From 81772b01779a42b9dd1826d44c7fa93944c8912f Mon Sep 17 00:00:00 2001 From: mine-cetinkaya-rundel Date: Tue, 6 Feb 2024 22:05:54 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20posit-co?= =?UTF-8?q?nf-2024/workshops@1761717e1e882df718824bc16aa0e9a5ea579a25=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- index.html | 52 +++++++++++++++++++++---------------------- search.json | 2 +- workshops/tables.html | 4 ++-- 3 files changed, 29 insertions(+), 29 deletions(-) diff --git a/index.html b/index.html index cc94e85..2268cde 100644 --- a/index.html +++ b/index.html @@ -219,7 +219,7 @@

Workshops

- + Advanced Shiny for Python @@ -230,7 +230,7 @@

Workshops

Take your Shiny apps to the next level with modules - + Advanced Tidymodels @@ -241,7 +241,7 @@

Workshops

An advanced class to learn how to use tidymodels to optimize different models, conduct feature engineering, and other activities. - + Advanced to Shiny for R @@ -252,7 +252,7 @@

Workshops

1-sentence summary of workshop. - + Big Data in R with Arrow @@ -263,7 +263,7 @@

Workshops

An introduction to Apache Arrow for creating efficient analysis pipelines with larger-than-memory data in R. - + Build-a-Dashboard Workshop (with Quarto, R and/or Python) @@ -274,7 +274,7 @@

Workshops

Create sleek, elegant, and eye-catching dashboards with static and/or interactive elements with Quarto. For R and Python users. - + Causal Inference in R @@ -285,7 +285,7 @@

Workshops

Learn to answer causal questions with causal diagrams, propensity score modeling, and more. - + Data Science Workflows with Posit Tools — Python Focus @@ -296,7 +296,7 @@

Workshops

Build an opinionated and Pythonic data science workflow using Posit’s professional products and open-source tools. - + Data Science Workflows with Posit Tools — R Focus @@ -307,7 +307,7 @@

Workshops

Use open source packages and Posit’s professional tools — Workbench, Connect, and Package Manager — to improve your end-to-end data science workflows. - + Databases (Details TBD) @@ -318,7 +318,7 @@

Workshops

1-sentence summary of workshop. - + Dataviz (Details TBD) @@ -329,7 +329,7 @@

Workshops

1-sentence summary of workshop. - + DevOps for Data Scientists @@ -340,7 +340,7 @@

Workshops

This workshop is intended for data scientists who wish to learn more about the basic principles and tools of DevOps and to get hands-on experience putting DevOps workflows into production. - + From R User to R Programmer @@ -351,7 +351,7 @@

Workshops

Improve your R programming skills and reduce the amount of duplication in your code. - + Intro to MLOps with vetiver @@ -362,7 +362,7 @@

Workshops

Utilize the vetiver framework in Python and R for efficient versioning, deployment, and monitoring of machine learning models in production. - + Introduction to Data Science with Python @@ -373,7 +373,7 @@

Workshops

Learn the foundations of Python for data science through a cohort-based, mentor-led, hands-on apprenticeship for working professionals. - + Introduction to Data Science with R and Tidyverse @@ -384,7 +384,7 @@

Workshops

Learn the foundations of R for data science through a cohort-based, mentor-led, hands-on apprenticeship for working professionals. - + Introduction to Quarto @@ -395,7 +395,7 @@

Workshops

Author a rich array of documents in Quarto. - + Introduction to Shiny for Python @@ -406,7 +406,7 @@

Workshops

Learn the basic building blocks of Shiny for Python, including the new Shiny Express syntax. - + Introduction to Shiny for R @@ -417,7 +417,7 @@

Workshops

Introduction to builing interactive web apps using Shiny and R - + Introduction to tidymodels @@ -428,7 +428,7 @@

Workshops

Machine learning with tabular data using the tidymodels framework. - + ML Python (Details TBD) @@ -439,7 +439,7 @@

Workshops

1-sentence summary of workshop. - + Making Tables with gt and Great Tables @@ -450,7 +450,7 @@

Workshops

Create publication-quality tables with gt and Great Tables. For R and Python users. - + Package Development: The Rest of the Owl @@ -461,7 +461,7 @@

Workshops

Learn what’s different about writing R code that lives in a package (vs. a script). - + Quarto Websites @@ -472,7 +472,7 @@

