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inflation_history: read longprices.xls and chapter_3.xlsx from data-lectures #824

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mmcky merged 4 commits into from
Aug 6, 2026
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inflation_history: read longprices.xls and chapter_3.xlsx from data-lectures #824

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inflation_history: read longprices.xls and chapter_3.xlsx from data-l…
mmcky Aug 6, 2026
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inflation_history: repoint the "hosted on github" link too
mmcky Aug 6, 2026
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inflation_history: capitalise GitHub in the narrative link
mmcky Aug 6, 2026
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Keep the local copies for now: repoint first, delete after the next p…
mmcky Aug 6, 2026
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8 changes: 4 additions & 4 deletions lectures/inflation_history.md
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Expand Up @@ -79,11 +79,11 @@ 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
data_url = "https://github.com/QuantEcon/lecture-python-intro/raw/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,
Expand Down Expand Up @@ -225,7 +225,7 @@ 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`.

Expand Down Expand Up @@ -355,7 +355,7 @@ We prepare the data for each country

```{code-cell} ipython3
# Import data
data_url = "https://github.com/QuantEcon/lecture-python-intro/raw/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
Expand Down
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