From 882ac5cf5f4f1f6e747b05a60809de3109bbd5a4 Mon Sep 17 00:00:00 2001 From: Richard <75509898+Multipixels@users.noreply.github.com> Date: Thu, 16 Nov 2023 16:59:05 -0500 Subject: [PATCH] update theme --- ArcGISPro.md | 30 ++--- ArcGIS_Assistant.md | 6 - Copy_ArcGIS_Content.md | 11 +- IntermediatePython.md | 14 +-- Intro-Geospatial-Data.md | 13 +-- IntroPython.md | 4 +- Jupyter.md | 5 - Kmeans.md | 22 ++-- Machine-learning-python.md | 12 +- Matlab.md | 14 +-- README.md | 13 +-- Random-Forest.md | 22 ++-- SVM.md | 22 ++-- _config.yml | 94 ++++++++++++--- _how-to-create-a-site.md | 65 ----------- _includes/footer_custom.html | 1 - _layouts/default.html | 216 ----------------------------------- datacleaning.md | 20 ++-- ggplot2.md | 22 ++-- index.md | 37 +++--- linearregression.md | 23 ++-- logisticregression.md | 19 ++- rprog.md | 4 +- vcgit.md | 12 +- vda.md | 24 ++-- 25 files changed, 229 insertions(+), 496 deletions(-) delete mode 100644 _how-to-create-a-site.md delete mode 100644 _includes/footer_custom.html delete mode 100644 _layouts/default.html diff --git a/ArcGISPro.md b/ArcGISPro.md index c03b0be..6125572 100644 --- a/ArcGISPro.md +++ b/ArcGISPro.md @@ -4,43 +4,37 @@ title: Moving from ArcMap to ArcGIS Pro nav_order: 9 --- -## Making the Move from ArcMap to ArcGIS Pro +Workshop Title Slide -Workshop Title Slide +# Making the Move from ArcMap to ArcGIS Pro Are you an ArcGIS Desktop user who is curious about the differences between ArcMap and ArcGIS Pro? This workshop is geared towards existing ArcMap users who are interested in making the switch to ArcGIS Pro and will cover topics such as: the timeline of support for ArcMap, licensing and access, differences and similarities between the two programs, and how to import files from ArcMap and share your content.  -Presentation by Christine Homuth, Spatial Information (GIS) Specialist. +Presentation by Christine Homuth, Spatial Information (GIS) Specialist. [Get in touch with Christine.](https://library.mcmaster.ca/homuth-christine) -# Workshop preparation +## Workshop preparation Preparation for this tutorial consists of two steps: [Getting the software](#get-the-software) and [the data](#get-the-data). See below. -## Get the software +### Get the software To follow along with the tutorial, you will require access to ArcGIS Pro. Current McMaster students, staff, and faculty can request a license for ArcGIS Pro through the [ArcGIS Software Request Form](https://library.mcmaster.ca/services/gis) available on the Library's website. [Free trials](https://www.esri.com/en-us/arcgis/products/arcgis-pro/trial) of the software are also available from Esri. -## Get the data +### Get the data This tutorial uses a sample .mxd file. You can choose to [download the sample .mxd](https://github.com/scds/dash-webinars/blob/main/assets/docs/ArcMap_to_ArcGISPro_MXD.zip) or work with your own file. -# Workshop Slides +## Workshop Slides -
- -
+ -[Download as a PDF](https://github.com/scds/dash-webinars/blob/main/assets/docs/ArcMap-to-ArcGISPro-Slides.pdf) -
+[Download as PDF.](assets/docs/ArcMap-to-ArcGISPro-Slides.pdf) -# Workshop Tutorial +## Workshop Tutorial -
- -
+ -[Download as a PDF](https://github.com/scds/dash-webinars/blob/main/assets/docs/ArcMap-to-ArcGISPro-Tutorial.pdf) -
+[Download as PDF.](assets/docs/ArcMap-to-ArcGISPro-Tutorial.pdf) diff --git a/ArcGIS_Assistant.md b/ArcGIS_Assistant.md index 5677df7..1154588 100644 --- a/ArcGIS_Assistant.md +++ b/ArcGIS_Assistant.md @@ -34,9 +34,3 @@ Below are the steps involved in copying content between accounts using the ArcGI - _In some cases content is copied as a reference to the original source item; in other cases the content is migrated over to the second account_ For more information on this process and the supported item types, please refer to the [User Guide](https://guide.assistant.esri-ps.com/docs). -\ -\ -\ -Continue to the next section on using [Jupyter Notebooks](https://scds.github.io/dash-webinars/Jupyter.html) - -Return to the [tutorial home page](https://scds.github.io/dash-webinars/Copy_ArcGIS_Content.html) diff --git a/Copy_ArcGIS_Content.md b/Copy_ArcGIS_Content.md index 6d2603b..5c3d4d3 100644 --- a/Copy_ArcGIS_Content.md +++ b/Copy_ArcGIS_Content.md @@ -1,14 +1,16 @@ --- layout: default title: Copy ArcGIS Content -nav_order: 16 +nav_order: 15.5 has_children: true --- +Workshop Title Slide + # How to Copy ArcGIS Online Content Between Accounts -Workshop Title Slide ## Introduction + Current students, staff, and faculty have access to ArcGIS Online through an Educational Institution Agreement. Content created in the ArcGIS web applications will remain online following graduation but won’t be maintained or updated and are subject to availability of the application. Did you know you can copy some content from your McMaster ArcGIS Online account to a personal account? This asynchronous online tutorial will provide you with resources and tools to copy content between accounts. @@ -17,7 +19,8 @@ Online module created by Christine Homuth, Spatial Information (GIS) Specialist. For more information [contact Christine](mailto:libgis@mcmaster.ca) or [schedule a consultation](https://libcal.mcmaster.ca/appointments/gis). -## Migrating Content +## Migrating Content + The workshop outlines two of the methods available that can be used to copy your content between ArcGIS accounts. This content has been adapted from the following [Esri Canada Getting Technical](https://resources.esri.ca/getting-technical) articles: @@ -36,8 +39,6 @@ To get started: 2. Choose to *Sign In* with your ArcGIS account. 