From 2925dd53a2677b44882f01621a1d54d0defa8a6a Mon Sep 17 00:00:00 2001 From: Cody Hennesy Date: Fri, 7 Jun 2024 09:53:41 -0500 Subject: [PATCH 01/12] Create 2024-06-15-lc-python-update.md Blog on updated lc python lesson --- _posts/2024/06/2024-06-15-lc-python-update.md | 40 +++++++++++++++++++ 1 file changed, 40 insertions(+) create mode 100644 _posts/2024/06/2024-06-15-lc-python-update.md diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md new file mode 100644 index 000000000..ef4603af8 --- /dev/null +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -0,0 +1,40 @@ +--- +layout: page +authors: ["Cody Hennesy", "Tim Dennis", "Scott Peterson", "David Palmquist"] +teaser: "Introducing Python Intro for Libraries, an updated lesson designed to introduce Python and reproducible workflows for library data analysis." +title: "Library Carpentry Curriculum Advisory Committee Approves a Major Update to the LC Python Lesson" +date: 2024-06-15 +time: "09:00:00" +tags: ["Curriculum", "Library Carpentry", "Python", "Maintainers"] +--- + +### Introduction +We are excited to announce that the Library Carpentry Curriculum Advisory Committee (LC-CAC) has approved a major update to the [Python Intro for Libraries lesson](https://librarycarpentry.org/lc-python-intro/). + +The lesson demonstrates how to use Python to clean, analyze, and visualise library usage data, providing an introduction to reproducible workflows in Python for library and information workers. While the lesson repurposes some elements from the previous Library Carpentry Introduction to Python, it is a major overhaul that includes a new library-specific dataset, the use of JupyterLab instead of Spyder, and new episodes that use Pandas to tidy a dataset and Plotly to visualise data. + +### What is covered in this lesson? +The updated lesson includes twelve substantive episodes that cover Python fundamentals such as variables, types, lists, functions, for loops, and conditionals. The lesson demonstrates how to import CSV files representing annual usage data from the Chicago Public Library system into Pandas, and focuses on wrangling, analyzing, and visualizing this quantitative dataset. Packages that are introduced include glob, Pandas, and Plotly. Along with Python fundamentals, learners will use Pandas to: +- Import and export CSV files +- Manipulate, clean, and analyze data +- Create tidy datasets +- Generate figures and interactive plots + +### Why a course on Python? +Python is a widely used language for data science tasks and is commonly leveraged for metadata and cataloging, collection analysis, assessment, and other related tasks in libraries. Python can be used for web scraping, collecting data via Application Programming Interfaces (APIs), and to clean and organize data and metadata. As a popular tool in data science, computational social sciences, and digital humanities, Python is also a great toolkit for working with researchers across multiple disciplines. + +### Course Development +The current Library Carpentry Python course has been developed, taught, and adapted by many past and present members of the Carpentries communities. The previous iteration of the lesson was adapted from the Software Carpentry [Plotting & Programming in Python lesson](https://swcarpentry.github.io/python-novice-gapminder/), and was developed and maintained by Konrad Foerstner, Drew Heles, Elizabeth Wickes, Laura Wrubel, Carlos Martinez and Richard Vankoningsveld. The current iteration was created by Cody Hennesy, Tim Dennis, Scott Peterson, and David Palmquist. +The lesson was revised based on strong demand for a Library Carpentry Python lesson, and the desire for the lesson to use a dataset that was directly related to library work. While the structure of the previous lesson was generally followed, the content was almost completely rewritten. Newer concepts and tools such as f-strings, JupyterLab, Tidy Data, and Plotly are now introduced, while less time is devoted to some core Python concepts. The current maintainers plan to develop Python web scraping and APIs lessons in the future that will include more coverage of Python fundamentals at the point of need. + +### Why was this lesson adopted by the curriculum advisors? +The LC-CAC approved the updated lesson based on its improved relevance to library and information workers, and the integration of more contemporary development practices and platforms. The maintainers have collected and integrated learner and instructor feedback from several pilot lessons, with plans to continue teaching the lesson in a number of in-person and online contexts. + +### What