From edb76c65d8313aa080583ed2aa43f7263977b947 Mon Sep 17 00:00:00 2001 From: mmcky Date: Fri, 1 Mar 2024 13:47:05 +1100 Subject: [PATCH] minor updates to code output --- lectures/inequality.md | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/lectures/inequality.md b/lectures/inequality.md index aa4eb4d1..88f4b42b 100644 --- a/lectures/inequality.md +++ b/lectures/inequality.md @@ -64,6 +64,7 @@ For each of these measures, we will look at both simulated and real data. We will need to install the following packages ```{code-cell} ipython3 +:tags: [hide-output] !pip install wbgapi ``` @@ -582,7 +583,6 @@ plt.show() Looking at this graph you can see that inequality was falling in the USA until 1981 when it appears to have started to change course and steadily rise over time (growing inequality). ```{admonition} TODO -:class: warning Why did GINI fall in 2020? I would have thought it accelerate in the other direction or was there a lag in investment returns around COVID ``` @@ -633,10 +633,7 @@ results.to_csv("_static/lecture_specific/inequality/usa-gini-nwealth-tincome-lin ```{code-cell} ipython3 ginis = pd.read_csv("_static/lecture_specific/inequality/usa-gini-nwealth-tincome-lincome.csv", index_col='year') -``` - -```{code-cell} ipython3 -ginis +ginis.head(n=5) ``` Let's plot the Gini coefficients for net wealth, labor income and total income.