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Development","sub_category":"Population and Poverty","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"# censusdis\n\n[![Hippocratic License HL3-CL-ECO-EXTR-FFD-LAW-MIL-SV](https://img.shields.io/static/v1?label=Hippocratic%20License\u0026message=HL3-CL-ECO-EXTR-FFD-LAW-MIL-SV\u0026labelColor=5e2751\u0026color=bc8c3d)](https://firstdonoharm.dev/version/3/0/cl-eco-extr-ffd-law-mil-sv.html)\n![PyPI](https://img.shields.io/pypi/v/censusdis)\n![PyPI - Python Version](https://img.shields.io/pypi/pyversions/censusdis)\n\n![PyPI - Status](https://img.shields.io/pypi/status/censusdis?label=PyPI%20Status)\n![PyPI - Format](https://img.shields.io/pypi/format/censusdis?label=PyPI%20Format)\n![PyPI - Downloads](https://img.shields.io/pypi/dm/censusdis?label=PyPI%20Downloads)\n\n![GitHub last commit](https://img.shields.io/github/last-commit/censusdis/censusdis)\n[![Tests Badge](../reports/junit/tests-badge.svg)](https://censusdis.github.io/censusdis/)\n[![Coverage Badge](../reports/coverage/coverage-badge.svg)](https://censusdis.github.io/censusdis/)\n[![Documentation Status](https://readthedocs.org/projects/censusdis/badge/?version=latest)](https://censusdis.readthedocs.io/en/latest/?badge=latest)\n\n`censusdis` is a package for discovering, loading, analyzing, and computing diversity, integration, and segregation metrics to U.S. Census demographic data. \nIt is designed\n\n- to support **every dataset**, **every geography, and every year**. It's not just about ACS data through the last time the software\nwas updated and released;\n- to support **all geographies, on and off-spine**, not just states, counties, and census tracts;\n- to have **integrated mapping capabilities** that save you time and extra coding;\n- to be intuitive, Pythonic, and fast.\n\nClick any of the thumbnails below to see the notebook that generated it.\n\n[\u003cimg src=\"../docs/_static/images/sample01.png\" alt=\"Diversity in New Jersey\" height=160\u003e](../notebooks/ACS%20Demo.ipynb)\n[\u003cimg src=\"../docs/_static/images/sample02.png\" alt=\"2020 Median Income by County in Georgia\" height=160\u003e](../notebooks/Data%20With%20Geometry.ipynb)\n[\u003cimg src=\"../docs/_static/images/sample05.png\" alt=\"Nationwide Integration at the Census Tract over Block Group Level\" height=160\u003e](../notebooks/Nationwide%20Diversity%20and%20Integration.ipynb)\n[\u003cimg src=\"../docs/_static/images/sample03.png\" alt=\"White Alone Population as a Percent of County Population\" height=160\u003e](../notebooks/Seeing%20White.ipynb)\n[\u003cimg src=\"../docs/_static/images/sample06.png\" alt=\"Urban Census Tracts in Illinois\" height=160\u003e](../notebooks/Geographies%20Contained%20within%20Geographies.ipynb)\n[\u003cimg src=\"../docs/_static/images/sample07.png\" alt=\"NYC Area with Water Overlap Removed\" height=160\u003e](../notebooks/Remove%20Water.ipynb)\n[\u003cimg src=\"../docs/_static/images/sample00.png\" alt=\"Integration in SoMa Tracts\" height=160\u003e](../notebooks/SoMa%20DIS%20Demo.ipynb)\n[\u003cimg src=\"../docs/_static/images/sample04.png\" alt=\"Average Age by Public Use Microdata Area in Massachusetts\" height=160\u003e](../notebooks/PUMS%20Demo.ipynb)\n\n## Installation and First Example\n\ncensusdis can be installed with `pip`:\n\n```shell\npip install censusdis\n```\n\nEvery censusdis query needs four things:\n\n1. What data set we want to query.\n2. What vintage, or year.\n3. What variables.\n4. What geographies.\n\nHere is an example of how we can use censusdis to download data once we know\nthose four things.\n\n```python\nimport censusdis.data as ced\nfrom censusdis.datasets import ACS5\nfrom censusdis import states\n\ndf_median_income = ced.download(\n    # Data set: American Community Survey 5-Year\n    dataset=ACS5,\n    \n    # Vintage: 2022\n    vintage=2022, \n    \n    # Variable: median household income\n    download_variables=['NAME', 'B19013_001E'], \n    \n    # Geography: All counties in New Jersey.\n    state=states.NJ,\n    county='*'\n)\n```\n\nThere are many more examples in the tuturial and in the sample notebooks.\n\n## Tutorial (A Great Place to Start!)\n\nWe presented a [half-day tutorial](https://cfp.scipy.org/2024/talk/BTG9U3/) \non `censusdis` at [SciPy '24](https://www.scipy2024.scipy.org/). All the \nmaterial covered in the tutorial is available as in a github repo at\nhttps://github.com/censusdis/censusdis-tutorial-2024.