you can do +We invite Carpentries instructors to teach the new lesson and provide feedback via the [repository Issues page](https://github.com/LibraryCarpentry/lc-python-intro/issues) or [by reaching out to the maintainers](https://github.com/LibraryCarpentry/lc-python-intro/blob/main/CONTRIBUTING.md). Our goal is to move the lesson from [beta to stable](https://carpentries.github.io/lesson-development-training/19-operations.html#the-lesson-life-cycle) over the next year. If you are interested in contributing to the lesson in an ongoing way, we welcome new maintainers: reach out to the current maintainers via the links above to discuss possibilities. If you have other ideas about building future Python lessons for Library Carpentry, and what modules should be included, please [contact the LC-CAC](https://github.com/LibraryCarpentry/curriculum-advisors?tab=readme-ov-file#how-to-contact-the-curriculum-advisory-committee). + +### Course author biographies +- Cody Hennesy is the Computational Research Librarian at the University of Minnesota, Twin Cities, where he supports researchers with reproducible and methodologically sound practices to collect and analyze library and open digital collections. He is a member of the LC-CAC. +- Tim Dennis, the Director of the Data Science Center at UCLA Library, specializes in helping researchers and students apply computational and data methods. His work focuses on increasing access, supporting activism-minded research, and transforming data services through inclusive pedagogy and expanded familiarity with open source software. +- Scott Peterson is in the Arts & Humanities Division of the UC Berkeley Library where he is the Head of the Morrison and Graduate Services libraries. He is a member of the UC Carpentries Group and hosts monthly Carpentries Workshop Debrief and Teaching Discussion sessions. +- David Palmquist is Systems Analyst with the Pollak Library at Cal State University, Fullerton. Carpentries instructor, maintainer, and member of the CSU Carpentries Collective which strives to expand Carpentries workshop opportunities delivered by CSU faculty and staff. From 9e2c6824a95db5909f3990b391258dea1e1cc62b Mon Sep 17 00:00:00 2001 From: Tim Dennis Date: Wed, 26 Jun 2024 10:26:07 -0700 Subject: [PATCH 02/12] Update _posts/2024/06/2024-06-15-lc-python-update.md Co-authored-by: Oscar Masinyana <132367843+OscarSiba@users.noreply.github.com> --- _posts/2024/06/2024-06-15-lc-python-update.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md index ef4603af8..eb94a994b 100644 --- a/_posts/2024/06/2024-06-15-lc-python-update.md +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -3,7 +3,7 @@ layout: page authors: ["Cody Hennesy", "Tim Dennis", "Scott Peterson", "David Palmquist"] teaser: "Introducing Python Intro for Libraries, an updated lesson designed to introduce Python and reproducible workflows for library data analysis." title: "Library Carpentry Curriculum Advisory Committee Approves a Major Update to the LC Python Lesson" -date: 2024-06-15 +date: 2024-06-26 time: "09:00:00" tags: ["Curriculum", "Library Carpentry", "Python", "Maintainers"] --- From 0aadf9fd5d9ea3399d33492d4e7eba72175564ee Mon Sep 17 00:00:00 2001 From: Tim Dennis Date: Wed, 26 Jun 2024 10:26:36 -0700 Subject: [PATCH 03/12] Update _posts/2024/06/2024-06-15-lc-python-update.md Co-authored-by: Oscar Masinyana <132367843+OscarSiba@users.noreply.github.com> --- _posts/2024/06/2024-06-15-lc-python-update.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md index eb94a994b..4988ea7d4 100644 --- a/_posts/2024/06/2024-06-15-lc-python-update.md +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -11,7 +11,7 @@ tags: ["Curriculum", "Library Carpentry", "Python", "Maintainers"] ### Introduction We are excited to announce that the Library Carpentry Curriculum Advisory Committee (LC-CAC) has approved a major update to the [Python Intro for Libraries lesson](https://librarycarpentry.org/lc-python-intro/). -The lesson demonstrates how to use Python to clean, analyze, and visualise library usage data, providing an introduction to reproducible workflows in Python for library and information workers. While the lesson repurposes some elements from the previous Library Carpentry Introduction to Python, it is a major overhaul that includes a new library-specific dataset, the use of JupyterLab instead of Spyder, and new episodes that use Pandas to tidy a dataset and Plotly to visualise data. +The lesson demonstrates how to use Python to clean, analyse, and visualise library usage data, providing an introduction to reproducible workflows in Python