3. Choose *Save As* to save a copy of the map to your account. - - ### Continue Continue on with the workshop by exploring the options to copy content, listed below in the Table of Contents. diff --git a/IntermediatePython.md b/IntermediatePython.md index 75c2871..5911d03 100644 --- a/IntermediatePython.md +++ b/IntermediatePython.md @@ -4,27 +4,27 @@ title: Intermediate Python Programming nav_order: 8 --- -## Intermediate Python Programming +Workshop Title Slide -Workshop Title Slide +# Intermediate Python Programming Python is a powerful and easy-to-learn programming language used by many scientists. From web scraping to bioinformatics, Python is bound to have a module that could be useful to you. This workshop will include a brief review of variable types and control flow before moving on to functions, variable scope, object-oriented programming, and several of Python’s important science libraries. Presentation by Isaac Kinley, DASH Support Assistant and PhD Candidate in Psychology, Neuroscience, and Behaviour. [Book an appointment with Isaac or another member of the DASH Team.](https://library.mcmaster.ca/services/dash) -# Workshop preparation +## Workshop Preparation Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. -## Get the data +### Get the data Access the workshop file in [Notebook form](https://colab.research.google.com/drive/1IRh2fHy6pK0Yu4qUUCQ9UQ-T9qMdxu5N?usp=sharing) or in [.py and .pynb extensions](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EkSTOJueZqVGlz3uujESxMkBaC2onNUG6aJfJMRyURw4Ew?e=ZV4vRS) -## Get the software +### Get the software This hands-on workshop uses [**Python**](https://www.python.org/downloads/), a software application for data analysis. The program is free to download. ## Workshop Recording - + -View the original [here](https://echo360.ca/media/f96d9dca-8b22-4b3b-a2d4-a375540a5916/public). +[View the original here.](https://echo360.ca/media/f96d9dca-8b22-4b3b-a2d4-a375540a5916/public) diff --git a/Intro-Geospatial-Data.md b/Intro-Geospatial-Data.md index c526b21..15868cd 100644 --- a/Intro-Geospatial-Data.md +++ b/Intro-Geospatial-Data.md @@ -4,20 +4,17 @@ title: Intro to Geospatial Data nav_order: 14 --- -## Introduction to Geospatial Data +Workshop Title Slide -Workshop Title Slide +# Introduction to Geospatial Data Geospatial data is data about objects or features on or near the surface of the Earth and can be mapped using Geographic Information Systems (GIS) software. This workshop introduces participants to geospatial data formats and concepts as well as sources for this data. Presentation by Christine Homuth, Spatial Information (GIS) Specialist. [Get in touch with Christine.](https://library.mcmaster.ca/homuth-christine) -# Workshop Slides +## Workshop Slides -
- -
+ -[Download as a PDF](https://github.com/scds/dash-webinars/blob/main/assets/docs/Intro_Geospatial_Data_Slides.pdf) -
+[Download as PDF.](assets/docs/Intro_Geospatial_Data_Slides.pdf) diff --git a/IntroPython.md b/IntroPython.md index 3945ed9..0b90eac 100644 --- a/IntroPython.md +++ b/IntroPython.md @@ -4,9 +4,9 @@ title: Intro to Python Programming nav_order: 7 --- -## Introduction to Python Programming +Workshop Title Slide -Workshop Title Slide +# Introduction to Python Programming This beginner level workshop will introduce you to the basic concepts of one of the world’s most popular programming languages, Python. In this tutorial, you’ll learn how to store data using Python’s data types and variables, control the flow of a program using control structures, and create reusable code using functions. No prior knowledge of Python is required. diff --git a/Jupyter.md b/Jupyter.md index f0e0330..38ff5f7 100644 --- a/Jupyter.md +++ b/Jupyter.md @@ -93,8 +93,3 @@ cloned_items = gis_destination.content.clone_items(items=[item], copy_data=True) print("Completed!") ``` - -\ -Continue to see [Resources](https://scds.github.io/dash-webinars/ArcGIS_Python_Resources.html) on this process and working with Python in ArcGIS. - -Return to the [tutorial home page](https://scds.github.io/dash-webinars/Copy_ArcGIS_Content.html). diff --git a/Kmeans.md b/Kmeans.md index 4416cdb..6b85632 100644 --- a/Kmeans.md +++ b/Kmeans.md @@ -4,9 +4,9 @@ title: Machine Learning with R - K-Means Clustering nav_order: 2 --- -## Machine Learning with R: K-Means Clustering +Workshop Title Slide -Workshop Title Slide +# Machine Learning with R: K-Means Clustering Clustering is an unsupervised machine learning approach for finding subgroups of observations within a data set. This workshop will introduce participants to the theoretical part of the most common clustering method, K-means clustering. Afterwards, participants will gain hands-on experience in how to conduct K-means clustering in R, as well as how to interpret and visualize their results. @@ -15,29 +15,25 @@ Presentation by Shaila Jamal, DASH Support Assistant and PhD Candidate in Earth, This event is run in collaboration with the YWCA's Uplift Program, which supports women and non-binary people re-skilling to enter the tech industry. -# Workshop preparation +## Workshop Preparation Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. -## Get the data +### Get the data [Access the RMD and CSV files mentioned in the workshop.](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EvZSraT60XZFlhNtCbbEQr0Bxb0pt53qnqJ-LnrFlKEvXA?e=wGkIvS) -## Get the software +### Get the software This hands-on workshop uses [**R**](https://www.r-project.org/), a software application for data analysis. The program is free to download. ## Workshop Recording - + -View the original [here](https://echo360.ca/media/e878d90e-d572-4533-ab6c-2ce8b47ee65b/public). +[View the original here.](https://echo360.ca/media/e878d90e-d572-4533-ab6c-2ce8b47ee65b/public) ## Workshop Slides -
- -
- -[Download as a PDF](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EvZSraT60XZFlhNtCbbEQr0Bxb0pt53qnqJ-LnrFlKEvXA?e=wGkIvS) -
