🌐 [translation-sync] french_rev: read the five datasets from data-lectures

.translate/state/french_rev.md.yml

@@ -1,6 +1,6 @@
-source-sha: 72ae33d877de134693fda82dcc761fdbe9a0501d
-synced-at: "2026-07-18"
+source-sha: 6986e35a3f3e0c87c47713ffe48af5c3ca0a191b
+synced-at: "2026-08-06"
 model: claude-sonnet-5
-mode: RESYNC
+mode: UPDATE
 section-count: 8
-tool-version: 0.17.0
+tool-version: 0.25.0

lectures/french_rev.md

@@ -4,7 +4,7 @@ jupytext:
     extension: .md
     format_name: myst
     format_version: 0.13
-    jupytext_version: 1.16.1
+    jupytext_version: 1.16.7
 kernelspec:
   display_name: Python 3 (ipykernel)
   language: python
@@ -24,7 +24,6 @@ translation:
 
 # 法国大革命期间的通货膨胀
 
-
 ## 概览
 
 本讲座描述了 {cite}`sargent_velde1995` 中所写的法国大革命（1789-1799）期间的一些货币和财政特征。
@@ -65,23 +64,25 @@ translation:
 ## 数据来源
 
 本讲使用了 {cite}`sargent_velde1995` 中汇编的三个表格中的数据：
-  * [datasets/fig_3.xlsx](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/datasets/fig_3.xlsx)
-  * [datasets/dette.xlsx](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/datasets/dette.xlsx)
-  * [datasets/assignat.xlsx](https://github.com/QuantEcon/lecture-python-intro/blob/main/lectures/datasets/assignat.xlsx)
+  * [fig_3.xlsx](https://github.com/QuantEcon/data-lectures/blob/main/lectures/fig_3.xlsx)
+  * [dette.xlsx](https://github.com/QuantEcon/data-lectures/blob/main/lectures/dette.xlsx)
+  * [assignat.xlsx](https://github.com/QuantEcon/data-lectures/blob/main/lectures/assignat.xlsx)
 
 ```{code-cell} ipython3
 import numpy as np
 import pandas as pd
 import matplotlib.pyplot as plt
+from io import BytesIO
+import requests
 plt.rcParams.update({'font.size': 12})
 
 import matplotlib as mpl
 FONTPATH = "fonts/SourceHanSerifSC-SemiBold.otf"
 mpl.font_manager.fontManager.addfont(FONTPATH)
 plt.rcParams['font.family'] = ['Source Han Serif SC']
 
-base_url = 'https://github.com/QuantEcon/lecture-python-intro/raw/'\
-           + 'main/lectures/datasets/'
+base_url = 'https://github.com/QuantEcon/data-lectures/raw/'\
+           + 'main/lectures/'
 
 fig_3_url = f'{base_url}fig_3.xlsx'
 dette_url = f'{base_url}dette.xlsx'
@@ -667,8 +668,10 @@ def fit(x, y):
 
 ```{code-cell} ipython3
 # 加载数据
-caron = np.load('datasets/caron.npy')
-nom_balances = np.load('datasets/nom_balances.npy')
+caron_response = requests.get(f'{base_url}caron.npy')
+nom_balances_response = requests.get(f'{base_url}nom_balances.npy')
+caron = np.load(BytesIO(caron_response.content))
+nom_balances = np.load(BytesIO(nom_balances_response.content))
 
 infl = np.concatenate(([np.nan], 
       -np.log(caron[1:63, 1] / caron[0:62, 1])))
@@ -1131,4 +1134,4 @@ plt.show()
 相比之下，真实票据时期和恶性通货膨胀时期的散点云都符合这样一种理论：实际余额是由公众自主选择的，因而会对通货膨胀作出反应。
 
 ```{solution-end}
-```
+```