list of data professionals who have volunteered to answer questions, promote, or mentor newcomers in data science, engineering, and analysis.-Angela Bassa

Why You Swipe Right

Using two months of swipes from his Tinder profile, one man evaluated his dating preferences. You might feel a bit voyeuristic, but this full series is worth a read for its examination of race and online dating.-Ajay Sharma

Crushed It! Landing a Data Science Job

How to crack your first (or fourth) round of data science interviews.-Erin Shellman

Python is Weird (an Unabashedly Biased Intro to Python for R Users)

Most Pandas tutorials start with a solid assumption that you know Python and you’re completely devoted to the religious tenant of being Pythonic. This one doesn’t, and it’ll help you wrap your head around this new way of thinking.-Eric R. Scott

Instagram Data Analysis Using Panoply and Mode

A thorough walkthrough, from connecting a database through the final visualizations.-Towards Data Science

Type Stable Estimation

This paper argues that code objects in statistical software should match up with the actual mathematical objects involved in formal data modeling.-Aleatoric

Build Your Career in Data Science

While there are lots of good blog posts on individual topics, there really isn't one place people can go to get a better understanding of a data science career. Until this book!-Manning Publications

Matrices as Tensor Network Diagrams

This framework is great way to wrap your head around matrices (and it makes proofs cleaner and simpler!).-Math3ma

Lyft Data Scientist Shares Five Pieces of Career Advice

A nice quick read that covers topics like starting a new role, stakeholder management, and building a consultancy.-Towards Data Science

Find Your Slow with profvis

profvis identifies problem patches in your R code that are slowing everything down, shaving satisfying seconds off the running time of your project.-Megan Stodel

Javascript Statistics Snippets

Ever wanted to do something simple—like generate random values from a distribution—without importing a whole new library? This repo's got your back.-Nick Strayer


This Python package allows you to easily retrain OpenAI's GPT-2 text-generating model on new texts, like Buzzfeed article titles.-Max Woolf

Follow-up: I Found Two Identical Packs of Skittles, Among 468 Packs With a Total of 27,740 Skittles

Analyzing packs of Skittles (or sometimes M&Ms) seems to be a very common exercise in introductory statistics. But what's the likelihood of identifying two identical packs of Skittles? And how does that likelihood stack up against reality?-Possibly Wrong

How to Filter in R: A Detailed Introduction to the dplyr Filter Function

There are many ways to filter in R. Consider dplyr filter for its user-friendly syntax, how easy it is to work with, and how nicely it plays with the other dplyr functions.-Michael Toth

Why software projects take longer than you think – a statistical model

“How much time do you need?” has a whole new meaning now.-Erik Bernhardsson

A Simple Approach To Templated SQL Queries In Python

As Instacart's former VP of Data Science put it: “Almost every data product I’ve built has had parameterized SQL in it, and this is a great guide for how to do it well!”-Towards Data Science

Excel Error, but Could Happen in Any Tool

JD Long sums up this post perfectly: it “walks through an analysis where the results depend on how null values are handled. Good reminder to 1) understand if data has nulls 2) be thoughtful about handling nulls 3) compare groups with/without nulls.”-Junk Charts

Escaping Excel Hell with Python and Pandas

Tune into this fun discussion about introducing the Excel users in your life to Python.-TalkPython

10 things R can do that might surprise you

R is building on its solid data analysis foundations and is rapidly becoming an all-purpose connective language for data science.-Simply Statistics

Advice for New Data Scientists

While this post is intended primarily for data scientists embedded in product teams, many of the tips can be generalized to any new hire in a tech role.-Airbnb Engineering & Data Science

Using Deep Learning to “Read Your Thoughts” — With Keras and EEG

Saying a word in one’s mind, even if not spoken aloud, can result in the firing of the nerves controlling the muscles involved in speech. With some readily available equipment, you can train a model to classify these sub-vocalized words in less than a day.-Justin Alvey

Tidy Tuesday Screencast: Tidying and Analyzing US PhDs in R

If you spend a lot of time importing Excel spreadsheets, don't miss this episode: it focuses on the process of importing, cleaning, and tidying messy data.-David Robinson

Journey to Data Science

Need a dose of inspiration? This thread of folks who recently became data scientists will give you the warm fuzzies.-Twitter

SQL: One of the Most Valuable Skills

SQL is permanent. SQL is flexible. SQL can be your super power.-Craig Kerstiens

The Ultimate List of Data Science Podcasts

When they say “ultimate,” they really mean it. Fire one of these up the next time you're exercising at the gym, commuting to work, or doing chores.-Real Python

Minimally Sufficient Pandas

Limiting Pandas to a small subset can keep your focus on the actual data analysis and not on the syntax. This detailed guide offers a single approach to completing a variety of common data analysis tasks.-Dunder Data