for library and information workers. While the lesson repurposes some elements from the previous Library Carpentry Introduction to Python, it is a major overhaul that includes a new library-specific dataset, the use of JupyterLab instead of Spyder, and new episodes that use Pandas to tidy a dataset and Plotly to visualise data. ### What is covered in this lesson? The updated lesson includes twelve substantive episodes that cover Python fundamentals such as variables, types, lists, functions, for loops, and conditionals. The lesson demonstrates how to import CSV files representing annual usage data from the Chicago Public Library system into Pandas, and focuses on wrangling, analyzing, and visualizing this quantitative dataset. Packages that are introduced include glob, Pandas, and Plotly. Along with Python fundamentals, learners will use Pandas to: From f97f48219b7d2e0db3873e386bb25d3053902e80 Mon Sep 17 00:00:00 2001 From: Tim Dennis Date: Wed, 26 Jun 2024 10:26:50 -0700 Subject: [PATCH 04/12] Update _posts/2024/06/2024-06-15-lc-python-update.md Co-authored-by: Oscar Masinyana <132367843+OscarSiba@users.noreply.github.com> --- _posts/2024/06/2024-06-15-lc-python-update.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md index 4988ea7d4..30d37d953 100644 --- a/_posts/2024/06/2024-06-15-lc-python-update.md +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -14,7 +14,7 @@ We are excited to announce that the Library Carpentry Curriculum Advisory Commit The lesson demonstrates how to use Python to clean, analyse, and visualise library usage data, providing an introduction to reproducible workflows in Python for library and information workers. While the lesson repurposes some elements from the previous Library Carpentry Introduction to Python, it is a major overhaul that includes a new library-specific dataset, the use of JupyterLab instead of Spyder, and new episodes that use Pandas to tidy a dataset and Plotly to visualise data. ### What is covered in this lesson? -The updated lesson includes twelve substantive episodes that cover Python fundamentals such as variables, types, lists, functions, for loops, and conditionals. The lesson demonstrates how to import CSV files representing annual usage data from the Chicago Public Library system into Pandas, and focuses on wrangling, analyzing, and visualizing this quantitative dataset. Packages that are introduced include glob, Pandas, and Plotly. Along with Python fundamentals, learners will use Pandas to: +The updated lesson includes twelve substantive episodes that cover Python fundamentals such as variables, types, lists, functions, for loops, and conditionals. The lesson demonstrates how to import CSV files representing annual usage data from the Chicago Public Library system into Pandas, and focuses on wrangling, analysing, and visualising this quantitative dataset. Packages that are introduced include glob, Pandas, and Plotly. Along with Python fundamentals, learners will use Pandas to: - Import and export CSV files - Manipulate, clean, and analyze data - Create tidy datasets From ecf2863dd37e8a25af8cbcd2e55b9811231329de Mon Sep 17 00:00:00 2001 From: Tim Dennis Date: Wed, 26 Jun 2024 10:26:58 -0700 Subject: [PATCH 05/12] Update _posts/2024/06/2024-06-15-lc-python-update.md Co-authored-by: Oscar Masinyana <132367843+OscarSiba@users.noreply.github.com> --- _posts/2024/06/2024-06-15-lc-python-update.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md index 30d37d953..d8468fb4a 100644 --- a/_posts/2024/06/2024-06-15-lc-python-update.md +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -21,7 +21,7 @@ The updated lesson includes twelve substantive episodes that cover Python fundam - Generate figures and interactive plots ### Why a course on Python? -Python is a widely used language for data science tasks and is commonly leveraged for metadata and cataloging, collection analysis, assessment, and other related tasks in libraries. Python can be used for web scraping, collecting data via Application Programming Interfaces (APIs), and to clean and organize data and metadata. As a popular tool in data science, computational social sciences, and digital humanities, Python is also a great toolkit for working with researchers across multiple disciplines. +Python is a widely used language for data science tasks and is commonly leveraged for metadata and cataloguing, collection analysis, assessment, and other related tasks in libraries. Python can be used for web scraping, collecting data via Application Programming Interfaces (APIs), and to clean and organise data and metadata. As a popular tool in