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notebooks/v2/analyzing_income_distribution.ipynb

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@@ -17,21 +17,26 @@
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},
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"source": [
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"Copyright 2025 Google LLC.\n",
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"SPDX-License-Identifier: Apache-2.0\n",
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"SPDX-License-Identifier: Apache-2.0"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "vWo_v5cI-JXC"
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},
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"source": [
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"# Analyzing Income Distribution\n",
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"\n",
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"The American Community Survey (published by the US Census) annually reports the number of individuals in a given income bracket at the state level. We can use this information, stored in Data Commons, to visualize disparity in income for each state in the US. Our goal for this tutorial will be to generate a plot that visualizes the total number of individuals across a given set of income brackets for a given state.\n",
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"\n",
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"**Notebook Version** - 2.0.0"
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"Before we begin, we'll set up our notebook."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "9_SFWWxoSoMn",
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"outputId": "beace858-d118-4ff9-dc65-36b998033d29"
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},
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
@@ -47,19 +52,6 @@
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"!pip install \"datacommons-client[Pandas]\" --upgrade --quiet"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "vWo_v5cI-JXC"
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},
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"source": [
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"# Analyzing Income Distribution\n",
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"\n",
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"The American Community Survey (published by the US Census) annually reports the number of individuals in a given income bracket at the state level. We can use this information, stored in Data Commons, to visualize disparity in income for each state in the US. Our goal for this tutorial will be to generate a plot that visualizes the total number of individuals across a given set of income brackets for a given state.\n",
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"\n",
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"Before we begin, we'll set up our notebook."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,

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