Learning From Eight Years of Data Science Mistakes

This talk covers mistakes made during analyses (including communication when delivering results) team and infrastructure mistakes, plus some advice for incoming data scientists.-rstudio::conf 2019

Data science curriculum roadmap

This set of topic recommendations is a good starting point for data-centric academic programs looking to revise their curriculum or start a completely new one.-Brandon Rohrer

Statistics: P values are just the tip of the iceberg

Ridding science of shoddy statistics will require scrutiny of every step, not merely the last one.-Nature

Rstudio::conf 2019: lessons learned

Couldn't make Rstudio::conf? Get caught up on what you missed with this summary of five major themes from the talks there.-Brooke Watson

Solving the Model Representation Problem With broom

An introduction to the broom package, which aims to create a framework for representing statistical models, estimation methods, and fits with R objects.-Alex Hayes

Going Off the Map: Exploring purrr’s Other Functions

Learn how to use some of purrr’s lesser known functions to write cleaner and more concise code.-Hooked on Data

Preparing for a Tech Talk, Part 1: Motivation

This series covers the process preparing for a tech talk—from conceiving the idea to the actual day of the presentation. Up first: why and how to pick a topic.-Overreacted

How Do I? …

The ultimate reference material for R folks: a searchable table of 190+ R-stats tasks with code snippets.-Sharon Machlis

Selection Effects

Why do you often feel like you’re in the slower of two lanes during rush hour? Or why you feel like the bus is taking forever to get here? These scenarios (and many others!) can be explained by selection bias.-Carl T. Bergstrom

The ‘knight on an infinite chessboard’ puzzle: efficient simulation in R

A nice walkthrough of solving a chess conundrum, with an eye on keeping the simulation fast and interpretable.-Variance Explained

How to Develop the Five Soft Skills That Will Make You a Great Analyst

Soft skills tend to be more difficult to learn than hard skills, which is exactly why we all need to work on them. Here's a framework for assessing yourself and improving those skills.-Mode

Real-time Process for Completing a Task in R

“I'm sitting down to start a task in R. I don't entirely know how to complete it. I'm going to try to document my process in this thread in real time.” This thread is really enlightening (and a relief for anyone who feels like half their job is Googling).-We are R-Ladies

Level up from `cron` to Airflow with R on Your Macbook

You can use Airflow in the same way you might use cron to schedule and execute jobs. Here's how to get it up and running.-Cerebral Mastication

The Lesser Known Stars of the Tidyverse

A walkthrough of how to use some more obscure R packages and functions in exploratory analysis.-Hooked on Data

Battling the Bots

An interesting profile of a musicologist who turned his background identifying fraud in music composition into a job examining how online propaganda campaigns work.-Foreign Policy

Tidy Tuesday

Through this weekly data project, members of the RStats community get a new dataset on which to practice their wrangling and data visualization skills. Catch up on what's been done so far (https://twitter.com/hashtag/tidytuesday?src=hash) or get ready for tomorrow's dataset.-R for Data Science


Trying to wrap your head around non-standard evaluation? Check out this tutorial for tidy evaluation in R.-Ian Lyttle

Some Important Data Science Tools that aren’t Python, R, SQL or Math

Data scientists don’t exist in a vacuum. Here are some of the tools you'll need to be capable of building production-ready applications.-Towards Data Science

How Becoming Not a Data Scientist Made Me a Better Data Scientist

Working as a software engineer helped Joel Grus understand how to write better code... as a data scientist.-Joel Grus

The hacker's guide to uncertainty estimates

Estimating uncertainty is easier said than done. This post covers a whole arsenal of tricks, including confidence intervals, Monte Carlo methods, and inverse Hessians.-Erik Bernhardsson

Scipy Lecture Notes

Sebastian Raschka surfaced this well-maintained hub of knowledge with a ringing endorsement: “I think this is really an under-appreciated resource. Probably the most comprehensive guide out there, it's free, and constantly updated!”-Scipy Lecture Notes

Chromebook Data Science

These free MOOCs exist so anyone with the ability to read, write, and do basic math can get into data science using nothing but a web browser and an internet connection.-Simply Statistics

JOINs in SQL, Python, and R

Though SQL has long been the industry standard for accessing relational data, nowadays, it’s more and more common to do this same work in a scripting language like Python or R. Here's how.-Mode

Strata speaker slides & videos

Catch up on all the presentations from the Strata Data Conference in NYC last week.-O'Reilly Conferences

What Data Scientists Really Do, According to 35 Data Scientists

Here are the common themes that have emerged that have emerged from speaking with data scientists both in and outside tech.-Harvard Business Review

4 Things You Should Stop Doing in SQL and Start Doing in Python

Each language has its strengths and we’ve often pondered the distinctions, but there are some actions in SQL that are simply more efficient in Python.-Mode

What You Need to Know Before Considering a PhD

This post suggests pondering the practical experience offered by industry jobs and the disproportionately high rate of depression amongst graduate students before you apply for a PhD program in machine learning or data science.-fast.ai