data science, computational social sciences, and digital humanities, Python is also a great toolkit for working with researchers across multiple disciplines. ### Course Development The current Library Carpentry Python course has been developed, taught, and adapted by many past and present members of the Carpentries communities. The previous iteration of the lesson was adapted from the Software Carpentry [Plotting & Programming in Python lesson](https://swcarpentry.github.io/python-novice-gapminder/), and was developed and maintained by Konrad Foerstner, Drew Heles, Elizabeth Wickes, Laura Wrubel, Carlos Martinez and Richard Vankoningsveld. The current iteration was created by Cody Hennesy, Tim Dennis, Scott Peterson, and David Palmquist. From 59ba3c04ac98ee8bf1bc94221eb1de7de4d99bc9 Mon Sep 17 00:00:00 2001 From: Tim Dennis Date: Wed, 26 Jun 2024 10:27:06 -0700 Subject: [PATCH 06/12] Update _posts/2024/06/2024-06-15-lc-python-update.md Co-authored-by: Oscar Masinyana <132367843+OscarSiba@users.noreply.github.com> --- _posts/2024/06/2024-06-15-lc-python-update.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md index d8468fb4a..0bbe88592 100644 --- a/_posts/2024/06/2024-06-15-lc-python-update.md +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -16,7 +16,7 @@ The lesson demonstrates how to use Python to clean, analyse, and visualise libra ### What is covered in this lesson? The updated lesson includes twelve substantive episodes that cover Python fundamentals such as variables, types, lists, functions, for loops, and conditionals. The lesson demonstrates how to import CSV files representing annual usage data from the Chicago Public Library system into Pandas, and focuses on wrangling, analysing, and visualising this quantitative dataset. Packages that are introduced include glob, Pandas, and Plotly. Along with Python fundamentals, learners will use Pandas to: - Import and export CSV files -- Manipulate, clean, and analyze data +- Manipulate, clean, and analyse data - Create tidy datasets - Generate figures and interactive plots From 110d8c3106ea47d5f93e8c05af174155bac40631 Mon Sep 17 00:00:00 2001 From: Tim Dennis Date: Wed, 26 Jun 2024 10:27:31 -0700 Subject: [PATCH 07/12] Update _posts/2024/06/2024-06-15-lc-python-update.md Co-authored-by: Oscar Masinyana <132367843+OscarSiba@users.noreply.github.com> --- _posts/2024/06/2024-06-15-lc-python-update.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md index 0bbe88592..1e955179c 100644 --- a/_posts/2024/06/2024-06-15-lc-python-update.md +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -24,7 +24,7 @@ The updated lesson includes twelve substantive episodes that cover Python fundam Python is a widely used language for data science tasks and is commonly leveraged for metadata and cataloguing, collection analysis, assessment, and other related tasks in libraries. Python can be used for web scraping, collecting data via Application Programming Interfaces (APIs), and to clean and organise data and metadata. As a popular tool in data science, computational social sciences, and digital humanities, Python is also a great toolkit for working with researchers across multiple disciplines. ### Course Development -The current Library Carpentry Python course has been developed, taught, and adapted by many past and present members of the Carpentries communities. The previous iteration of the lesson was adapted from the Software Carpentry [Plotting & Programming in Python lesson](https://swcarpentry.github.io/python-novice-gapminder/), and was developed and maintained by Konrad Foerstner, Drew Heles, Elizabeth Wickes, Laura Wrubel, Carlos Martinez and Richard Vankoningsveld. The current iteration was created by Cody Hennesy, Tim Dennis, Scott Peterson, and David Palmquist. +The current Library Carpentry Python course has been developed, taught, and adapted by many past and present members of The Carpentries communities. The previous iteration of the lesson was adapted from the Software Carpentry [Plotting & Programming in Python lesson](https://swcarpentry.github.io/python-novice-gapminder/), and was developed and maintained by Konrad Förstner, Drew Heles, Elizabeth Wickes, Laura Wrubel, Carlos Martinez and Richard Vankoningsveld. The current iteration was created by Cody Hennesy, Tim Dennis, Scott Peterson, and David Palmquist. The lesson was revised based on strong demand for a Library Carpentry Python lesson, and the desire for the lesson to use a dataset that was directly related to library work. While the structure of the previous lesson was generally followed, the content was almost completely