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update link to the Spatial Data Equity Tool
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hw_2.ipynb

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"source": [
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"# Homework 2\n",
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"\n",
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"_[General assignment information](https://python-public-policy.afeld.me/en/{{school_slug}}/assignments.html)_"
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"_[General assignment information](https://python-public-policy.afeld.me/en/{{school_slug}}/assignments.html)_\n"
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]
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},
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{
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"\n",
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"- [`merge()`](https://pandas.pydata.org/docs/user_guide/merging.html#merge)\n",
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"- [How to manipulate textual data](https://pandas.pydata.org/docs/getting_started/intro_tutorials/10_text_data.html)\n",
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"- [How to create new columns derived from existing columns](https://pandas.pydata.org/docs/getting_started/intro_tutorials/05_add_columns.html)"
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"- [How to create new columns derived from existing columns](https://pandas.pydata.org/docs/getting_started/intro_tutorials/05_add_columns.html)\n"
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]
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},
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"source": [
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"## Coding\n",
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"\n",
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"The goal here is to practice joining datasets through pandas. Hint: The instructions here are intentionally incomplete."
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"The goal here is to practice joining datasets through pandas. Hint: The instructions here are intentionally incomplete.\n"
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]
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},
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{
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"\n",
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"- Use [Scout](https://scoutopendata.com/explore/NYC) to filter by column name.\n",
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"- Don't spend too long on this step.\n",
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"- [Keep the dataset small](https://python-public-policy.afeld.me/en/{{school_slug}}/assignments/open_ended.html#reducing-data-size) (under 500,000-ish rows) to make it easier to work with."
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"- [Keep the dataset small](https://python-public-policy.afeld.me/en/{{school_slug}}/assignments/open_ended.html#reducing-data-size) (under 500,000-ish rows) to make it easier to work with.\n"
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]
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},
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{
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"tags": []
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},
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"source": [
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"**What's the URL of your dataset?**"
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"**What's the URL of your dataset?**\n"
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]
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},
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{
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]
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},
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"source": [
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"YOUR RESPONSE HERE"
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"YOUR RESPONSE HERE\n"
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]
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},
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{
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"source": [
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"### Step 1\n",
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"\n",
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"[Load it into Jupyter.](https://python-public-policy.afeld.me/en/{{school_slug}}/assignments/open_ended.html#storing-data)"
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"[Load it into Jupyter.](https://python-public-policy.afeld.me/en/{{school_slug}}/assignments/open_ended.html#storing-data)\n"
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]
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},
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{
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"source": [
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"### Step 2\n",
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"\n",
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"Open the [Population by Borough](https://data.cityofnewyork.us/City-Government/New-York-City-Population-by-Borough-1950-2040/xywu-7bv9) dataset and [load it into Jupyter](https://python-public-policy.afeld.me/en/{{school_slug}}/assignments/open_ended.html#storing-data)."
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"Open the [Population by Borough](https://data.cityofnewyork.us/City-Government/New-York-City-Population-by-Borough-1950-2040/xywu-7bv9) dataset and [load it into Jupyter](https://python-public-policy.afeld.me/en/{{school_slug}}/assignments/open_ended.html#storing-data).\n"
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]
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},
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"source": [
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"### Step 3\n",
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"\n",
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"Use [`merge()`](https://pandas.pydata.org/docs/user_guide/merging.html#merge) to combine the two, and output the resulting table."
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"Use [`merge()`](https://pandas.pydata.org/docs/user_guide/merging.html#merge) to combine the two, and output the resulting table.\n"
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]
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},
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"<details>\n",
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"<summary><strong>Hint</strong></summary>\n",
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"Having trouble merging the datasets? Try looking at the unique values in the columns you're trying to merge on.\n",
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"</details>"
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"</details>\n"
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]
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},
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{
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"1. Do a [`groupby()`](https://pandas.pydata.org/docs/user_guide/groupby.html) on the original dataset.\n",
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"1. Join with the populations by borough.\n",
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"1. Compute the per-capita values as a new column.\n",
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"</details>"
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"</details>\n"
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]
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},
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{
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"\n",
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"- [Pythonic Data Cleaning With Pandas and NumPy](https://realpython.com/python-data-cleaning-numpy-pandas/)\n",
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"- [\"You’re Not Mapping Rats, You're Mapping Gentrification\"](https://deadspin.com/you-re-not-mapping-rats-you-re-mapping-gentrification-1835005060/) — article about bias in 311 data\n",
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"- [The Spatial Data Equity Tool](https://medium.com/@urban_institute/introducing-a-spatial-equity-data-tool-b959c40298cf)\n",
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"- [The Spatial Data Equity Tool](https://urban-institute.medium.com/introducing-the-spatial-equity-data-tool-version-2-f2a8e900f84)\n",
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"- [Intro to Plotly Express](https://plotly.com/python/plotly-express/). You don't have to work through every one of these examples; just review to get familiar with what types of charts are possible.\n",
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"\n",
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"### Optional\n",
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"\n",
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"## Participation\n",
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"\n",
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"Reminder about the [between-class participation requirement](https://python-public-policy.afeld.me/en/{{school_slug}}/syllabus.html#participation)."
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"Reminder about the [between-class participation requirement](https://python-public-policy.afeld.me/en/{{school_slug}}/syllabus.html#participation).\n"
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]
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}
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],

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