Who wrote the anti-Trump New York Times op-ed? Using tidytext to find document similarity

The New York Times anonymous op-ed has spurred a bevy of data scientists to try to uncover the author using natural language processing. Here’s one attempt that serves as a nice R tutorial to boot.-Variance Explained

Get More From Your Salesforce Data: 4 SQL Queries to Write First

This post walks through a sample report replicating common Salesforce CRM reporting in SQL, so you can more easily audit, adjust, and extend that analysis.-Mode

Guidelines For A/B Testing

There are many ways A/B Testing can go wrong, but most of them won’t be obvious. Here are 12 guidelines that will help you guard against some common mistakes and set you up for success.-Hooked on Data

The Podcast of Small Differences

The first episode of this new “data science flavored” podcast covers what the two hosts—of physics and economics backgrounds—wished they knew on day one of their first data science jobs.-Otis Anderson & Ian Blumenfeld

Knowing Your Blindspot as an Analyst

“I thought that being the one with access to data made me the arbiter of truth, and that I was right by default when talking with someone who wasn’t using quantitative information to back up their ideas. I was wrong.”-Mode

Partitioning the Variation in Data

“Why do things vary?” is one of the fundamental questions you can ask during any exploratory data analysis. Here's how to gauge if the variation you're witnessing is fixed or random.-Simply Statistics

Analyzing IMDb Data The Intended Way, with R and ggplot2

IMDb has made their official dataset more accessible to analyze just for fun. Check out the data with this step-by-step tutorial, chock-full of code examples.-Max Woolf

Speed up your R Work

A tutorial on how to speed up work in R by partitioning data and process-level parallelization with rqdatatable, data.table, and dplyr.-Win-Vector Blog

Red Flags In Data Science Interviews

Companies will never straight up tell you they are bad to work for. Here are 12 warning signs to look out for when you’re interviewing at a company with multiple data scientists or analysts.-Hooked on Data

Add Constrained Optimization To Your Toolbelt

Stitch Fix shows how they use constrained optimization to get work to stylists and warehouses in a manner that’s fair and efficient, without cutting corners on client experience. For those fluent in Python: you should be able to model your own business problem by the end of this post.-Multithreaded

A year as a Data Scientist right after college: An honest review

A fresh-faced data scientist shares his experience in the workforce—what lived up to his expectations, and what didn’t.-Towards Data Science

Advice For Applying To Data Science Jobs

This the most thorough, well-organized post on the data science job application process we’ve ever seen. Bookmark it immediately.-Hooked on Data

Trustworthy Data Analysis

The manner in which you present the results of an analysis is part of the analysis and plays a large role in determining whether people trust your work or not.-Simply Statistics

Rethinking Academic Data Sharing

“There is a reasonable debate going on regarding whether companies should be able to share [personal] data and for what purposes. Academics have to realize that they are also part of this debate and that any decisions made in that domain will likely affect them.”-Simply Statistics

UTC is Enough for Everyone, Right?

Although this post is aimed at programmers, there's a lot in here for analysts as well, especially in regards to how to properly store time in databases.-Zach Holman

Seven Strategies for Optimizing Numerical Code

Some advice on how to use reporting as a means to create strong stakeholder relationships in your organization.-Locally Optimistic

7 R Data Science Influencers to Follow

Whether you’re new to the R community, or you’re already an active package-creator or analyst, listening in on R Twitter conversations is great way to stay up to speed.-Mode

Exploring The Structure and Dependencies of An R Package

pkgnet is an R library designed for the analysis of… R libraries! With a graph representation of a package and its dependencies, you can prioritize functions to unit test and examine recursive dependencies you take on by using a given package.-UptakeOpenSource

A Shiny App to Visualize and Share My Dogs’ Medical History

What’s a digital nomad and R-user to do when she needs to share her dogs’ medical records with multiple vets? Build a Shiny app, of course! Here’s how.-Jenna Allen

One Analyst’s Guide for going from Good to Great

Junior analysts, hearken! This guide is perfect for breaking through your skill plateau.-Fishtown Analytics

Lumpers and Splitters: Tensions in Taxonomies

“As data scientists tasked with segmenting clients and products, we find ourselves in the same boat with species taxonomists, straddling the line between lumping individuals into broad groups and splitting into small segments.”-MultiThreaded

5 Data Scientists on Making the Leap from Academia to Industry

We asked five leaders who transitioned from research backgrounds to data science jobs to share their thoughts on the process, from how they landed their first job to things they wished they'd known.-Mode

Set Operations in SQL and Python: a Comparison

Set operations take center stage in the latest installment of our Bridge the Gap series. Learn how to compare and combine data sets in both SQL and Python, so you can choose the best tool for the job.-Mode

