Merge pull request #28 from stefmolin/updates

Updates for 2024

Author: stefmolin

.github/workflows/env-checks.yml

@@ -1,6 +1,6 @@
 # This workflow builds the workshop environment on Mac, Linux, and Windows for
 # multiple versions of Python to confirm it can be properly installed.
-# 
+#
 # Author: Stefanie Molin
 
 name: Env Build
@@ -33,7 +33,7 @@ jobs:
 
     # The type of runner that the job will run on
     runs-on: ${{ matrix.os }}
-    
+
     defaults:
       run:
         shell: bash -el {0}
@@ -42,13 +42,13 @@ jobs:
         fail-fast: false
         matrix:
             os: [macos-latest, ubuntu-latest, windows-latest]
-            python-version: ["3.8", "3.9", "3.10"]
+            python-version: ["3.9", "3.10", "3.11", "3.12"]
 
     # Steps represent a sequence of tasks that will be executed as part of the job
     steps:
       # checks-out your repository under $GITHUB_WORKSPACE, so your job can access it
-      - uses: actions/checkout@v3
-      
+      - uses: actions/checkout@v4
+
       # remove the Python version from the file for testing
       - name: strip hardcoded Python version from environment for testing
         run: |
@@ -59,12 +59,13 @@ jobs:
           fi;
 
       # create the conda env
-      - uses: conda-incubator/setup-miniconda@v2
+      - uses: conda-incubator/setup-miniconda@v3
         with:
           python-version: ${{ matrix.python-version }}
           auto-update-conda: true
           miniforge-variant: Mambaforge
-          use-mamba: true
+          mamba-version: "*"
+          channels: conda-forge
           channel-priority: true
           activate-environment: data_viz_workshop
           environment-file: environment.yml

README.md

@@ -13,7 +13,7 @@ While there are many plotting libraries to choose from, the prolific Matplotlib
 
 ## Workshop Outline
 
-This is a workshop on data visualization in Python first delivered at [ODSC West 2021](https://odsc.com/speakers/introduction-to-data-visualization-in-python/) and subsequently at [ODSC East 2022](https://odsc.com/speakers/introduction-to-data-visualization-in-python/), [PyCon Italia 2022](https://pycon.it/en/talk/beyond-the-basics-data-visualization-in-python?day=2022-06-03), [ODSC Europe 2022](https://odsc.com/speakers/introduction-to-data-visualization-in-python/), [EuroPython 2022](https://ep2022.europython.eu/session/beyond-the-basics-data-visualization-in-python), [ODSC West 2022](https://odsc.com/speakers/introduction-to-data-visualization-in-python/), the Toronto Machine Learning Summit (TMLS) 2022, [PyCon US 2023](https://us.pycon.org/2023/schedule/presentation/17/), [ODSC East 2023](https://odsc.com/speakers/introduction-to-data-visualization-in-python/), [PyCon Italia 2023](https://pycon.it/en/event/beyond-the-basics-data-visualization-in-python-2), and [PyCon Portugal 2023](https://pretalx.evolutio.pt/pycon-pt-2023/talk/STX8K3/). It's divided into the following sections:
+This is a workshop on data visualization in Python first delivered at [ODSC West 2021](https://odsc.com/speakers/introduction-to-data-visualization-in-python/) and subsequently at [ODSC East 2022](https://odsc.com/speakers/introduction-to-data-visualization-in-python/), [PyCon Italia 2022](https://pycon.it/en/talk/beyond-the-basics-data-visualization-in-python?day=2022-06-03), [ODSC Europe 2022](https://odsc.com/speakers/introduction-to-data-visualization-in-python/), [EuroPython 2022](https://ep2022.europython.eu/session/beyond-the-basics-data-visualization-in-python), [ODSC West 2022](https://odsc.com/speakers/introduction-to-data-visualization-in-python/), the Toronto Machine Learning Summit (TMLS) 2022, [PyCon US 2023](https://us.pycon.org/2023/schedule/presentation/17/), [ODSC East 2023](https://odsc.com/speakers/introduction-to-data-visualization-in-python/), [PyCon Italia 2023](https://pycon.it/en/event/beyond-the-basics-data-visualization-in-python-2), [PyCon Portugal 2023](https://pretalx.evolutio.pt/pycon-pt-2023/talk/STX8K3/), and PyCon Colombia 2024. It's divided into the following sections:
 
 ### Section 1: Getting Started With Matplotlib
 We will begin by familiarizing ourselves with Matplotlib. Moving beyond the default options, we will explore how to customize various aspects of our visualizations. By the end of this section, you will be able to generate plots using the Matplotlib API directly, as well as customize the plots that libraries like pandas and Seaborn create for you.
@@ -39,7 +39,10 @@ You can work through the notebooks locally or in your browser. Pick the installa
 ### Local Installation
 **Warning**: It is highly recommended that you use your personal laptop for the installation.
 
-0. Install [Anaconda](https://docs.anaconda.com/anaconda/install/)/[Miniconda](https://docs.conda.io/en/latest/miniconda.html) or [Mambaforge](https://mamba.readthedocs.io/en/latest/installation.html#fresh-install), if not already installed.
+0. Install the following, if not already installed:
+    - [Anaconda](https://docs.anaconda.com/anaconda/install/)/[Miniconda](https://docs.conda.io/en/latest/miniconda.html) or [Mambaforge](https://mamba.readthedocs.io/en/latest/installation.html#fresh-install)
+    - [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
+
 1. Fork this repository:
 
     ![location of fork button in GitHub](./media/fork_button.png)

environment.yml

@@ -2,18 +2,18 @@ name: data_viz_workshop
 channels:
     - conda-forge
 dependencies:
-    - python>=3.8.0,<=3.10.20
-    - bokeh=2.4.3
+    - python>=3.9.0,<=3.13.0
+    - bokeh=3.4.1
     - ffmpeg
-    - geopandas=0.12.2
-    - jupyterlab>=3.5.2
-    - matplotlib=3.7.1
-    - numpy=1.23.5
-    - pandas=2.0.0
-    - seaborn=0.11.2
-    - shapely=1.8.5
-    - pyviz::geoviews-core=1.9.6
-    - pyviz::geoviews=1.9.6
-    - pyviz::holoviews=1.15.4
-    - pyviz::hvplot=0.8.3
-    - pyviz::panel=0.14.4
+    - geopandas=0.14.4
+    - jupyterlab>=4.1.8
+    - matplotlib=3.8.4
+    - numpy=1.26.4
+    - pandas=2.2.2
+    - seaborn=0.13.2
+    - shapely=2.0.4
+    - pyviz::geoviews-core=1.12.0
+    - pyviz::geoviews=1.12.0
+    - pyviz::holoviews=1.18.3
+    - pyviz::hvplot=0.9.2
+    - pyviz::panel=1.4.2

media/stackoverflow_questions.mp4

@@ -65,7 +65,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.10"
+   "version": "3.12.3"
   }
  },
  "nbformat": 4,