+ +[Download as PDF.](assets/docs/DASHWorkshop-K-means-clustering_ShailaJamal.pdf) diff --git a/Machine-learning-python.md b/Machine-learning-python.md index 2212ccf..9c361b1 100644 --- a/Machine-learning-python.md +++ b/Machine-learning-python.md @@ -4,27 +4,27 @@ title: Machine Learning with Python nav_order: 10 --- -## Machine Learning with Python +Workshop Title Slide -Workshop Title Slide +# Machine Learning with Python Machine Learning is an exciting way to get more insight out of your data. Working with Python, this workshop will cover some basic theory and algorithms for feature learning, classification, and regression. Presentation by Isaac Kinley, DASH Support Assistant and PhD Candidate in Psychology, Neuroscience, and Behaviour. [Book an appointment with Isaac or another member of the DASH Team.](https://library.mcmaster.ca/services/dash) -# Workshop preparation +## Workshop preparation Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. -## Get the data +### Get the data Access the workshop file in [Notebook form](https://colab.research.google.com/drive/1Bn9RlzIizqAuGKI5oZxjjNSWce-Z_Ujj?usp=sharing) or in [.py and .pynb extensions](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/ErRDPuXg88NMteEABkzQbHABH7vW3s0M_P2zRlF4bfIndg?e=6vZFDd) -## Get the software +### Get the software This hands-on workshop uses [**Python**](https://www.python.org/downloads/), a software application for data analysis. The program is free to download. ## Workshop Recording - + View the original [here](https://echo360.ca/media/dd02dd21-aa07-407b-8cdd-f2af0a445e0d/public). diff --git a/Matlab.md b/Matlab.md index dcea5ce..c0ce725 100644 --- a/Matlab.md +++ b/Matlab.md @@ -4,9 +4,9 @@ title: Data Visualization with MATLAB nav_order: 12 --- -## Data Visualization with MATLAB +Workshop Title Slide -Workshop Title Slide +# Data Visualization with MATLAB This asynchronous module discusses how you can create publication-quality figures using MATLAB or its free alternative, Octave. The module covers plotting options for one- and two-dimensional continuous and categorical data and explore options for customizing your figure's appearance.  @@ -14,18 +14,18 @@ Presentation by Subhanya Sivajothy (Data Analysis and Visualization Librarian). [Book an appointment with Subhanya or another member of the DASH Team.](https://library.mcmaster.ca/services/dash) -# Workshop preparation +## Workshop preparation Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. -## Get the data +### Get the data Access the data file [in .xlsx extension](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EsD3ng2kvL9OqNGogNshky4BmAGqsCRixEDZpdFhheR-VA?e=lMjuNh). -## Get the software +### Get the software This hands-on workshop uses [**MATLAB**](https://matlab.mathworks.com/), a software application for data visualization, and [**Octave**](https://octave.org/), its free alternative. ## Asynchronous Video Module - + -View the original [here](https://echo360.ca/media/577394b6-26b8-4a6a-a8b1-7ba39a358693/public). +[View the original here.](https://echo360.ca/media/577394b6-26b8-4a6a-a8b1-7ba39a358693/public) diff --git a/README.md b/README.md index a8b22f9..86ced45 100644 --- a/README.md +++ b/README.md @@ -1,14 +1,11 @@ -# DASH Webinars -Materials for DASH Workshops - -This repository contains workshop files, as well as files used to create the [workshop webpage](https://scds.github.io/dash-webinars) with GitHub Pages. +# 2022-23 DASH Webinars +Materials for the **2022-2023 DMDS Webinars**. +This repository contains workshop files, as well as files used to create the [webpage](https://scds.github.io/dash-webinars) with GitHub Pages. Contributions by the following individuals: - Workshop content created by Christine Homuth, John Fink, Vivek Jadon, Shaila Jamal, and Isaac Kinley. -- Content edited for online use by Veronica Litt +- Content edited for online use by Veronica Litt and Richie Motorgeanu - Online pages created by Veronica Litt - - -All content is made available under a GNU General Public License v3.0. +All content is made available under a [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/). diff --git a/Random-Forest.md b/Random-Forest.md index 8a764cf..65db40f 100644 --- a/Random-Forest.md +++ b/Random-Forest.md @@ -4,9 +4,9 @@ title: Machine Learning with R - Random Forest nav_order: 6 --- -## Machine Learning with R: Random Forest Classification Approach +Workshop Title Slide -Workshop Title Slide +# Machine Learning with R: Random Forest Classification Approach The Random Forest is a powerful algorithm used for classification in the industry. The classification algorithm consists of many decision trees to get more accurate predictions. This workshop will go over the theoretical part of Random Forest, then provide attendees with hands-on training on conducting Random Forest classification, training the data, testing accuracy, and working with tuning parameters.  @@ -17,29 +17,25 @@ Presentation by Shaila Jamal, DASH Support Assistant and PhD Candidate in Earth, This event is run in collaboration with the YWCA's Uplift Program, which supports women and non-binary people re-skilling to enter the tech industry. -# Workshop preparation +## Workshop Preparation Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. -## Get the data +### Get the data [Access the files mentioned in the workshop.](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EvNi6oQQJghPvvQvJU-KO2oBF1us3kkRNhZT4WlPwWU4Og?e=j3a4QD) -## Get the software +### Get the software This hands-on workshop uses [**R**](https://www.r-project.org/), a software application for data analysis. The program is free to download. ## Workshop Recording - + -View the original [here](https://echo360.ca/media/dcab4112-0199-47ce-a4cf-5453c2a82ec5/public). +[View the original here.](https://echo360.ca/media/dcab4112-0199-47ce-a4cf-5453c2a82ec5/public) ## Workshop Slides -
- -
- -[Download as a PDF](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EvNi6oQQJghPvvQvJU-KO2oBF1us3kkRNhZT4WlPwWU4Og?e=j3a4QD) -