Data-driven unit testing for data scientists and quant developers alike

The key to good unit testing is paying attention to the data in your tests and focus on testing the most important parts of your model or system. These guidelines will help you streamline your unit testing and avoid ambiguous results.-Cartesian Faith

SQL for Data Analyst

By the end of this free and beginner-friendly course, you’ll be able to write efficient SQL queries to successfully handle a variety of data analysis tasks.-Udacity

How to rewrite your SQL queries in Pandas, and more

A phrasebook that you'll come back to time and time again. Bookmark it!-codeburst.io

Conversations with Future Data Scientists

Ryan Swanstrom put together a YouTube playlist of his answers to questions from aspiring data scientists like “How do I transition to data science?” or “Why should I start a data science project?” Most of these videos are under the 2-minute mark.-Data Science 101

Semantics of timezone-aware datetime arithmetic

One reason why you can't "just use UTC" all the time is that you often need "wall time" semantics—the relationship between two times as displayed by the clock on the wall, regardless of the absolute elapsed duration between them. Here's how to deal with that in Python.-Paul Ganssle

Resources for Data Science Job Seekers

Here’s what you need to help you nail the job hunt and land a role you’ll love.-Mode

Bridge the Gap: Window Functions in Python and SQL

When we understand how Python and SQL overlap, we can make smarter decisions about which to use and when. Our new Bridge the Gap series explores just that, starting with a tool that most of us use everyday.-Mode

My Journey Into Data Science and Bio-Informatics — Part 1: Programming

One year ago, the author of this post had never executed a single line of code. Today, he works on a team trying to understand the underlying genetic alterations of neuroblastoma, a devastating tumor that affects young children. These are the resources and courses he used to get there.-O’Reilly Media

Data Science at the Command Line

Clear your weekend. O’Reilly has put this hands-on-guide online, for free!-O’Reilly Media

Introducing DataFramed, a Data Science Podcast

Here’s something new for your ears. This podcast promises to explore what modern data science looks like in practice via in-depth conversations with practitioners.-DataCamp

Myths and mistakes of PyCon proposals

Here are some tips for getting your proposal accepted from a bonafide member of the PyCon Program Committee.-Irina Truong

Why old-school PostgreSQL is so hip again

How did a 21-year-old piece of technology become the world’s fourth most popular database?-InfoWorld

Don’t Ignore Bears: The Pitfalls of Summarizing Data with Medians

Some folks are big fans of the median as a summary statistic. But it has some big downsides—as all statistics do.-Towards Data Science

It Came from the Data Lake

Do you really need a data lake for that project? Or can you replace Hadoop with your laptop? Check out this presentation to learn how to use Python to process larger data sets (5-10 GB) on your local machine.-Vicki Boykis

An Interactive Tutorial on Numerical Optimization

People often implement numerical optimization algorithms in machine learning projects without much thought as to how they work. This post aims to change that with interactive visual representations of each algorithm.-Ben Frederickson

Changepoint Analysis of Time Series Data

Learn how you can use the changepoint R package to identify when a video switches from one scene to the next.-Uru

Causal Inference With pandas.DataFrames

There's now a causality package in Python to make causal inference more accessible so analysts and data scientists can incorporate it into their day-to-day. The intro is worth reading, even if you're not a Python user.-Adam Kelleher

How do you convince other people to use R?

Tired of being the lone R user in your organization? Try out these arguments on your colleagues.-Simply Statistics

Python's strftime directives

This reference for changing date/time formats in Python is so handy that one Twitter user (https://twitter.com/kscottz/status/922627756914962433) said of its creator: “This person has saved the world a thousand years of human effort. This person deserves a beer.”-strftime.org

Landing a Data Science Gig in New York City

Trying to break into the NYC data science job market? Sans a PhD? This guide was tailor-made for you.-Ground Truth

R for Journalists

This site is a great launch pad for anyone who's new to R, journalist or not. Each post provides step-by-step instructions and code for making a visualization with data about a current event.-R for Journalists

R Studio Community

R Studio recently opened up a forum. It's a great place to hang out with other R users, talk with R package developers during open office hours, or ask newbie questions if you're intimidated by Stack Overflow.-R Studio

Fast GeoSpatial Analysis in Python

If you get frustrated by the sluggishness of Python's GeoSpatial stack, check out this experiment. Combining Cython, Dask, and GeoPandas sped up the mapping of 120 million geospatial data points by 30x.-Matthew Rocklin

Becoming a 10x Data Scientist

Whether or not you believe 10x developers exist, data scientists can learn a ton from seasoned developers who are considered incredibly prolific and proficient.-Algorithmia

Practical Data Science for Stats

Many aspects of day-to-day analytics work are missing from the conventional statistics literature and curriculum. This bookmark-worthy collection aims to solve that problem, with tons of preprints on modern analytical workflows.-PeerJ

Python Cheat Sheet for Data Science: Intermediate

A handy reference for Pythonistas who have been around the block a few times.-Dataquest

