Merge pull request #7 from dlab-berkeley/main

add Python workshops

Brewfile

@@ -0,0 +1,29 @@
+tap "homebrew/bundle"
+tap "homebrew/cask"
+tap "homebrew/core"
+brew "harfbuzz"
+brew "pango"
+brew "adwaita-icon-theme"
+brew "augeas"
+brew "bchunk"
+brew "berkeley-db@4"
+brew "enca"
+brew "geckodriver"
+brew "git"
+brew "git-lfs"
+brew "libidn2"
+brew "gtk-mac-integration"
+brew "iso-codes"
+brew "gspell"
+brew "gtksourceview3"
+brew "krb5"
+brew "libxml2"
+brew "pandoc", link: false
+brew "postgresql@14"
+brew "py3cairo"
+brew "pyenv"
+brew "rename"
+brew "ruby"
+brew "wget"
+cask "emacs"
+cask "wine-stable"

Gemfile

@@ -6,4 +6,4 @@ git_source(:github) {|repo_name| "https://github.com/#{repo_name}" }
 
 # gem "rails"
 
-gem "jekyll", "~> 3.8"
+gem "jekyll", "~> 4.2"

Gemfile.lock

@@ -4,60 +4,67 @@ GEM
     addressable (2.8.1)
       public_suffix (>= 2.0.2, < 6.0)
     colorator (1.1.0)
-    concurrent-ruby (1.1.5)
-    em-websocket (0.5.1)
+    concurrent-ruby (1.2.2)
+    em-websocket (0.5.3)
       eventmachine (>= 0.12.9)
-      http_parser.rb (~> 0.6.0)
+      http_parser.rb (~> 0)
     eventmachine (1.2.7)
-    ffi (1.11.1)
+    ffi (1.15.5)
     forwardable-extended (2.6.0)
-    http_parser.rb (0.6.0)
-    i18n (0.9.5)
+    google-protobuf (3.22.2-x86_64-darwin)
+    http_parser.rb (0.8.0)
+    i18n (1.12.0)
       concurrent-ruby (~> 1.0)
-    jekyll (3.8.4)
+    jekyll (4.3.2)
       addressable (~> 2.4)
       colorator (~> 1.0)
       em-websocket (~> 0.5)
-      i18n (~> 0.7)
-      jekyll-sass-converter (~> 1.0)
+      i18n (~> 1.0)
+      jekyll-sass-converter (>= 2.0, < 4.0)
       jekyll-watch (~> 2.0)
-      kramdown (~> 1.14)
+      kramdown (~> 2.3, >= 2.3.1)
+      kramdown-parser-gfm (~> 1.0)
       liquid (~> 4.0)
-      mercenary (~> 0.3.3)
+      mercenary (>= 0.3.6, < 0.5)
       pathutil (~> 0.9)
-      rouge (>= 1.7, < 4)
+      rouge (>= 3.0, < 5.0)
       safe_yaml (~> 1.0)
-    jekyll-sass-converter (1.5.2)
-      sass (~> 3.4)
+      terminal-table (>= 1.8, < 4.0)
+      webrick (~> 1.7)
+    jekyll-sass-converter (3.0.0)
+      sass-embedded (~> 1.54)
     jekyll-watch (2.2.1)
       listen (~> 3.0)
-    kramdown (1.17.0)
-    liquid (4.0.3)
-    listen (3.1.5)
-      rb-fsevent (~> 0.9, >= 0.9.4)
-      rb-inotify (~> 0.9, >= 0.9.7)
-      ruby_dep (~> 1.2)
-    mercenary (0.3.6)
+    kramdown (2.4.0)
+      rexml
+    kramdown-parser-gfm (1.1.0)
+      kramdown (~> 2.0)
+    liquid (4.0.4)
+    listen (3.8.0)
+      rb-fsevent (~> 0.10, >= 0.10.3)
+      rb-inotify (~> 0.9, >= 0.9.10)
+    mercenary (0.4.0)
     pathutil (0.16.2)
       forwardable-extended (~> 2.6)
     public_suffix (5.0.1)
-    rb-fsevent (0.10.3)
-    rb-inotify (0.10.0)
+    rb-fsevent (0.11.2)
+    rb-inotify (0.10.1)
       ffi (~> 1.0)
-    rouge (3.11.0)
-    ruby_dep (1.5.0)
+    rexml (3.2.5)
+    rouge (4.1.0)
     safe_yaml (1.0.5)
-    sass (3.7.4)
-      sass-listen (~> 4.0.0)
-    sass-listen (4.0.0)
-      rb-fsevent (~> 0.9, >= 0.9.4)
-      rb-inotify (~> 0.9, >= 0.9.7)
+    sass-embedded (1.60.0-x86_64-darwin)
+      google-protobuf (~> 3.21)
+    terminal-table (3.0.2)
+      unicode-display_width (>= 1.1.1, < 3)
+    unicode-display_width (2.4.2)
+    webrick (1.8.1)
 
