diff --git a/.gitignore b/.gitignore
index 02d30563..d1e96dd0 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,6 +5,7 @@ dask-worker-space
 
 .vscode/
 .ipynb_checkpoints/
+.virtual_documents/
 
 lectures/mathfoo.py
 lectures/mod.py
diff --git a/lectures/_config.yml b/lectures/_config.yml
index ed5d990d..78ea39d0 100644
--- a/lectures/_config.yml
+++ b/lectures/_config.yml
@@ -25,7 +25,8 @@ sphinx:
                        'https://keras.io/',
                        'https://data.oecd.org/',
                        'https://www.reddit.com/',
-                       'https://openai.com']
+                       'https://openai.com',
+                       'https://chatgpt.com/']
     html_favicon: _static/lectures-favicon.ico
     html_theme: quantecon_book_theme
     html_static_path: ['_static']
diff --git a/lectures/numpy.md b/lectures/numpy.md
index ff495cc8..05dea077 100644
--- a/lectures/numpy.md
+++ b/lectures/numpy.md
@@ -709,7 +709,7 @@ row, column = a.shape
 result = np.empty((3, 3))
 for i in range(row):
     for j in range(column):
-        result[i, j] = a[i, j] + b[i]
+        result[i, j] = a[i, j] + b[i,0]
 
 result
 ```
@@ -1474,6 +1474,17 @@ print(A)
 
 **Part2**: Move on to replicate the result of the following broadcasting operation. Meanwhile, compare the speeds of broadcasting and the `for` loop you implement.
 
+For this part of the exercise you can use the `tic`/`toc` functions from the `quantecon` library to time the execution. 
+
+Let's make sure this library is installed.
+
+```{code-cell} python3
+:tags: [hide-output]
+!pip install quantecon
+```
+
+Now we can import the quantecon package.
+
 ```{code-cell} python3
 import quantecon as qe
 
diff --git a/lectures/pandas.md b/lectures/pandas.md
index 30096241..f3830973 100644
--- a/lectures/pandas.md
+++ b/lectures/pandas.md
@@ -506,12 +506,7 @@ An important database for economists is [FRED](https://research.stlouisfed.org/f
 
 For example, suppose that we are interested in the [unemployment rate](https://research.stlouisfed.org/fred2/series/UNRATE).
 
-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)
-
-(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.
+(To download the data as a csv, click on the top right `Download` and select the `CSV (data)` option).
 
 Alternatively, we can access the CSV file from within a Python program.