Buggy Python Code: The 10 Most Common Mistakes That Python Developers Make

This list ain’t for rookies. Here are some of the subtle, harder-to-catch errors that have even advanced Python users tearing their hair out.-Toptal

Giving Your First Data Science Talk

Here’s why you should consider giving a talk and how to prep. Our favorite insight: your audience is the you from six months (or one year or five years) ago. -Hooked on Data

Using optaplanner to plan water supplies

Does your job involve a lot of resource planning? Learn how to use OptaPlanner—an open-source constraint satisfaction solver—in the most Silicon Valley way possible: planning out water logistics for Burning Man.-Richard Weiss

Craft Your Python Like Poetry

The Python style guide PEP 8 specifies line length at 79 characters, but that doesn't mean you should wrap lines when they hit an arbitrary length. If you need to sharpen your poetic sensibilities, these code examples will teach you how to write readable, beautiful Python.-Trey Hunner

I have data. I need insights. Where do I start?

What to do when your boss dumps a bunch of data in your lap and says “tell me something interesting.”-Towards Data Science

You Say Data, I Say System

Every spreadsheet or database view or visualization is the result of an entire system of decisions: how to collect, compute, and represent the data. This article provides an excellent framework for being mindful of the choices that shape the end product you see on your screen.-Hacker Noon

Py 2.0

Check this out if you’ve got an iPhone and want to learn to code Python, SQL, HTML—actually, pretty much any language—on the go.-Product Hunt

29 common beginner Python errors on one page

Beginner or not, you’ll want to print out this flowchart and keep it at your desk.-Python for Biologist

How to Call B.S. on Big Data: A Practical Guide

One of our favorite tips in here: 'If you’d ask [a question] at a car dealership, you should ask it online, too.'-The New Yorker

4 steps to conducting a proper root cause analysis

Whip out this guide the next time your boss asks you a question like “Why is revenue down?”-Outlier AI

The Hitchhiker’s Guide to d3.js

Intimidated by the long list of functions in d3’s API documentation? Paralyzed by choosing from dozens of d3 tutorials? Start here.-Ian Johnson

Methodologies as Vanity Metrics

“When you work on learning new methods (Now I know Random Forest! Now I know K-L Divergence! Now I know Deep Learning!) it feels good—you’re exercising your brain, you know something you didn’t before—and it’s easy to think you’re progressing. But methods don’t in and of themselves drive value.”-Ian Blumenfeld

Profiling a Dataset of Craft Beers

Learn how to summarize a dataset with descriptive statistics using this fun Python tutorial.-Jean-Nicholas Hould

Setting up SQL for beginners is hard

SQL’s human-language-like syntax and declarative nature make it the perfect language for people with no coding experience. But getting data available in the right structure presents a major barrier to entry. Here’s how to quickly build a stack for teaching SQL to others.-Vicki Boykis

Alternatives to a Degree to Prove Yourself in Deep Learning

Why blogging might be the best way to land a job offer.-fast.ai

The Etymology of Trig Functions

Way more engaging than your high school math class.-Matthew Conlen

How to ask questions data science can solve

Asking the right questions is half the battle. This post takes a different approach to formulating questions, by mapping them to the tools of the trade.-Towards Data Science

1,000+ Women in Data Science

Your Twitter feed just got so much better.-Renee Teate

Group-by From Scratch

What’s the best way to split-apply-combine in Python? Although pandas groupby() is the widely-accepted default answer, there are situations where using built-in Python operations and NumPy and SciPy operations are more effective.-Jake VanderPlas

Taking Prophet for a Spin

Been meaning to try Prophet? Check out this walkthrough of Facebook’s Bayesian-influenced time series forecasting package (for both R and Python!).-Fast Forward Labs

How to Make the Leap from Excel to SQL

Learning SQL is easier when you have Excel in your toolbelt. And moving your analysis into SQL will seriously speed up your workflow.-Mode

Blinded by Statistical Significance

Putting too much stock in an arbitrary threshold may lead to bad decisions.-KelloggInsight Blog

Not Even Scientists Can Easily Explain P-values

We want to know if results are right, but a p-value doesn’t measure that. It can’t tell you the magnitude of an effect, the strength of the evidence or the probability that the finding was the result of chance.-FiveThirtyEight

What’s Wrong With My Time Series

When you want to test a model’s predictive power, cross validation is usually the way to go. However, since data points in a time series are dependent on each other, randomly selecting subsets for training and testing won’t do. Check out these other ways to determine error sources in time series.-MultiThreaded

Mathematicians becoming data scientists: Should you? How to?

