GitHub

@@ -77,7 +77,7 @@ countries and assign it to `realwage`.

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The dataset can be accessed with the following link:

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```{code-cell} ipython3

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url1 = 'https://raw.githubusercontent.com/QuantEcon/lecture-python/master/source/_static/lecture_specific/pandas_panel/realwage.csv'

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url1 = 'https://raw.githubusercontent.com/QuantEcon/lecture-python-programming/main/lectures/_static/lecture_specific/pandas_panel/realwage.csv'

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```

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```{code-cell} ipython3

@@ -197,7 +197,7 @@ function.

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The dataset can be accessed with the following link:

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```{code-cell} ipython3

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url2 = 'https://raw.githubusercontent.com/QuantEcon/lecture-python/master/source/_static/lecture_specific/pandas_panel/countries.csv'

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url2 = 'https://raw.githubusercontent.com/QuantEcon/lecture-python-programming/main/lectures/_static/lecture_specific/pandas_panel/countries.csv'

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```

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```{code-cell} ipython3

@@ -506,7 +506,7 @@ in Europe by age and sex from [Eurostat](https://ec.europa.eu/eurostat/data/data

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The dataset can be accessed with the following link:

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```{code-cell} ipython3

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url3 = 'https://raw.githubusercontent.com/QuantEcon/lecture-python/master/source/_static/lecture_specific/pandas_panel/employ.csv'

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url3 = 'https://raw.githubusercontent.com/QuantEcon/lecture-python-programming/main/lectures/_static/lecture_specific/pandas_panel/employ.csv'

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```

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Reading in the CSV file returns a panel dataset in long format. Use `.pivot_table()` to construct

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