+ +[Download as PDF.](assets/docs/RandomForestSlides.pdf) \ No newline at end of file diff --git a/SVM.md b/SVM.md index 2cba879..21e58a8 100644 --- a/SVM.md +++ b/SVM.md @@ -4,9 +4,9 @@ title: Machine Learning with R - SVM Classification nav_order: 5 --- -## Machine Learning with R: SVM Classification +Workshop Title Slide -Workshop Title Slide +# Machine Learning with R: SVM Classification Support Vector Machine (SVM) is a supervised machine learning algorithm used for both classification and regression. This workshop will only cover the theoretical and practical parts of SVM classification as SVM is mostly used in classification problems. After the introduction, participants will receive hands-on training in the implementation of SVM classification in R, as well as training and testing datasets and setting up tuning and kernal parameters. @@ -15,29 +15,27 @@ Presentation by Shaila Jamal, DASH Support Assistant and PhD Candidate in Earth, This event is run in collaboration with the YWCA's Uplift Program, which supports women and non-binary people re-skilling to enter the tech industry. -## Workshop preparation +## Workshop Preparation Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. -## Get the data +### Get the data [Access the files mentioned in the workshop.](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/Ej5XmWVfk_lFo22EYEm5W7wBYVpm4EfhAjP_zswChjEnmg?e=DyrklA) -## Get the software +### Get the software This hands-on workshop uses [**R**](https://www.r-project.org/), a software application for data analysis. The program is free to download. ## Workshop Recording - + -View the original [here](https://echo360.ca/media/127f1d5d-606d-4360-8eac-517e9ae37b65/public). +[View the original here.](https://echo360.ca/media/127f1d5d-606d-4360-8eac-517e9ae37b65/public) ## Workshop Slides -
- -
+ + +[Download as PDF.](assets/docs/SVM Slides.pdf) -[Download as a PDF](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/Ej5XmWVfk_lFo22EYEm5W7wBYVpm4EfhAjP_zswChjEnmg?e=DyrklA) -
diff --git a/_config.yml b/_config.yml index cd705ec..0736e3c 100644 --- a/_config.yml +++ b/_config.yml @@ -1,8 +1,58 @@ -title: DASH Webinars # *** Enter workshop title here -subtitle: 'The Data Analysis Support Hub' +title: 2022-23 DASH Webinars # *** Enter workshop title here +github_repo_url: "https://scds.github.io/dash-webinars/" # *** Enter workshop URL (in github pages) here +gh_edit_repository: "https://scds.github.io/dash-webinars/" # *** Enter the github URL for your repo +ga_tracking: "G-9W20BCR169" # *** This needs to be set up in Google Analytics once you know the website URL (ask Jay to do this). Then the tracking code needs to be taken from Google Analytics and pasted here. -remote_theme: scds/just-the-docs -github_repo_url: "https://scds.github.io/dmds-template/" # ***Enter workshop URL (in github pages) here +# This line appears in the footer. Use it to credit the people who created the workshop content, and those who set up the online pages. +# If you know some HTML, you can use HTML tags. +# To create a link: the text you want to show up +# Template: 'Module content created by NAME and NAME; edited for online use and online pages created by NAME.' +credits: 'Content created by the Sherman Centre; Online pages created and edited for online use by Veronica Litt and Richie Motorgeanu.' + +# DMDS Settings +# subtitle: "This workshop is part of the Do More with Digital Scholarship (DMDS) series." +# nav_footer_logo_bottom: "https://raw.githubusercontent.com/scds/jtd-mcmaster/main/assets/images/scds-logo.png" +# nav_footer_logo_bottom_href: "https://scds.ca/" +# nav_footer_logo_top: "" +# nav_footer_logo_top_href: "" + +# DASH settings +subtitle: 'This workshop is part of the Data Analysis Support Hub (DASH) series.' +nav_footer_logo_bottom: "https://raw.githubusercontent.com/scds/jtd-mcmaster/main/assets/images/scds-logo.png" +nav_footer_logo_bottom_href: "https://scds.ca/" +nav_footer_logo_top: "https://raw.githubusercontent.com/scds/jtd-mcmaster/main/assets/images/dash-logo.png" +nav_footer_logo_top_href: "https://library.mcmaster.ca/services/dash" + +# RDM settings +# subtitle: 'This workshop is part of the Research Data Management (RDM) series.' +# nav_footer_logo_bottom: "https://raw.githubusercontent.com/scds/jtd-mcmaster/main/assets/images/scds-logo.png" +# nav_footer_logo_bottom_href: "https://scds.ca/" +# nav_footer_logo_top: "https://raw.githubusercontent.com/scds/jtd-mcmaster/main/assets/images/rdm-logo.png" +# nav_footer_logo_top_href: "https://rdm.mcmaster.ca/" + +# OTHER settings - Override series specific settings +# subtitle: "This workshop is part of the __ series." +# nav_footer_logo_bottom: "https://raw.githubusercontent.com/scds/jtd-mcmaster/main/assets/images/scds-logo.png" +# nav_footer_logo_bottom_href: "https://scds.ca/" +# nav_footer_logo_top: "" +# nav_footer_logo_top_href: "" + +# _____ _ _ _ _ _ +# | ____| __| | (_) | |_ / \ | |__ ___ __ __ ___ +# | _| / _` | | | | __| / _ \ | '_ \ / _ \ \ \ / / / _ \ +# | |___ | (_| | | | | |_ / ___ \ | |_) | | (_) | \ V / | __/ +# |_____| \__,_| |_| \__| /_/ \_\ |_.