Tips for determining if you’ll actually like the work data scientists do and positioning your mathematics background as an asset when you’re interviewing.-Quomodocumque

How to change careers and become a data scientist - one quant’s experience

One quant shares her story of switching from energy trading to data science: the resources she used, the classes she took, her decision to move to the Bay Area, and her advice for handling tech culture shock.-fast.ai

The Zero Bug

Hidden errors can be worse than visible errors. This post presents a fallacy that plagues many data analysts: common data aggregation tools usually can’t “count to zero” from examples.-Win-Vector Blog

I ranked every Intro to Data Science course on the internet, based on thousands of data points

There are a ton of data science training options online, but which one is the best?-freeCodeCamp

Unlearning descriptive statistics

If you’ve ever used an arithmetic mean, a Pearson correlation, or a standard deviation to describe a dataset, this post is for you.-Stijn Debrouwere

Guide to Encoding Categorical Values in Python

There are a ton of ways to turn categorical variables from text attributes into numerical values. Here’s how to implement the many options offered by pandas and scikit-learn on your own datasets.-Practical Business Python

Data Science for Beginners

“These videos are basic but useful, whether you’re interested in doing data science or you work with data scientists.”-Microsoft Azure

Intro to Data Science for Academics

From Reed College to Revenue at Twitter, one data scientist shares his insights on how academics can be successful in industry—by finding ways to create value in every corner of the business.-Noah Pepper

My Experience as a Freelance Data Scientist

Itching to strike out on your own? Read up on the pros and cons before you give your two weeks notice.-Greg Reda

Matching to estimate the causal effects of firing an NFL coach

To fire or not to fire? When a football team gives their coach the boot, are they better off for it? (Bonus: a nice primer on causal inference.)-StatsbyLopez

How These Three Women Made Mid-Career Pivots Into Data Science

How do we narrow the gender gap in data science? Early STEM education for girls isn’t the only solution. Here are the journeys of three women who switched from creative jobs to data roles mid-career.-Fast Company

What’s the state of the job market in data science and machine learning?

“Th[e] proliferation of courses, resources, books and startups would hint that machine learning is becoming more and more accessible to the average programmer and that the market is on track to getting saturated quickly. Is this the current trend?”-Hacker News

What library do you use for information theory in Python?

This thread is a goldmine if you’re looking to calculate entropy, mutual information, or any other information theory metric.-Randy Olson

Time Series Analysis in Python- Linear Models to GARCH

A well-written, comprehensive primer on the time series models available in Python.-BlackArbs

The Game Theory of the Yankee Swap

Want to get the best present at this year’s White Elephant gift exchange? Prep for total domination with these Python models.-Ben Casselman

How the Circle Line rogue train was caught with data

When a series of signal interferences led to massive disruptions on a Singapore subway line, a team of data scientists stepped in to solve the mystery… with Python!-Data.gov.sg

Building a Financial Model with Pandas

Expand your knowledge of Python and Pandas and analyze your mortgage payment options. Two birds, one stone.-Practical Business Python

Text Analysis and Visualization

Ever wanted to try text analysis in Python, but didn’t know where to start? Here’s your launch pad.-Irene Ros

8 Data Science Skills That Every Employee Needs

A nice primer to share with your colleagues.-Amplitude

Is Bayesian A/B Testing Immune to Peeking? Not Exactly

A common A/B testing mistake is to monitor the test and stop it when the p-value reaches a certain threshold. Many have suggested that using Bayesian methods eliminates this “peeking problem,” but all is not as it appears.-Variance Explained

Practical advice for analysis of large, complex data sets

“This document has been read more than anything else I’ve done at Google over the last eleven years. Even four years after the last major update, I find that there are multiple Googlers with the document open any time I check.”-The Unofficial Google Data Science Blog

PostgreSQL Date Functions (and 7 Ways to Use Them in Business Analysis)

PostgreSQL date functions (like DATE_TRUNC, EXTRACT, and AGE) make wrangling timestamps much easier. Here are 7 examples of applying these date functions to business scenarios.-Mode

How to Master Anti Joins and Apply Them to Business Problems

How to perform an anti join using LEFT JOIN and WHERE. Plus three examples of using anti joins in business scenarios.-Mode

What Would It Take To Turn Blue States Red?

Explore this interactive data visualization to see how small voting shifts among different demographics can impact the Presidential election.-FiveThirtyEight

Farmers Markets

Can you find real maple syrup outside of Vermont? Or seafood in the midwest? Or pet food anywhere? Check out these interactive visualizations to see what you’re most likely to find at a farmers market near you.-Susie Lu

On Average

Does the average person actually exist? Probably not, as it turns out. Learn how the concept of “average” influences product design, and why that’s not always a good thing.-99% Invisible

Goodbye, Ivory Tower. Hello, Silicon Valley Candy Store.

