diff --git a/lectures/datasets/chapter_3.xlsx b/lectures/datasets/chapter_3.xlsx
deleted file mode 100644
index 1a2e141..0000000
Binary files a/lectures/datasets/chapter_3.xlsx and /dev/null differ
diff --git a/lectures/datasets/longprices.xls b/lectures/datasets/longprices.xls
deleted file mode 100644
index a3f100e..0000000
Binary files a/lectures/datasets/longprices.xls and /dev/null differ
diff --git a/lectures/inflation_history.md b/lectures/inflation_history.md
index a3e77d1..dda01f4 100644
--- a/lectures/inflation_history.md
+++ b/lectures/inflation_history.md
@@ -68,12 +68,12 @@ In the present context, the  phrase "hard currency" means that the countries wer
 Under a gold or silver standard, some money also consisted of "warehouse certificates" that represented paper claims on gold or silver coins. Bank notes issued by the government or private banks can be viewed as examples of such "warehouse certificates".
 ```
 
-Let us bring the data into pandas from a spreadsheet that is [hosted on github](https://github.com/QuantEcon/lecture-python-intro/tree/main/lectures/datasets).
+Let us bring the data into pandas from a spreadsheet that is [hosted on GitHub](https://github.com/QuantEcon/data-lectures/blob/main/CATALOG.md).
 
 ```{code-cell} ipython3
 # Import data and clean up the index
 pyodide_http.patch_all()
-data_url = "https://raw.githubusercontent.com/QuantEcon/lecture-python-intro/main/lectures/datasets/longprices.xls"
+data_url = "https://github.com/QuantEcon/data-lectures/raw/main/lectures/longprices.xls"
 df_fig5 = pd.read_excel(data_url, 
                         sheet_name='all', 
                         header=2, 
@@ -217,7 +217,7 @@ We have added logarithms of the exchange rates vis-à-vis the US dollar to
 from chapter 3 of {cite}`sargent2013rational`.
 
 Data underlying our graphs appear in tables in an appendix to chapter 3 of {cite}`sargent2013rational`.
-We have transcribed all of these data into a spreadsheet {download}`chapter_3.xlsx <https://github.com/QuantEcon/lecture-python-intro/raw/main/lectures/datasets/chapter_3.xlsx>` that we read into pandas.
+We have transcribed all of these data into a spreadsheet {download}`chapter_3.xlsx <https://github.com/QuantEcon/data-lectures/raw/main/lectures/chapter_3.xlsx>` that we read into pandas.
 
 In the code cell below we clean the data and build a `pandas.dataframe`.
 
@@ -347,7 +347,7 @@ We prepare the data for each country
 
 ```{code-cell} ipython3
 # Import data
-data_url = "https://raw.githubusercontent.com/QuantEcon/lecture-python-intro/main/lectures/datasets/chapter_3.xlsx"
+data_url = "https://github.com/QuantEcon/data-lectures/raw/main/lectures/chapter_3.xlsx"
 xls = pd.ExcelFile(data_url)
 
 # Select relevant sheets