Workshops

Build a website from scratch with Quarto. - + R in Production @@ -483,7 +483,7 @@

Workshops

Learn how to write robust R code that both works reliably in production, and when it fails, is easy to debug. - + Using Databricks with R @@ -494,7 +494,7 @@

Workshops

Overview of the latests methods to connect, and interact with Databricks services. - + What They Forgot To Teach You About R diff --git a/search.json b/search.json index 101c132..8abcdca 100644 --- a/search.json +++ b/search.json @@ -4,7 +4,7 @@ "href": "workshops/tables.html", "title": "Making Tables with gt and Great Tables", "section": "", - "text": "Description\nThe gt package for R and the Great Tables package for Python both deal with an important element of written communication: tables. We don’t believe tables have to be drab or dull. Rather, we think that tables have the power to inspire and to excite!\nIn this workshop, you’ll learn about how to make tables that can accurately convey information yet look aesthetically pleasing. We will handle the first stumbling block: what do we even call the different parts of a table? After getting the table terminology down we’ll learn how to effectively assemble the table components and create powerful displays of information. We will start simply and progressively, working toward more complex table designs. Since there are two packages (one in R, one in Python) we will take a blended approach and learn about table generation in bilingual fashion.\nWe’ll cover the following:\n\nCreate table components and put them together (e.g., header, footer, stub, etc.)\nFormat cell values (numeric/scientific, date/datetime, etc.)\nRearranging columns and handling column value alignments\nStyling the table, either through data values or on a more granular level\nAdding icons, plots, images, and incorporating your own HTML\nmore!\n\n\n\nAudience\nThis course is for you if you:\n\nhave some basic working knowledge of either R or Python (separate sets of materials will be available for both R and Python),\nhave data you often need to present as data summaries\nwould like to level-up your ability to generate tables for publication\n\n\n\nInstructor(s)\n\n\n\n\n\n\n\n\n\n\nRichard Iannone(he/him) is a software engineer at Posit, PBC. He mainly works on open-source packages; here is a short list of packages that he is focused on: gt, Great Tables, and blastula.\n\n\n\n\nHuman memory, statistics, and computing." + "text": "Description\nThe gt package for R and the Great Tables package for Python both deal with an important element of written communication: tables. We don’t believe tables have to be drab or dull. Rather, we think that tables have the power to inspire and to excite!\nIn this workshop, you’ll learn about how to make tables that can accurately convey information yet look aesthetically pleasing. We will handle the first stumbling block: what do we even call the different parts of a table? After getting the table terminology down we’ll learn how to effectively assemble the table components and create powerful displays of information. We will start simply and progressively, working toward more complex table designs. Since there are two packages (one in R, one in Python) we will take a blended approach and learn about table generation in bilingual fashion.\nWe’ll cover the following:\n\nCreate table components and put them together (e.g., header, footer, stub, etc.)\nFormat cell values (numeric/scientific, date/datetime, etc.)\nRearranging columns and handling column value alignments\nStyling the table, either through data values or on a more granular level\nAdding icons, plots, images, and incorporating your own HTML\nmore!\n\n\n\nAudience\nThis course is for you if you:\n\nhave some basic working knowledge of either R or Python (separate sets of materials will be available for both R and Python),\nhave data you often need to present as data summaries\nwould like to level-up your ability to generate tables for publication\n\n\n\nInstructor(s)\n\n\n\n\n\n\n\n\n\n\nRichard Iannone (he/him) is a software engineer at Posit, PBC. He mainly works on open-source packages; here is a short list of packages that he is focused on: gt, Great Tables, and blastula.\n\n\n\n\nMichael Chow. Human memory, statistics, and computing." }, { "objectID": "workshops/wtf.html", diff --git a/workshops/tables.html b/workshops/tables.html index 8dfb33c..4562b60 100644 --- a/workshops/tables.html +++ b/workshops/tables.html @@ -196,12 +196,12 @@

Instructor(s)

-Richard Iannone(he/him) is a software engineer at Posit, PBC. He mainly works on open-source packages; here is a short list of packages that he is focused on: gt, Great Tables, and blastula. +Richard Iannone (he/him) is a software engineer at Posit, PBC. He mainly works on open-source packages; here is a short list of packages that he is focused on: gt, Great Tables, and blastula. -Human memory, statistics, and computing. +Michael Chow. Human memory, statistics, and computing.