Some economists are trading in their professorships for tech jobs: 'Instead of thinking about national or global trends, they are studying the data trails of consumer behavior to help digital companies make smart decisions that strengthen their online marketplaces in areas like advertising, movies, music, travel and lodging.'-New York Times

Asking good questions is hard (but worth it)

Although this framework is written from a programmer’s perspective, it’s a great read for analysts and the folks who ask them questions day-in and day-out.-Julia Evans

Postgres Data Types to Redshift Data Types

Switching from one flavor of SQL to another can be a major pain. This table translates Postgres data types to their equivalent in Redshift. Definitely worth starring on Github.-Rob Story

The Three Faces of Bayes

The term “Bayesian” can refer to a variety of philosophies and ideas. Read this article before the next quant-heavy cocktail party you attend, so you’ll know what’s what.-Slackpropagation

R Psychologist

Puzzled by p-values? Confounded by confidence intervals? Stumped by significance testing? This site is a bevy of interactive visualizations illustrating tricky statistical concepts. Even if you’re a statistical genius, it’s worth a visit to play around.-Kristoffer Magnusson

70+ Resources for Transitioning to a Data Science Career

Considering a career in data science? Time to read up. Here's a list of tutorials, tips for interviewing, and stories from people who've made it.-Mode

Forget Python vs. R: how they can work together

Apparently we can all get along. The folks at Civis Analytics share the benefits of using both languages and give an example of how you can use C as a bridge to both Python and R. (Slides and a video from the original SciPy talk are also available.)-Civis Analytics

3 Reasons Counting is the Hardest Thing in Data Science

Counting isn’t technically difficult; the real challenge lies in managing relationships and office politics that surround the task.-Dayne Batten

Top 20 Pandas, NumPy, and SciPy Functions on Github

Some of the most popular Python functions, visualized in Python.-Alexander Galea

Build Algorithms Like You Give a Damn

Discussions at the 2016 WrangleConf focused on data science ethics and strategies for combatting harm by opening communication, recognizing bias, and fighting indifference.-Mode

Ethics for powerful algorithms

Contrary to a ProPublica investigation, COMPAS—a proprietary algorithm used to predict police recidivism and inform parole—isn’t statistically biased against black people. However, that doesn’t mean COMPAS isn’t deeply unfair. This is the first of four posts digging into data science ethics.-Abe Gong

Understanding Bias: A Pre-requisite For Trustworthy Results

“What causes bias? How can we correct it, and how does our picture of how the world works factor in to that?”-Adam Kelleher

A visual guide to Bayesian thinking

The best single source we’ve found for demystifying how Bayes’ Rule works, the intuition behind it, and how you can use it to inform your thinking.-Julia Galef

Thinking in SQL vs Thinking in Python

Using a new language requires a new mindset. Our chief analyst shares his learnings from adding Python to his SQL workflow.-Mode

The Theorem Every Data Scientist Should Know

Quick! Define the Central Limit Theorem. Scratching your head? You’re not alone. And yet, this theorem is key to what data scientists do every day: make statistical inferences about data.-Jean-Nicholas Hould

If Correlation Doesn’t Imply Causation, Then What Does?

This tweet sums up our feelings on this article exactly: 'Love that it gives a framework for thinking about correlations that isn’t just ¯ (ツ)_/¯'-Adam Kelleher

Building a data science portfolio

Much like writers and designers, data scientists are now expected to provide portfolios when they apply for jobs. Here’s what you need to know to get started.-Dataquest

Escaping Excel Hell with Python & Pandas

A great presentation on the problems that arise from spreadsheet analysis and how you can ditch Excel by learning some Python.-Chris Moffitt

10 Useful Python Data Visualization Libraries for Any Discipline

While many Python data visualizations libraries are narrowly focused on accomplishing a certain task, these libraries can be used regardless of your field.-Mode

Scientific Python Cheat Sheet

For those moments when you forget how to make a contour line plot in matplotlib or write a function in pure Python.-Institut de Physique du Globe de Paris

What SQL Analysts Need to Know About Python

Here's some info on the importance of Python and how to use it in day-to-day analysis.-Segment

Easier data analysis in Python with pandas

A series of video tutorials for pandas newbies who know some Python. Each video answers a student-posed question using real-world data.-Data School

PyData London Conference Presentations

A few weekends ago PyData hosted a conference in London, and they just released videos and slides of a bunch of the presentations.-PyData

Modern Pandas

This tutorial is great for experienced Python users looking to stay sharp on pandas. One Twitter user summed it up perfectly as “the abbreviated Strunk & White of data analysis.”-Tom Augspurger

Spreadsheet Thinking vs. Database Thinking

This a great read for anyone who’s new to working with relational databases.-eagereyes

SQL Joins Visualizer

Many a learner has embarked on the quest to learn SQL, only to be thwarted by the task of mastering joins. Never again. Click the type of join you want to execute and this site will generate the right code.-SQL Joins Visualizer

10+2 Data Science Methods that Every Data Scientist Should Know in 2016

Forgive the click-baity title. This is actually a really well-done roundup of the statistical and machine learning methods data scientists use daily, with Python and R scripts for each.-Takashi J. Ozaki

