Skip to content

Use CORS-clean hosts for in-browser data reads #54

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
mmcky merged 1 commit into from
Aug 6, 2026
Merged

Use CORS-clean hosts for in-browser data reads #54

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion lectures/inequality.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -247,7 +247,7 @@ The following code block imports a subset of the dataset `SCF_plus` for 2016,
which is derived from the [Survey of Consumer Finances](https://en.wikipedia.org/wiki/Survey_of_Consumer_Finances) (SCF).

```{code-cell} ipython3
url = 'https://github.com/QuantEcon/high_dim_data/raw/main/SCF_plus/SCF_plus_mini.csv'
url = 'https://media.githubusercontent.com/media/QuantEcon/high_dim_data/main/SCF_plus/SCF_plus_mini.csv'
df = pd.read_csv(url)
df_income_wealth = df.dropna()
```
Expand Down
4 changes: 2 additions & 2 deletions lectures/inflation_history.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -73,7 +73,7 @@ Let us bring the data into pandas from a spreadsheet that is [hosted on GitHub](
```{code-cell} ipython3
# Import data and clean up the index
pyodide_http.patch_all()
data_url = "https://github.com/QuantEcon/data-lectures/raw/main/lectures/longprices.xls"
data_url = "https://raw.githubusercontent.com/QuantEcon/data-lectures/main/lectures/longprices.xls"
df_fig5 = pd.read_excel(data_url,
sheet_name='all',
header=2,
Expand Down Expand Up @@ -347,7 +347,7 @@ We prepare the data for each country

```{code-cell} ipython3
# Import data
data_url = "https://github.com/QuantEcon/data-lectures/raw/main/lectures/chapter_3.xlsx"
data_url = "https://raw.githubusercontent.com/QuantEcon/data-lectures/main/lectures/chapter_3.xlsx"
xls = pd.ExcelFile(data_url)

# Select relevant sheets
Expand Down
2 changes: 1 addition & 1 deletion lectures/long_run_growth.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -94,7 +94,7 @@ Here we read the Maddison data into a pandas `DataFrame`:

```{code-cell} ipython3
pyodide_http.patch_all()
data_url = "https://github.com/QuantEcon/data-lectures/raw/main/lectures/mpd2020.xlsx"
data_url = "https://raw.githubusercontent.com/QuantEcon/data-lectures/main/lectures/mpd2020.xlsx"
data = pd.read_excel(data_url,
sheet_name='Full data')
data.head()
Expand Down
2 changes: 1 addition & 1 deletion lectures/mle.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -92,7 +92,7 @@ The following code imports this data and reads it into an array called `sample`
```{code-cell} ipython3
:tags: [hide-input]

url = 'https://github.com/QuantEcon/high_dim_data/raw/main/SCF_plus/SCF_plus_mini_no_weights.csv'
url = 'https://media.githubusercontent.com/media/QuantEcon/high_dim_data/main/SCF_plus/SCF_plus_mini_no_weights.csv'
df = pd.read_csv(url)
df = df.dropna()
df = df[df['year'] == 2016]
Expand Down
Loading