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8 changes: 4 additions & 4 deletions .translate/state/pandas.md.yml
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@@ -1,6 +1,6 @@
source-sha: 9490497982787a5b0eb54ee1dcd73ac326d5ae04
synced-at: "2026-03-20"
source-sha: 02e57a5befc2a9a081019edc748aba15e4b2f02a
synced-at: "2026-04-09"
model: claude-sonnet-4-6
mode: NEW
mode: UPDATE
section-count: 5
tool-version: 0.13.1
tool-version: 0.14.0
6 changes: 3 additions & 3 deletions .translate/state/python_advanced_features.md.yml
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source-sha: f791129259d11c138d7662c88f994c9d5ebaa875
synced-at: "2026-03-25"
source-sha: 02e57a5befc2a9a081019edc748aba15e4b2f02a
synced-at: "2026-04-09"
model: claude-sonnet-4-6
mode: UPDATE
section-count: 7
tool-version: 0.13.0
tool-version: 0.14.0
4 changes: 2 additions & 2 deletions lectures/pandas.md
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Expand Up @@ -179,7 +179,7 @@ s
我们将使用 `pandas` 函数 `read_csv` 从 URL 读取数据。

```{code-cell} ipython3
df = pd.read_csv('https://raw.githubusercontent.com/QuantEcon/lecture-python-programming/master/source/_static/lecture_specific/pandas/data/test_pwt.csv')
df = pd.read_csv('https://raw.githubusercontent.com/QuantEcon/lecture-python-programming/main/lectures/_static/lecture_specific/pandas/data/test_pwt.csv')
type(df)
```

Expand Down Expand Up @@ -814,4 +814,4 @@ plt.tight_layout()
```{solution-end}
```

[^mung]: 维基百科将数据整理(munging)定义为将数据从一种原始形式清理为结构化、净化形式的过程。
[^mung]: 维基百科将数据整理(munging)定义为将数据从一种原始形式清理为结构化、净化形式的过程。
2 changes: 1 addition & 1 deletion lectures/python_advanced_features.md
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Expand Up @@ -1195,7 +1195,7 @@ sum(draws)
:label: paf_ex1
```

完成以下代码,并使用[此 csv 文件](https://raw.githubusercontent.com/QuantEcon/lecture-python-programming/master/source/_static/lecture_specific/python_advanced_features/test_table.csv)进行测试,我们假设你已将该文件放在当前工作目录中:
完成以下代码,并使用 [此 csv 文件](https://raw.githubusercontent.com/QuantEcon/lecture-python-programming/main/lectures/_static/lecture_specific/python_advanced_features/test_table.csv) 进行测试,我们假设你已将该文件放在当前工作目录中:

```{code-block} python3
:class: no-execute
Expand Down
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