An Introduction to Inference

A good first step for those who work with data frequently and want to learn more about Bayesian statistical methods. From the author: 'It will be a bit mathy, but nothing beyond kahn-level probability.'-Vincent D. Warmerdam

6 Lesser Known Python Data Analysis Libraries

You’ve heard of NumPy and Pandas and matplotlib. Now check out these other handy libraries for dealing with data.-Jyotiska Khasnabish

How to Find Correlative Metrics For Conversion Optimization

A thorough walk-through of how to find correlative metrics and leverage them for conversion. It’s jam-packed with examples and advice from experts, plus a handy list of tools.-ConversionXL

This is the difference between statistics and data science

Another blog post trying to define data science? We know. We know. BUT! This one presents an interesting angle: the difference between a data scientist and a statistician comes down to product knowledge.-Mixpanel

Not So Standard Deviations: Episode 11 - Start and Stop

If you haven’t listened to NSSD yet, you’re missing out on an inside look at how data scientists work in industry and academia. In this episode, statisticians Hilary Parker and Dr. Roger Peng discuss their methods for tackling the beginning and ending parts of analyses (discussion starts at 20:43).-Not So Standard Deviations

Lift analysis - A data scientist’s secret weapon

Learn how to spot flaws in machine learning models with lift analysis (and why you should add it to your list of evaluation metrics).-Andy Goldschmidt

A Practical Guide to Anonymizing Datasets with Python & Faker

Sometimes you just want to show off an analysis or chart you built for your company… without revealing your company’s data. Now you can.-District Data Labs

Writing Data—an introduction to choosing & using data formats

JSON, CSV, or HDF5? This guide outlines the perks and pitfalls of file formats for alphanumeric data.-Build Things Together

Friction Between Programming Professionals and Beginners

In many technical forums, there’s a pattern of beginners asking a vague question and forum veterans responding with snarky or curt replies. Here are some suggestions both parties can use to keep conversations productive.-Programming for Beginners

Practical skills that practical data scientists need

Last week, Noah Lorang of Basecamp wrote that, most of the time, data scientists don’t need AI to solve business problems. They just need simple arithmetic. In this post, he elaborates on the skills he uses and questions he asks every day.-Signal v. Noise

Data scientists mostly just do arithmetic and that’s a good thing

A vast majority of the time, businesses don’t need machine learning to solve their problems. They need accurate, actionable data and people who consider context, know basic math, write SQL, and understand what makes businesses tick.-Signal v. Noise

LowClass Python—Style Guide for Data Scientists

This style guide is meant for use by advanced beginner to advanced intermediate developers of scientific code in Python. In other words, non-professional programmers...for example, data scientists.-Columbia University Applied Data Science

The Elements of Python Style

This document goes beyond PEP8 to cover the core of what I think of as great Python style. It is opinionated, but not too opinionated. It goes beyond mere issues of syntax and module layout, and into areas of paradigm, organization, and architecture.-Andrew Montalenti

The Art of Naming Things

Nothing’s worse than when you open a new dataset only to find it’s full of indecipherable labels. This two-part article provides suggestions to keep your naming convention consistent, concise, and informative while preventing data loss and a whole lot of headaches.-Penn State

A menagerie of messed up data analyses and how to avoid them

Don’t let mistakes botch your analyses. This post outlines six examples and offers advice for taking proactive measures against them.-Simply Statistics

Guess the Correlation

How good are you at gauging the correlation between two variables in a scatter plot? Find out!-Omar Wagih

Writing More Legible SQL

It’s easy to get lazy when writing SQL. Here are a few tips for cleaning up your queries so others can actually read your work.-Craig Kerstiens

AMA Data Scientist—Jake Porway of DataKind

Highlights of the discussion include advice for budding data scientists, ethical challenges, and opportunities to do good with data.-Reddit

Getting to the “Plateau of Productivity” with Python

Using the Gartner Hype Cycle as a framework, this post provides a load of context and tips for anyone who wants to pursue Python. As an added benefit, you could apply this structure to learning any technical language or tool.-Practical Business Python

The Missing 11th of the Month

According to Google’s Ngrams database, the 11th is mentioned significantly less than other monthly ordinals. But why? We don’t want to spoil the conclusion, but this post is a good reminder of why you shouldn’t blindly trust data.-Dr. David Hagen

The Field Guide to Data Science

Booz Allen just released The Second Edition of The Field Guide to Data Science, which walks you through how to use data to generate value for your organization. The guide includes practical advice, tested processes, and insights that are helpful for anyone who touches data, whether you’re a senior exec, a practioner, or a newbie.-Booz Allen Hamilton

Big Data Still Requires Humans To Make Meaningful Connections

It’s easy to get swept up in the exciting opportunities big data presents and forget that data alone isn’t a solution—it’s a tool to help solve problems. This article hits on a sentiment we’ve been hearing a lot lately—“we still need humans to help make sense of the data we are collecting.”-TechCrunch

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