rewritten. Newer concepts and tools such as f-strings, JupyterLab, Tidy Data, and Plotly are now introduced, while less time is devoted to some core Python concepts. The current maintainers plan to develop Python web scraping and APIs lessons in the future that will include more coverage of Python fundamentals at the point of need. ### Why was this lesson adopted by the curriculum advisors? From 646dec7efcf31d7228befc8addf2f51ac140f281 Mon Sep 17 00:00:00 2001 From: Tim Dennis Date: Wed, 26 Jun 2024 14:03:43 -0700 Subject: [PATCH 08/12] Update _posts/2024/06/2024-06-15-lc-python-update.md Co-authored-by: Oscar Masinyana <132367843+OscarSiba@users.noreply.github.com> --- _posts/2024/06/2024-06-15-lc-python-update.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md index 1e955179c..35fd98c7b 100644 --- a/_posts/2024/06/2024-06-15-lc-python-update.md +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -28,7 +28,7 @@ The current Library Carpentry Python course has been developed, taught, and adap The lesson was revised based on strong demand for a Library Carpentry Python lesson, and the desire for the lesson to use a dataset that was directly related to library work. While the structure of the previous lesson was generally followed, the content was almost completely rewritten. Newer concepts and tools such as f-strings, JupyterLab, Tidy Data, and Plotly are now introduced, while less time is devoted to some core Python concepts. The current maintainers plan to develop Python web scraping and APIs lessons in the future that will include more coverage of Python fundamentals at the point of need. ### Why was this lesson adopted by the curriculum advisors? -The LC-CAC approved the updated lesson based on its improved relevance to library and information workers, and the integration of more contemporary development practices and platforms. The maintainers have collected and integrated learner and instructor feedback from several pilot lessons, with plans to continue teaching the lesson in a number of in-person and online contexts. +The LC-CAC approved the updated lesson based on its improved relevance to library and information workers, and the integration of more contemporary development practices and platforms. The Maintainers have collected and integrated learner and Instructor feedback from several pilot lessons, with plans to continue teaching the lesson in a number of in-person and online contexts. ### What you can do We invite Carpentries instructors to teach the new lesson and provide feedback via the [repository Issues page](https://github.com/LibraryCarpentry/lc-python-intro/issues) or [by reaching out to the maintainers](https://github.com/LibraryCarpentry/lc-python-intro/blob/main/CONTRIBUTING.md). Our goal is to move the lesson from [beta to stable](https://carpentries.github.io/lesson-development-training/19-operations.html#the-lesson-life-cycle) over the next year. If you are interested in contributing to the lesson in an ongoing way, we welcome new maintainers: reach out to the current maintainers via the links above to discuss possibilities. If you have other ideas about building future Python lessons for Library Carpentry, and what modules should be included, please [contact the LC-CAC](https://github.com/LibraryCarpentry/curriculum-advisors?tab=readme-ov-file#how-to-contact-the-curriculum-advisory-committee). From 18585f893c78fcfaf808cd520eef844077f9a839 Mon Sep 17 00:00:00 2001 From: Tim Dennis Date: Wed, 26 Jun 2024 14:04:03 -0700 Subject: [PATCH 09/12] Update _posts/2024/06/2024-06-15-lc-python-update.md Co-authored-by: Oscar Masinyana <132367843+OscarSiba@users.noreply.github.com> --- _posts/2024/06/2024-06-15-lc-python-update.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md index 35fd98c7b..29d2dfa50 100644 --- a/_posts/2024/06/2024-06-15-lc-python-update.md +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -31,7 +31,7 @@ The lesson was revised based on strong demand for a Library Carpentry Python les The LC-CAC approved the updated lesson based on its improved relevance to library and information workers, and the integration of more contemporary development practices and platforms. The Maintainers have collected and integrated learner and Instructor feedback from several pilot lessons, with plans to continue teaching the lesson in a number of in-person and online contexts. ### What you can do -We invite Carpentries instructors to teach the new lesson and provide feedback via the [repository Issues page](https://github.com/LibraryCarpentry/lc-python-intro/issues) or [by reaching out to the