Merge branch 'maint-18octb' of https://github.com/QuantEcon/lecture-python-programming.myst into maint-18octb

Author: mmcky

.github/workflows/cache.yml

@@ -31,4 +31,5 @@ jobs:
         uses: actions/upload-artifact@v4
         with:
           name: build-cache
-          path: _build
+          path: _build
+          include-hidden-files: true

environment.yml

@@ -3,7 +3,7 @@ channels:
   - default
 dependencies:
   - python=3.12
-  - anaconda=2024.06
+  - anaconda=2024.10
   - pip
   - pip:
     - jupyter-book==1.0.3

lectures/_config.yml

@@ -23,7 +23,9 @@ sphinx:
                        'https://ieeexplore.ieee.org/document/8757088',
                        'https://www.sciencedirect.com/science/article/pii/S1477388021000177',
                        'https://keras.io/',
-                       'https://data.oecd.org/']
+                       'https://data.oecd.org/',
+                       'https://www.reddit.com/',
+                       'https://openai.com']
     html_favicon: _static/lectures-favicon.ico
     html_theme: quantecon_book_theme
     html_static_path: ['_static']

lectures/pandas.md

@@ -509,11 +509,7 @@ For example, suppose that we are interested in the [unemployment rate](https://r
 Via FRED, the entire series for the US civilian unemployment rate can be downloaded directly by entering
 this URL into your browser (note that this requires an internet connection)
 
-```{code-block} none
-https://research.stlouisfed.org/fred2/series/UNRATE/downloaddata/UNRATE.csv
-```
-
-(Equivalently, click here: [https://research.stlouisfed.org/fred2/series/UNRATE/downloaddata/UNRATE.csv](https://research.stlouisfed.org/fred2/series/UNRATE/downloaddata/UNRATE.csv))
+(To download the data as a csv, click here: [https://research.stlouisfed.org/fred2/series/UNRATE/downloaddata/UNRATE.csv](https://fred.stlouisfed.org/graph/fredgraph.csv?bgcolor=%23e1e9f0&chart_type=line&drp=0&fo=open%20sans&graph_bgcolor=%23ffffff&height=450&mode=fred&recession_bars=on&txtcolor=%23444444&ts=12&tts=12&width=1320&nt=0&thu=0&trc=0&show_legend=yes&show_axis_titles=yes&show_tooltip=yes&id=UNRATE&scale=left&cosd=1948-01-01&coed=2024-10-01&line_color=%234572a7&link_values=false&line_style=solid&mark_type=none&mw=3&lw=3&ost=-99999&oet=99999&mma=0&fml=a&fq=Monthly&fam=avg&fgst=lin&fgsnd=2020-02-01&line_index=1&transformation=lin&vintage_date=2024-11-03&revision_date=2024-11-03&nd=1948-01-01))
 
 This request returns a CSV file, which will be handled by your default application for this class of files.
 

lectures/workspace.md

@@ -121,7 +121,7 @@ This lecture takes you through the workings of two development environments.
 
 JupyterLab is a browser based development environment for Jupyter Notebooks, code scripts, and data files.
 
-You can [try JupyterLab in the browser](https://jupyter.org/try#jupyterlab) if you want to test it out before installing it locally.
+You can [try JupyterLab in the browser](https://jupyter.org/try-jupyter/lab/) if you want to test it out before installing it locally.
 
 You can install JupyterLab using pip