__/ \___/ \_/ \___| + +aux_links: + "SCDS Workshops": + - "https://scds.ca/online-learning/" + +navigation: true + +# Override Default SCDS Web Icon +favicon_ico: "" + +remote_theme: scds/jtd-mcmaster color_scheme: mcmaster # logo: "https://github.com/scds/intro-voyant/blob/main/assets/img/dmds-tableau.png?raw=true" @@ -12,39 +62,47 @@ color_scheme: mcmaster # Supports true (default) or false heading_anchors: true - -# Footer content -# appears at the bottom of every page's main content - # Back to top link back_to_top: true back_to_top_text: "Back to top" +# Removed by Richie - Requires manual updating. Automatic updating alternative is done in footer_custom.html. # Footer last edited timestamp -last_edit_timestamp: true # show or hide edit time - page must have `last_modified_date` defined in the frontmatter -last_edit_time_format: "%b %e %Y at %I:%M %p" # uses ruby's time format: https://ruby-doc.org/stdlib-2.7.0/libdoc/time/rdoc/Time.html +# last_edit_timestamp: true # show or hide edit time - page must have `last_modified_date` defined in the frontmatter +# last_edit_time_format: "%b %e %Y at %I:%M %p" # uses ruby's time format: https://ruby-doc.org/stdlib-2.7.0/libdoc/time/rdoc/Time.html # Footer "Edit this page on GitHub" link text gh_edit_link: true # show or hide edit this page link gh_edit_link_text: "View this content on GitHub" -gh_edit_repository: "https://github.com/scds/dmds-template" #*** ENTER the github URL for your repo gh_edit_branch: "main" # the branch that your docs is served from # gh_edit_source: docs # the source that your files originate from gh_edit_view_mode: "tree" # "tree" or "edit" if you want the user to jump into the editor immediately -nav_external_links: - - title: Introduction to Python - url: https://scds.github.io/intro-python/ - - title: Introduction to R Programming - url: https://scds.github.io/intro-r/ - plugins: - jekyll-remote-theme - jekyll-seo-tag + - jekyll-relative-links # Google Analytics Tracking -ga_tracking: G-9W20BCR169 ga_tracking_anonymize_ip: true # Use GDPR compliant Google Analytics settings (true by default) license_url: "http://creativecommons.org/licenses/by/4.0/" license_name: "Creative Commons Attribution 4.0 International License" license_image_url: "https://i.creativecommons.org/l/by/4.0/88x31.png" + +# Callout titles an colors +callouts_level: quiet # or loud +callouts: + highlight: + color: yellow + important: + title: Important + color: blue + new: + title: New + color: green + note: + title: Note + color: purple + warning: + title: Warning + color: red diff --git a/_how-to-create-a-site.md b/_how-to-create-a-site.md deleted file mode 100644 index d449594..0000000 --- a/_how-to-create-a-site.md +++ /dev/null @@ -1,65 +0,0 @@ -Follow these steps to create a new workshop website from this template repository: - -## 1. Create a new repository using this template -1. Navigate to the [SCDS DMDS template repository](https://github.com/scds/dmds-template) -2. Above the file list, click **Use this template** -3. Select scds as the repository owner -4. Give the new repository a name (we try to keep it to a few words and use hyphens to delimit words--e.g. *intro-voyant*) -5. Set the repository visibility to **Public** -6. Click **Create repository from template** -- Full instructions (from GitHub) [here](https://docs.github.com/en/free-pro-team@latest/github/creating-cloning-and-archiving-repositories/creating-a-repository-from-a-template#creating-a-repository-from-a-template). - -## 2. Configure GitHub Pages -1. In the new repository, go to **Settings > GitHub Pages** -2. As **Source**, select **main** branch -3. Do not choose a theme (a theme has already been configured) -4. Click save. The URL to your new website will be displayed. It will take the form ```https://scds.githib.io/```, where ```repository_name``` is the name you created in step 4 of the previous section. - -## 3. Set up Google Analytics -1. Go to the [admin page](https://analytics.google.com/analytics/web/#/a2574088p251711101/admin) for the SCDS workshop pages -2. Click Data Streams -3. Click **Add Stream > Web** -4. Enter the GitHub Pages URL created in previous section (i.e. ```https://scds.githib.io/```). Provide a name. - -## 4. Edit the README file -1. Enter the workshop name, workshop URL, and contributor name(s) where prompted - -## 5. Add necessary documents, images, and data -```assets/docs``` -- Add any PDFs (slides, worksheets, etc.) that you will either embed or link to in the main text - -```assets/img``` -- Add any workshop-specific image(s), including the title image and any images to be shown in the main content -- Keep the logo files, as they may be useful. - -```data/``` -- Add any datasets or other files that are required for the workshop. - -## 6. Edit the config.yml file -1. Update lines with inline comments beginning with ```***```. Put text in double quotes. These include the following variables: - - **title** (workshop title) - - **github_repo_url** (GitHub Pages URL from Section 2 [example: https://scds.github.io/Version-Control-Git/]) - - **gh_edit_repository** (GitHub repository URL from Section 1 [example: https://github.com/scds/Version-Control-Git]) - - **ga_tracking** (Measurement ID from GoogleAnalytics from Section 3) -Colour schemes are dictated by the ```colour scheme``` variable. These schemes are managed [here](https://github.com/scds/just-the-docs/tree/master/_sass/color_schemes) - -## 7. Add content to workshop pages -Content is currently block-commented out with `````` at the start and end, respectively. Edit content and replace links as needed. - -```index.md``` -- Edit the link to the title image -- Edit the other content - -```preparation.md``` -- Edit content and URLs to content (like data) - -```instructions.md``` -- Add any specific instructions -- Update URLs to embedded videos, download links, workshop slides, etc. -- If you want to have pages for multiple lessons, you can replace ```instructions.md``` with multiple pages (e.g. ```lesson-1.md``` and ```lesson-2.md```, etc.). Each new page will need a unique title and the **nav_order** variable for these pages (and ```learn-more.md```, as well). - -```learn-more.md``` -- Add content - - - diff --git a/_includes/footer_custom.html b/_includes/footer_custom.html deleted file mode 100644 index b6a11ef..0000000 --- a/_includes/footer_custom.html +++ /dev/null @@ -1 +0,0 @@ -

Brought to you by the Lewis & Ruth Sherman Centre for Digital Scholarship.

