From 079f719c865e9b6672446928210c4ff897d3be21 Mon Sep 17 00:00:00 2001 From: MJ Rossetti Date: Thu, 31 Oct 2024 14:15:42 -0400 Subject: [PATCH] Avoid line wrapping in URLs --- docs/notes/applied-stats/basic-tests.qmd | 5 ++++- docs/notes/applied-stats/correlation.qmd | 5 ++++- docs/notes/applied-stats/data-scaling.qmd | 5 ++++- docs/notes/applied-stats/summary-stats.qmd | 5 ++++- 4 files changed, 16 insertions(+), 4 deletions(-) diff --git a/docs/notes/applied-stats/basic-tests.qmd b/docs/notes/applied-stats/basic-tests.qmd index d936d94..0255096 100644 --- a/docs/notes/applied-stats/basic-tests.qmd +++ b/docs/notes/applied-stats/basic-tests.qmd @@ -16,7 +16,10 @@ For these examples, let's us this familiar example dataset of monthly financial ```{python} from pandas import read_csv -df = read_csv("https://raw.githubusercontent.com/prof-rossetti/python-for-finance/main/docs/data/monthly-indicators.csv") +repo_url = "https://raw.githubusercontent.com/prof-rossetti/python-for-finance" +request_url = f"{repo_url}/main/docs/data/monthly-indicators.csv" + +df = read_csv(request_url) df.head() ``` diff --git a/docs/notes/applied-stats/correlation.qmd b/docs/notes/applied-stats/correlation.qmd index 626c93d..39226fb 100644 --- a/docs/notes/applied-stats/correlation.qmd +++ b/docs/notes/applied-stats/correlation.qmd @@ -27,7 +27,10 @@ To examine correlation, let's revisit our familiar dataset of economic indicator ```{python} from pandas import read_csv -df = read_csv("https://raw.githubusercontent.com/prof-rossetti/python-for-finance/main/docs/data/monthly-indicators.csv") +repo_url = "https://raw.githubusercontent.com/prof-rossetti/python-for-finance" +request_url = f"{repo_url}/main/docs/data/monthly-indicators.csv" + +df = read_csv(request_url) df.head() ``` diff --git a/docs/notes/applied-stats/data-scaling.qmd b/docs/notes/applied-stats/data-scaling.qmd index 3e49619..b88de8c 100644 --- a/docs/notes/applied-stats/data-scaling.qmd +++ b/docs/notes/applied-stats/data-scaling.qmd @@ -18,7 +18,10 @@ To illustrate the motivations behind data scaling, let's revisit our familiar da ```{python} from pandas import read_csv -df = read_csv("https://raw.githubusercontent.com/prof-rossetti/python-for-finance/main/docs/data/monthly-indicators.csv") +repo_url = "https://raw.githubusercontent.com/prof-rossetti/python-for-finance" +request_url = f"{repo_url}/main/docs/data/monthly-indicators.csv" + +df = read_csv(request_url) df.head() ``` diff --git a/docs/notes/applied-stats/summary-stats.qmd b/docs/notes/applied-stats/summary-stats.qmd index f48c3e3..1bde29b 100644 --- a/docs/notes/applied-stats/summary-stats.qmd +++ b/docs/notes/applied-stats/summary-stats.qmd @@ -16,7 +16,10 @@ Let's consider this example dataset of monthly financial and economic indicators ```{python} from pandas import read_csv -df = read_csv("https://raw.githubusercontent.com/prof-rossetti/python-for-finance/main/docs/data/monthly-indicators.csv") +repo_url = "https://raw.githubusercontent.com/prof-rossetti/python-for-finance" +request_url = f"{repo_url}/main/docs/data/monthly-indicators.csv" + +df = read_csv(request_url) df.head() ```