From 71c357cf192bb555e863944c1300c09de258c046 Mon Sep 17 00:00:00 2001 From: Shu Date: Wed, 3 May 2023 17:57:48 +1000 Subject: [PATCH] update_data_urls --- lectures/heavy_tails.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/lectures/heavy_tails.md b/lectures/heavy_tails.md index ce709338b..be35de3dc 100644 --- a/lectures/heavy_tails.md +++ b/lectures/heavy_tails.md @@ -647,7 +647,7 @@ Here is a plot of the firm size distribution for the largest 500 firms in 2020 t ```{code-cell} ipython3 :tags: [hide-input] -df_fs = pd.read_csv('https://media.githubusercontent.com/media/QuantEcon/high_dim_data/update_csdata/cross_section/forbes-global2000.csv') +df_fs = pd.read_csv('https://media.githubusercontent.com/media/QuantEcon/high_dim_data/main/cross_section/forbes-global2000.csv') df_fs = df_fs[['Country', 'Sales', 'Profits', 'Assets', 'Market Value']] fig, ax = plt.subplots(figsize=(6.4, 3.5)) @@ -669,8 +669,8 @@ The size is measured by population. :tags: [hide-input] # import population data of cities in 2023 United States and 2023 Brazil from world population review -df_cs_us = pd.read_csv('https://media.githubusercontent.com/media/QuantEcon/high_dim_data/update_csdata/cross_section/cities_us.csv') -df_cs_br = pd.read_csv('https://media.githubusercontent.com/media/QuantEcon/high_dim_data/update_csdata/cross_section/cities_brazil.csv') +df_cs_us = pd.read_csv('https://media.githubusercontent.com/media/QuantEcon/high_dim_data/main/cross_section/cities_us.csv') +df_cs_br = pd.read_csv('https://media.githubusercontent.com/media/QuantEcon/high_dim_data/main/cross_section/cities_brazil.csv') fig, axes = plt.subplots(1, 2, figsize=(8.8, 3.6)) @@ -689,7 +689,7 @@ The data is from the Forbes Billionaires list in 2020. ```{code-cell} ipython3 :tags: [hide-input] -df_w = pd.read_csv('https://media.githubusercontent.com/media/QuantEcon/high_dim_data/update_csdata/cross_section/forbes-billionaires.csv') +df_w = pd.read_csv('https://media.githubusercontent.com/media/QuantEcon/high_dim_data/main/cross_section/forbes-billionaires.csv') df_w = df_w[['country', 'realTimeWorth', 'realTimeRank']].dropna() df_w = df_w.astype({'realTimeRank': int}) df_w = df_w.sort_values('realTimeRank', ascending=True).copy()