\ No newline at end of file diff --git a/_layouts/default.html b/_layouts/default.html deleted file mode 100644 index c8677d8..0000000 --- a/_layouts/default.html +++ /dev/null @@ -1,216 +0,0 @@ ---- -layout: table_wrappers ---- - - - - -{% include head.html %} - - - - Link - - - - - - Search - - - - - - Menu - - - - - - Expand - - - - - - Document - - - - - - -
-
- {% include title.html %} - - - -
- - -
-
-
- {% if site.search_enabled != false %} -
-
- - -
-
-
- {% endif %} - {% include header_custom.html %} - {% if site.aux_links %} - - {% endif %} -
-
- {% unless page.url == "/" %} - {% if page.parent %} - {%- for node in pages_list -%} - {%- if node.parent == nil -%} - {%- if page.parent == node.title or page.grand_parent == node.title -%} - {%- assign first_level_url = node.url | absolute_url -%} - {%- endif -%} - {%- if node.has_children -%} - {%- assign children_list = pages_list | where: "parent", node.title -%} - {%- for child in children_list -%} - {%- if page.url == child.url or page.parent == child.title -%} - {%- assign second_level_url = child.url | absolute_url -%} - {%- endif -%} - {%- endfor -%} - {%- endif -%} - {%- endif -%} - {%- endfor -%} - - {% endif %} - {% endunless %} -
- {% if site.heading_anchors != false %} - {% include vendor/anchor_headings.html html=content beforeHeading="true" anchorBody="" anchorClass="anchor-heading" anchorAttrs="aria-labelledby=\"%html_id%\"" %} - {% else %} - {{ content }} - {% endif %} - - {% if page.has_children == true and page.has_toc != false %} -
-

Table of contents

-
    - {%- assign children_list = pages_list | where: "parent", page.title | where: "grand_parent", page.parent -%} - {% for child in children_list %} -
  • - {{ child.title }}{% if child.summary %} - {{ child.summary }}{% endif %} -
    • - {% endfor %} -
- {% endif %} - - {% capture footer_custom %} - {%- include footer_custom.html -%} - {% endcapture %} - {% if footer_custom != "" or site.last_edit_timestamp or site.gh_edit_link %} -
-
- {% if site.back_to_top %} -

{{ site.back_to_top_text }}

- {% endif %} - - {{ footer_custom }} - - {% if site.last_edit_timestamp or site.gh_edit_link %} -
- {% if site.last_edit_timestamp and site.last_edit_time_format and page.last_modified_date %} -

- Page last modified: {{ page.last_modified_date | date: site.last_edit_time_format }}. -

- {% endif %} - {% if - site.gh_edit_link and - site.gh_edit_link_text and - site.gh_edit_repository and - site.gh_edit_branch and - site.gh_edit_view_mode - %} -

- {{ site.gh_edit_link_text }} -

- {% endif %} -
- {% endif %} -
- {% endif %} - -
-
- - {% if site.search_enabled != false %} - {% if site.search.button %} - - - - {% endif %} - -
- {% endif %} -
- - diff --git a/datacleaning.md b/datacleaning.md index 7e654f0..1ff6881 100644 --- a/datacleaning.md +++ b/datacleaning.md @@ -4,9 +4,9 @@ title: Data Cleaning with Python and Pandas nav_order: 16 --- -## Cleaning Up Messy Data with Python and Pandas +Workshop Title Slide -Workshop Title Slide +# Cleaning Up Messy Data with Python and Pandas Raw data often require special preparation for efficient statistical analyses and visualization. This workshop will introduce useful Python functionality along with the pandas package to help organize your raw data and create a clean dataset. Participants will learn how to read multiple CSV files, filter and manipulate their data, and then combine them into a single dataframe according to best practices.  @@ -14,23 +14,23 @@ Presentation by Maya Flannery (DASH Support Assistant). Please note that a begin [Book an appointment with Maya or another member of the DASH Team.](https://library.mcmaster.ca/services/dash) -# Workshop preparation +## Workshop Preparation Preparation for this tutorial consists of two steps: [Getting the software](#get-the-software) and [getting the data](#get-the-data). Follow the steps below. -## Get the software +### Get the software This hands-on workshop uses [**Python**](https://www.python.org/downloads/), a software application for data analysis. The program is free to download. The workshop also uses Jupyter Notebooks via [**Anaconda**](https://www.anaconda.com/). These programs are also free to download. -## Get the data +### Get the data Access the [**experiment files**](https://mcmasteru365-my.sharepoint.com/:u:/g/personal/littvs_mcmaster_ca/EbEdBfmCfmJKi-K1iHFm0kUBPR8Te_5yeQ7czQWq2XxHlA?e=2FuXDc) used in this workshop. Access the [**Jupyter Notebook**](https://raw.githubusercontent.com/scds/dash-webinars/main/workshop-pandas.ipynb) used in this workshop. -## Event Recording +## Workshop Recording - + -View the original [here](https://echo360.ca/media/a6890e05-3c38-4371-aafa-5b8328699704/public). +[View the original here.](https://echo360.ca/media/a6890e05-3c38-4371-aafa-5b8328699704/public) -## Additional Resources +## Links and Resources -[Intro to Pandas](https://pandas.pydata.org/pandas-docs/stable/getting_started/index.html#intro-to-pandas) +- [Intro to Pandas](https://pandas.pydata.org/pandas-docs/stable/getting_started/index.html#intro-to-pandas) diff --git a/ggplot2.md b/ggplot2.md index 5f6a34b..85e2165 100644 --- a/ggplot2.md +++ b/ggplot2.md @@ -4,9 +4,9 @@ title: Data Visualization in R using ggplot2 nav_order: 13 --- -## Data Visualization in R using ggplot2 +Workshop Title Slide -Workshop Title Slide +# Data Visualization in R using ggplot2 This virtual workshop provide an introduction to ggplot2, an open-source data visualization package for the statistical programming language R. This workshop will go overbasic tips for creating visualizations