maintainers](https://github.com/LibraryCarpentry/lc-python-intro/blob/main/CONTRIBUTING.md). Our goal is to move the lesson from [beta to stable](https://carpentries.github.io/lesson-development-training/19-operations.html#the-lesson-life-cycle) over the next year. If you are interested in contributing to the lesson in an ongoing way, we welcome new maintainers: reach out to the current maintainers via the links above to discuss possibilities. If you have other ideas about building future Python lessons for Library Carpentry, and what modules should be included, please [contact the LC-CAC](https://github.com/LibraryCarpentry/curriculum-advisors?tab=readme-ov-file#how-to-contact-the-curriculum-advisory-committee). +We invite Carpentries Instructors to teach the new lesson and provide feedback via the [repository Issues page](https://github.com/LibraryCarpentry/lc-python-intro/issues) or [by reaching out to the Maintainers](https://github.com/LibraryCarpentry/lc-python-intro/blob/main/CONTRIBUTING.md). Our goal is to move the lesson from [beta to stable](https://carpentries.github.io/lesson-development-training/19-operations.html#the-lesson-life-cycle) over the next year. If you are interested in contributing to the lesson in an ongoing way, we welcome new Maintainers: reach out to the current Maintainers via the links above to discuss possibilities. If you have other ideas about building future Python lessons for Library Carpentry, and what modules should be included, please [contact the LC-CAC](https://github.com/LibraryCarpentry/curriculum-advisors?tab=readme-ov-file#how-to-contact-the-curriculum-advisory-committee). ### Course author biographies - Cody Hennesy is the Computational Research Librarian at the University of Minnesota, Twin Cities, where he supports researchers with reproducible and methodologically sound practices to collect and analyze library and open digital collections. He is a member of the LC-CAC. From 8288eec91e8ada825134acea4d6298aea42ac797 Mon Sep 17 00:00:00 2001 From: Tim Dennis Date: Wed, 26 Jun 2024 14:04:14 -0700 Subject: [PATCH 10/12] Update _posts/2024/06/2024-06-15-lc-python-update.md Co-authored-by: Oscar Masinyana <132367843+OscarSiba@users.noreply.github.com> --- _posts/2024/06/2024-06-15-lc-python-update.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md index 29d2dfa50..72e7dbbcd 100644 --- a/_posts/2024/06/2024-06-15-lc-python-update.md +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -34,7 +34,7 @@ The LC-CAC approved the updated lesson based on its improved relevance to librar We invite Carpentries Instructors to teach the new lesson and provide feedback via the [repository Issues page](https://github.com/LibraryCarpentry/lc-python-intro/issues) or [by reaching out to the Maintainers](https://github.com/LibraryCarpentry/lc-python-intro/blob/main/CONTRIBUTING.md). Our goal is to move the lesson from [beta to stable](https://carpentries.github.io/lesson-development-training/19-operations.html#the-lesson-life-cycle) over the next year. If you are interested in contributing to the lesson in an ongoing way, we welcome new Maintainers: reach out to the current Maintainers via the links above to discuss possibilities. If you have other ideas about building future Python lessons for Library Carpentry, and what modules should be included, please [contact the LC-CAC](https://github.com/LibraryCarpentry/curriculum-advisors?tab=readme-ov-file#how-to-contact-the-curriculum-advisory-committee). ### Course author biographies -- Cody Hennesy is the Computational Research Librarian at the University of Minnesota, Twin Cities, where he supports researchers with reproducible and methodologically sound practices to collect and analyze library and open digital collections. He is a member of the LC-CAC. +- Cody Hennesy is the Computational Research Librarian at the University of Minnesota, Twin Cities, where he supports researchers with reproducible and methodologically sound practices to collect and analyse library and open digital collections. He is a member of the LC-CAC. - Tim Dennis, the Director of the Data Science Center at UCLA Library, specializes in helping researchers and students apply computational and data methods. His work focuses on increasing access, supporting activism-minded research, and transforming data services through inclusive pedagogy and expanded familiarity with open source software. - Scott Peterson is in the Arts & Humanities Division of the UC Berkeley Library where he is the Head of the Morrison and Graduate Services libraries. He is a member of the UC Carpentries Group and hosts monthly Carpentries Workshop Debrief and Teaching Discussion sessions. - David Palmquist is Systems Analyst with the Pollak Library at Cal State University, Fullerton. Carpentries instructor, maintainer, and member of the CSU Carpentries Collective which strives to expand Carpentries workshop opportunities delivered by CSU faculty and staff. From 5b338d73455092d53fce0b95414e9ef2d1034f6c Mon Sep 17 00:00:00 2001 From: Tim Dennis Date: Wed, 26 Jun 2024 14:04:26 -0700 Subject: [PATCH 11/12] Update _posts/2024/06/2024-06-15-lc-python-update.md Co-authored-by: Oscar Masinyana <132367843+OscarSiba@users.noreply.github.com> --- _posts/2024/06/2024-06-15-lc-python-update.