 PLATFORMS
   ruby
 
 DEPENDENCIES
-  jekyll (~> 3.8)
+  jekyll (~> 4.2)
 
 BUNDLED WITH
    1.16.2

_featured/1.md

@@ -1,10 +1,10 @@
 ---
-title: Deep Learning in R
-course_name: Deep Learning in R
-instructor: Evan Muzzall
-github_link: https://github.com/dlab-berkeley/Deep-Learning-in-R
-datahub_link: http://datahub.berkeley.edu/user-redirect/interact?account=dlab-berkeley&repo=Deep-Learning-in-R&branch=master&path=
+title: Python Fundamentals
+course_name: The absolute basics
+instructor:
+github_link:
+datahub_link:
 nbviewer_link:
-binder_link: https://mybinder.org/v2/gh/dlab-berkeley/Deep-Learning-in-R/master
+binder_link:
 ---
-Convey the basics of deep learning in R using keras on image datasets. Students are empowered with a general grasp of deep learning, example code that they can modify, a working computational environment, and resources for further study.
+This three-part interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience, with a focus on data science application. It covers the basics of Python and Jupyter, variables and data types, and a gentle introduction to data analysis in Pandas.

_featured/2.md

@@ -1,10 +1,10 @@
 ---
-title: Geospatial Fundamentals in R with sf
-course_name: Geospatial Fundamentals in R with sf
-instructor: Patty Frontiera
-github_link: https://github.com/dlab-berkeley/Geospatial-Fundamentals-in-R-with-sf
-datahub_link: http://datahub.berkeley.edu/user-redirect/interact?account=dlab-berkeley&repo=Geospatial-Fundamentals-in-R-with-sf&branch=master&path=
+title: Python Data Wrangling
+course_name: Manipulate DataFrames using Pandas in Python
+instructor:
+github_link:
+datahub_link:
 nbviewer_link:
-binder_link: https://mybinder.org/v2/gh/dlab-berkeley/Geospatial-Fundamentals-in-R-with-sf/master
+binder_link:
 ---
-D-Lab's Geospatial Fundamentals in R with sf (simple features) workshop, focusing on core concepts of geospatial information, vector data, and plotting; spatial analysis; raster data.
+In this workshop, we provide an introduction to data wrangling with Python. We will do so largely with the pandas package, which provides a rich set of tools to manipulate and interact with data frames, the most common data structure used when analyzing tabular data. We'll learn how to manipulate, index, merge, group, and plot data frames using pandas functions.

_featured/3.md

@@ -1,10 +1,10 @@
 ---
-title: Geocoding in R
-course_name: Geocoding in R
-instructor: Patty Frontiera
-github_link: https://github.com/dlab-berkeley/Geocoding-in-R
-datahub_link: http://datahub.berkeley.edu/user-redirect/interact?account=dlab-berkeley&repo=Geocoding-in-R&branch=master&path=
+title: Python Data Visualization
+course_name: Pandas, Matplotlib, and Seaborn
+instructor:
+github_link:
+datahub_link:
 nbviewer_link:
-binder_link: https://mybinder.org/v2/gh/dlab-berkeley/Geocoding-in-R/master
+binder_link:
 ---
-geocode in R using three online services: Google Geocoding API, ESRI World Geocoding Service, US Census Geocoder
+In this workshop, we provide an introduction to data visualization with Python. First, we'll cover some basics of visualization theory. Then, we'll explore how to plot data in Python using the matplotlib and seaborn packages.

docs/Brewfile

@@ -0,0 +1,29 @@
+tap "homebrew/bundle"
+tap "homebrew/cask"
+tap "homebrew/core"
+brew "harfbuzz"
+brew "pango"
+brew "adwaita-icon-theme"
+brew "augeas"
+brew "bchunk"
+brew "berkeley-db@4"
+brew "enca"
+brew "geckodriver"
+brew "git"
+brew "git-lfs"
+brew "libidn2"
+brew "gtk-mac-integration"
+brew "iso-codes"
+brew "gspell"
+brew "gtksourceview3"
+brew "krb5"
+brew "libxml2"
+brew "pandoc", link: false
+brew "postgresql@14"
+brew "py3cairo"
+brew "pyenv"
+brew "rename"
+brew "ruby"
+brew "wget"
+cask "emacs"
+cask "wine-stable"