and customizing the design of those graphs. A basic familiarity with R will be helpful for this workshop. @@ -14,23 +14,21 @@ Presentation by Subhanya Sivajothy (Data Analysis and Visualization Librarian). [Book an appointment with Subhanya or another member of the DASH Team.](https://library.mcmaster.ca/services/dash) -# Workshop preparation +## Workshop preparation Preparation for this tutorial consists of one step: [Getting the software](#get-the-software). Follow the steps below. -## Get the software +### Get the software This hands-on workshop uses [**R**](https://posit.co/download/rstudio-desktop/). ## Workshop Recording - + -View the original [here](https://echo360.ca/media/755f87f0-4515-416d-b32f-608a17ec8f26/public). +[View the original here.](https://echo360.ca/media/755f87f0-4515-416d-b32f-608a17ec8f26/public) -## Additional Resources +## Links and Resources -[ggplot2 Cheat Sheet](https://github.com/rstudio/cheatsheets/blob/main/data-visualization.pdf) | - -[Information on Colour](http://sape.inf.usi.ch/quick-reference/ggplot2/colour) | - -[Data Visualization Guide](https://datavizcatalogue.com/) | +- [ggplot2 Cheat Sheet](https://github.com/rstudio/cheatsheets/blob/main/data-visualization.pdf) +- [Information on Colour](http://sape.inf.usi.ch/quick-reference/ggplot2/colour) +- [Data Visualization Guide](https://datavizcatalogue.com/) diff --git a/index.md b/index.md index ec5f9d3..35f7f06 100644 --- a/index.md +++ b/index.md @@ -5,6 +5,12 @@ description: DASH Webinars nav_order: 1 --- +{%- assign workshops = site.pages + | where_exp: "item", "item.grand_parent == null" + | where_exp: "item", "item.parent == null" + | sort: "title" +-%} + Workshop Title Slide # Welcome to DASH: The Data Analysis Support Hub Webinars @@ -14,24 +20,19 @@ DASH workshops help registrants with data analysis and visualization by providin DASH workshops welcome students, staff, and faculty from any discipline, as well as the public at large. A number of DASH workshops are also geared towards beginners, so even if you’re new to data analysis, we encourage you to sign up and learn! ## 2022-2023 DASH Workshop Topics -This year's programming includes events on the following topics: -- Machine Learning with R: K-Means Clustering -- Machine Learning with R: Linear Regression -- Intro to Python Programming -- Intermediate Python Programming -- Machine Learning with R: Logistic Regression -- Making the Move from ArcMap to ArcGIS Pro -- Machine Learning with R: Support Vector Machine Classification -- Intro to Machine Learning with Python -- Intro to R Programming -- Data Visualization with MATLAB -- Machine Learning with R: Random Forest Classification -- Data Visualization in R using ggplot2 -- Visual Data Analysis with Microsoft Excel -- Intro to Geospatial Data -- Intro to LaTeX -- How to Copy ArcGIS Online Content Between Accounts -- Version Control with Git + +
+ + Workshops + +
    +{% for workshop in workshops %} +{% if workshop.title != null and workshop.title != "Home" and workshop.title != "Learn More" %} +
  • {{workshop.title}}
    • +{% endif %} +{% endfor %} +
+
## Collaborations and Co-Sponsored Events DASH collaborates with the Do More with Digital Scholarship and Research Data Management workshop series on certain events. Access recordings of [DMDS events](https://scds.github.io/dmds-22-23/Intro.html) and [RDM Webinars](https://scds.github.io/intro-rdm/). diff --git a/linearregression.md b/linearregression.md index 0b33286..0c80b55 100644 --- a/linearregression.md +++ b/linearregression.md @@ -4,9 +4,9 @@ title: Machine Learning with R - Linear Regression nav_order: 3 --- -## Machine Learning with R: Linear Regression +Workshop Title Slide -Workshop Title Slide +# Machine Learning with R: Linear Regression This workshop will cover an introduction to linear regression with single and multiple predictor variables, followed by hands-on training on conducting linear regression in R, model training, testing accuracy, and how to interpret and visualize results. @@ -15,30 +15,25 @@ Presentation by Shaila Jamal, DASH Support Assistant and PhD Candidate in Earth, This event is run in collaboration with the YWCA's Uplift Program, which supports women and non-binary people re-skilling to enter the tech industry. -# Workshop preparation +## Workshop preparation Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. -## Get the data +### Get the data [Access all the files mentioned in the workshop.](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EkUm2pZxDgpNs6-QOG_M5ZUBuIFCHlOM0DEQyTuwqu0wRg?e=Ghg5bD) -## Get the software +### Get the software This hands-on workshop uses [**R**](https://www.r-project.org/), a software application for data analysis. The program is free to download. ## Workshop Recording - + -View the original [here](https://echo360.ca/media/89dd7672-a26e-49df-93b7-b0d3c6249116/public). +[View the original here.](https://echo360.ca/media/89dd7672-a26e-49df-93b7-b0d3c6249116/public) ## Workshop Slides -
- -
- -[Download as a PDF](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EvZSraT60XZFlhNtCbbEQr0Bxb0pt53qnqJ-LnrFlKEvXA?e=wGkIvS) -