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md index 72e7dbbcd..8c844daf3 100644 --- a/_posts/2024/06/2024-06-15-lc-python-update.md +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -35,6 +35,6 @@ We invite Carpentries Instructors to teach the new lesson and provide feedback v ### Course author biographies - Cody Hennesy is the Computational Research Librarian at the University of Minnesota, Twin Cities, where he supports researchers with reproducible and methodologically sound practices to collect and analyse library and open digital collections. He is a member of the LC-CAC. -- Tim Dennis, the Director of the Data Science Center at UCLA Library, specializes in helping researchers and students apply computational and data methods. His work focuses on increasing access, supporting activism-minded research, and transforming data services through inclusive pedagogy and expanded familiarity with open source software. +- Tim Dennis, the Director of the Data Science Center at UCLA Library, specialises in helping researchers and students apply computational and data methods. His work focuses on increasing access, supporting activism-minded research, and transforming data services through inclusive pedagogy and expanded familiarity with open source software. - Scott Peterson is in the Arts & Humanities Division of the UC Berkeley Library where he is the Head of the Morrison and Graduate Services libraries. He is a member of the UC Carpentries Group and hosts monthly Carpentries Workshop Debrief and Teaching Discussion sessions. - David Palmquist is Systems Analyst with the Pollak Library at Cal State University, Fullerton. Carpentries instructor, maintainer, and member of the CSU Carpentries Collective which strives to expand Carpentries workshop opportunities delivered by CSU faculty and staff. From b9971affb48d72a6cdd16aef547a6e7ef90e8592 Mon Sep 17 00:00:00 2001 From: Tim Dennis Date: Wed, 26 Jun 2024 14:04:38 -0700 Subject: [PATCH 12/12] Update _posts/2024/06/2024-06-15-lc-python-update.md Co-authored-by: Oscar Masinyana <132367843+OscarSiba@users.noreply.github.com> --- _posts/2024/06/2024-06-15-lc-python-update.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_posts/2024/06/2024-06-15-lc-python-update.md b/_posts/2024/06/2024-06-15-lc-python-update.md index 8c844daf3..edc84eb97 100644 --- a/_posts/2024/06/2024-06-15-lc-python-update.md +++ b/_posts/2024/06/2024-06-15-lc-python-update.md @@ -37,4 +37,4 @@ We invite Carpentries Instructors to teach the new lesson and provide feedback v - Cody Hennesy is the Computational Research Librarian at the University of Minnesota, Twin Cities, where he supports researchers with reproducible and methodologically sound practices to collect and analyse library and open digital collections. He is a member of the LC-CAC. - Tim Dennis, the Director of the Data Science Center at UCLA Library, specialises in helping researchers and students apply computational and data methods. His work focuses on increasing access, supporting activism-minded research, and transforming data services through inclusive pedagogy and expanded familiarity with open source software. - Scott Peterson is in the Arts & Humanities Division of the UC Berkeley Library where he is the Head of the Morrison and Graduate Services libraries. He is a member of the UC Carpentries Group and hosts monthly Carpentries Workshop Debrief and Teaching Discussion sessions. -- David Palmquist is Systems Analyst with the Pollak Library at Cal State University, Fullerton. Carpentries instructor, maintainer, and member of the CSU Carpentries Collective which strives to expand Carpentries workshop opportunities delivered by CSU faculty and staff. +- David Palmquist is Systems Analyst with the Pollak Library at Cal State University, Fullerton. He is a Carpentries Instructor, Maintainer, and member of the CSU Carpentries Collective which strives to expand Carpentries workshop opportunities delivered by CSU faculty and staff.