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Merge branch 'main' into update-business-cycle-data-364
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.github/workflows/cache.yml

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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@v6
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uses: actions/checkout@v7
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with:
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fetch-depth: 0
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- name: Setup Anaconda

.github/workflows/ci.yml

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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@v6
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uses: actions/checkout@v7
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with:
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fetch-depth: 0
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- name: Setup Anaconda
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name: execution-reports
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path: _build/html/reports
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- name: Preview Deploy to Netlify
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uses: nwtgck/actions-netlify@v3.0
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uses: nwtgck/actions-netlify@v4.0
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with:
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publish-dir: '_build/html/'
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production-branch: main

.github/workflows/collab.yml

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container:
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image: us-docker.pkg.dev/colab-images/public/runtime:latest
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steps:
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- uses: actions/checkout@v6
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- uses: actions/checkout@v7
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with:
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ref: ${{ github.event.pull_request.head.sha }}
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- name: Check for dockerenv file
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name: execution-reports
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path: _build/html/reports
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- name: Preview Deploy to Netlify
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uses: nwtgck/actions-netlify@v3.0
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uses: nwtgck/actions-netlify@v4.0
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.github/workflows/linkcheck.yml

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# Checkout the live site (html)
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- name: Checkout
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uses: actions/checkout@v6
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uses: actions/checkout@v7
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with:
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ref: gh-pages
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- name: Link Checker

.github/workflows/publish.yml

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runs-on: ubuntu-latest
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steps:
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- name: Checkout
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uses: actions/checkout@v6
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uses: actions/checkout@v7
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with:
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fetch-depth: 0
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- name: Setup Anaconda
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env:
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GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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- name: Deploy to Netlify
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uses: nwtgck/actions-netlify@v3.0
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uses: nwtgck/actions-netlify@v4.0
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environment.yml

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- default
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dependencies:
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- python=3.13
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- anaconda=2025.12
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- anaconda=2026.06
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- pip
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- pip:
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- jupyter-book==1.0.4post1
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- quantecon-book-theme==0.20.3
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- quantecon-book-theme==0.21.0
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- sphinx-tojupyter==0.6.0
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- sphinxext-rediraffe==0.3.0
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- sphinx-exercise==1.2.1

lectures/inequality.md

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# Repeat the observations according to their weights
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counts = list(round(df[df['year'] == year]['weights'] ))
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y = df[df['year'] == year][var].repeat(counts)
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y = np.asarray(y)
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# `.copy()` gives a writeable array (pandas 3.0 returns a read-only one)
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y = np.asarray(y).copy()
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# Shuffle the sequence to improve the plot
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rd.shuffle(y)

lectures/input_output.md

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```{code-cell} ipython3
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:tags: [hide-output]
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!pip install quantecon_book_networks
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!pip install quantecon_book_networks==1.6
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!pip install quantecon
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!pip install pandas-datareader
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```

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