- + +[Download as PDF.](assets/docs/LRSlides.pdf) diff --git a/logisticregression.md b/logisticregression.md index 2492f79..558c5c0 100644 --- a/logisticregression.md +++ b/logisticregression.md @@ -4,9 +4,9 @@ title: Machine Learning with R - Logistic Regression nav_order: 4 --- -## Machine Learning with R: Logistic Regression +Workshop Title Slide -Workshop Title Slide +# Machine Learning with R: Logistic Regression Logistic regression in R programming is a classification algorithm used to find the probably of event success and event failure. This workshop will cover an introduction to logistic regression, followed by hands-on training in how to conduct a logistic regression in R, model training, testing accuracy, and how to interpret and visualize results. @@ -15,28 +15,25 @@ Presentation by Shaila Jamal, DASH Support Assistant and PhD Candidate in Earth, This event is run in collaboration with the YWCA's Uplift Program, which supports women and non-binary people re-skilling to enter the tech industry. -# Workshop preparation +## Workshop preparation Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. -## Get the data +### Get the data [Access the files mentioned in this workshop.](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/El_xfO9xn4ZDv4qGsQl9LCUBWxF09Om5wAFZGk05Kzybeg?e=9COMzx) -## Get the software +### Get the software This hands-on workshop uses [**R**](https://www.r-project.org/), a software application for data analysis. The program is free to download. ## Workshop Recording - + View the original [here](https://echo360.ca/media/73af7636-e49a-4eb0-a6cb-98ecbec0d9a8/public). ## Workshop Slides -
- -
+ -[Download as a PDF](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/El_xfO9xn4ZDv4qGsQl9LCUBWxF09Om5wAFZGk05Kzybeg?e=9COMzx) -
+[Download as PDF.](assets/docs/LogisticSlides.pdf) diff --git a/rprog.md b/rprog.md index 1ca7138..910bebb 100644 --- a/rprog.md +++ b/rprog.md @@ -4,9 +4,9 @@ title: Intro to R Programming nav_order: 11 --- -## Introduction to R Programming +Workshop Title Slide -Workshop Title Slide +# Introduction to R Programming R has a powerful suite of high-level statistical functions, but sometimes you need lower-level control over the functionality of your script. No prior knowledge of R is required. In this workshop, you will learn how to write programs in R using functions and control flow. We will cover variables, data types, functions, conditional blocks, loops, and debugging. diff --git a/vcgit.md b/vcgit.md index 002765a..0fb7014 100644 --- a/vcgit.md +++ b/vcgit.md @@ -4,24 +4,24 @@ title: Version Control with Git nav_order: 17 --- -## Version Control with Git +Workshop Title Slide -Workshop Title Slide +# Version Control with Git Come learn about git! Git is a version control system widely used in software engineering, academia, and anywhere where projects need reliable and granular versioning -- especially when the projects need to scale to thousands of contributors. You'll learn the basics of working with git repositories, how to pull new repositories from sites like Github, and more. Presentation by John Fink, Digital Scholarship Librarian. [Book an appointment with John or another member of the SCDS Team.](https://libcal.mcmaster.ca/appointments/) -# Workshop preparation +## Workshop Preparation Preparation for this tutorial consists of one step: [Getting the software](#get-the-software). Follow the step below. -## Get the software +### Get the software This hands-on workshop uses [**Git**](https://git-scm.com/downloads), a free program that allows version control. ## Workshop Recording - + -View the original [here](https://echo360.ca/media/920779d4-4319-49f1-9b3a-d5c9ebb33723/public). +[View the original here.](https://echo360.ca/media/920779d4-4319-49f1-9b3a-d5c9ebb33723/public) diff --git a/vda.md b/vda.md index c5838ba..3fc11f9 100644 --- a/vda.md +++ b/vda.md @@ -4,40 +4,38 @@ title: Visual Data Analysis with MS Excel nav_order: 15 --- -## Visual Data Analysis with Microsoft Excel +Workshop Title Slide -Workshop Title Slide +# Visual Data Analysis with Microsoft Excel Data visualization is the graphical representation of information and data. This workshop will cover topics such as applications of data analysis basics for visualizations; effective designs of basic charts such as pie charts, bar charts, and scatterplots; time series analysis and visualization; and more advanced analytical displays like bar-in-bar, slope charts, dot plots, and bullet charts.  A basic working knowledge of MS Excel is required for this workshop.  -Presentation by Shaila Jamal, DASH Support Assistant and PhD Candidate in Earth, Environment, and Society. +Presentation by Shaila Jamal, DASH Support Assistant and PhD Candidate in Earth, Environment, and Society. [Book an appointment with Shaila or another member of the DASH Team.](https://library.mcmaster.ca/services/dash) -# Workshop preparation +## Workshop Preparation Preparation for this tutorial consists of two steps: [Getting the data](#get-the-data) and [Getting the software](#get-the-software). Follow the steps below. -## Get the data +### Get the data [Access the files mentioned in the workshop.](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EvEe64azH5dPvcGVazH-VSIBxllXvnHPp3ELy6knsHTZlQ?e=3OmIaU) -## Get the software +### Get the software This hands-on workshop uses [**Excel**](https://www.microsoft.com/en-us/microsoft-365/free-office-online-for-the-web), a software application for data analysis. The program is included with McMaster tuition and a free version is linked in the previous sentence. ## Workshop Recording - + -View the original [here](https://echo360.ca/media/66d0e84b-3056-4a9c-ad6f-3a98ef784979/public). +[View the original here.](https://echo360.ca/media/66d0e84b-3056-4a9c-ad6f-3a98ef784979/public) ## Workshop Slides -
- -
+ + +[Download as PDF.](assets/docs/VDASlides.pdf) -[Download as a PDF](https://mcmasteru365-my.sharepoint.com/:f:/g/personal/littvs_mcmaster_ca/EvEe64azH5dPvcGVazH-VSIBxllXvnHPp3ELy6knsHTZlQ?e=3OmIaU) -