\nThe tutorial consists of a series of five lessons, \neach with worked exercises, and two choices for a final project. If you \nreally want to learn the ins and outs of what `censusdis` can do, from the\nmost basic queries all the way through some relatively advanced topics, this\nis the tutorial for you.\n\n\n### An Older Tutorial\n\nFor an older tutorial that is shorter but does not include some of the newest features, \nplease see the [censusdis-tutorial](https://github.com/vengroff/censusdis-tutorial) repository.\nThis tutorial was presented at [PyData Seattle 2023](https://pydata.org/seattle2023/). If you want to try it out for yourself, the README.md\ncontains links that let you run the tutorial notebooks live on [mybinder.org](https://mybinder.org/) in your browser without needing to set up a\nlocal development environment or download or install any code.\n\n### Tutorial Video\n\nWe expect a vireo of the [SciPy '24 tutorial](https://github.com/censusdis/censusdis-tutorial-2024) to be available soon, \nhopefully by some time in August '24.\n\nA 86 minute \n[video](https://www.youtube.com/watch?v=3vyC7ON0Tvg) \nof the older tutorial as presented at \n[PyData Seattle 2023](https://pydata.org/seattle2023/)\nis also available.\n\n[![PyData Seattle Tutorial Video](https://img.youtube.com/vi/3vyC7ON0Tvg/0.jpg)](https://www.youtube.com/watch?v=3vyC7ON0Tvg)\n\n## Overview \n\n`censusdis` is a package for discovering, loading, analyzing, and computing\ndiversity, integration, and segregation metrics\nto U.S. Census demographic data. It is designed to be intuitive and Pythonic,\nbut give users access to the full collection of data and maps the US Census\npublishes via their APIs. It also avoids hard-coding metadata\nabout U.S. Census variables, such as their names, types, and\nhierarchies in groups. Instead, it queries this from the \nU.S. Census API. This allows it to operate over a large set\nof datasets and years, likely including many that don't\nexist as of time of this writing. It also integrates\ndownloading and merging the geometry of geographic \ngeometries to make plotting data and derived metrics simple\nand easy. Finally, it interacts with the `divintseg`\npackage to compute diversity and integration metrics.\n\nThe design goal of `censusdis` are discussed in more\ndetail in [design-goals.md](../design-goals.md).\n\n\u003e ### I'm not sure I get it. Show me what it can do.\n\u003e \n\u003e The [Nationwide Diversity and Integration](../notebooks/Nationwide%20Diversity%20and%20Integration.ipynb)\n\u003e notebook demonstrates how we can download, process, and \n\u003e plot a large amount of US Census demographic data quickly\n\u003e and easily to produce compelling results with just a few\n\u003e lines of code.\n\n\u003e ### I'm sold! I want to dive right in!\n\u003e \n\u003e To get straight to installing and trying out\n\u003e code hop over to our \n\u003e [Getting Started](https://censusdis.readthedocs.io/en/latest/intro.html)\n\u003e guide.\n\n`censusdis` lets you quickly and easily load US Census data and make plots like \nthis one:\n\n![Median income by block group in GA](../docs/_static/images/sample02.png)\n\nWe downloaded the data behind this plot, including\nthe geometry of all the block groups, with a\nsingle call:\n\n```python\nimport censusdis.data as ced\nfrom censusdis.states import STATE_GA\n\n# This is a census variable for median household income.\n# See https://api.census.gov/data/2020/acs/acs5/variables/B19013_001E.html\nMEDIAN_HOUSEHOLD_INCOME_VARIABLE = \"B19013_001E\"\n\ngdf_bg = ced.download(\n    \"acs/acs5\",  # The American Community Survey 5-Year Data\n    2020,\n    [\"NAME\", MEDIAN_HOUSEHOLD_INCOME_VARIABLE],\n    state=STATE_GA,\n    block_group=\"*\",\n    with_geometry=True\n)\n```\n\nSimilarly, we can download data and geographies, do a little\nanalysis on our own using familiar [Pandas](https://pandas.pydata.org/)\ndata frame operations, and plot graphs like these\n\n![Percent of population identifying as white by county](../docs/_static/images/sample03.png)\n![Integration is SoMa](../docs/_static/images/sample00.png)\n\n## Modules\n\nThe public modules that make up the `censusdis` package are\n\n| Module                | Description                                                                                                   |\n|-----------------------|:--------------------------------------------------------------------------------------------------------------|\n| `censusdis.geography` | Code for managing geography hierarchies in which census data is organized.                                    | \n| `censusdis.data`      | Code for fetching data from the US Census API, including managing datasets, groups, and variable hierarchies. |\n| `censusdis.maps`      | Code for downloading map data from the US, caching it locally, and using it to render maps.                   |\n| `censusdis.states`    | Constants defining the US States. Used by the other modules.                                                  |\n| `censusdis.counties`  | Constants defining counties in all of the US States.                                                          |\n\n## Demonstration Notebooks\n\nThere are several demonstration notebooks available to illustrate how `censusdis` can\nbe used. They are found in the \n[notebook](https://github.com/vengroff/censusdis/tree/main/notebooks) \ndirectory of the source code.\n\nThe demo notebooks include\n\n| Notebook Name                                                                                                       | Description                                                                                                                                                                          |\n|---------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [ACS Comparison Profile.ipynb](../notebooks/ACS%20Comparison%20Profile.ipynb)                                       | Load and plot American Community Survey (ACS) Comparison Profile data at the state level.                                                                                            |\n| [ACS Data Profile.ipynb](../notebooks/ACS%20Data%20Profile.ipynb)                                                   | Load and plot American Community Survey (ACS) Data Profile data at the state level.                                                                                                  |\n| [ACS Demo.ipynb](../notebooks/ACS%20Demo.ipynb)                                                                     | Load American Community Survey (ACS) Detail Table data for New Jersey and plot diversity statewide at the census block group level.                                                  |\n| [ACS Subject Table.ipynb](../notebooks/ACS%20Subject%20Table.ipynb)                                                 | Load and plot American Community Survey (ACS) Subject Table data at the state level.                                                                                                 |\n| [Block Groups in CBSAs.ipynb](../notebooks/Block%20Groups%20in%20CBSAs.ipynb)                                       | Load and spatially join on-spine and off-spine geographies and plot the results on a map.                                                                                            |\n| [Congressional Districts.ipynb](../notebooks/Congressional%20Districts.ipynb)                                       | Load congressional districts and tract-level data within them.                                                                                                                       |\n| [Data With Geometry.ipynb](../notebooks/Data%20With%20Geometry.ipynb)                                               | Load American Community Survey (ACS) data for New Jersey and plot diversity statewide at the census block group level.                                                               |\n| [Exploring Variables.ipynb](../notebooks/Exploring%20Variables.ipynb)                                               | Load metatdata on a group of variables, visualize the tree hierarchy of variables in the group, and load data from the leaves of the tree.                                           |\n| [Geographies Contained within Geographies.ipynb](../notebooks/Geographies%20Contained%20within%20Geographies.ipynb) | Demonstrate working with geograhies from different hierarchies.                                                                                                                      |\n| [Getting Started Examples.ipynb](../notebooks/Getting%20Started%20Examples.ipynb)                                   | Sample code from the [Getting Started](https://censusdis.readthedocs.io/en/latest/intro.html) guide.                                                                                 |                                                         |\n| [Nationwide Diversity and Integration.ipynb](../notebooks/Nationwide%20Diversity%20and%20Integration.ipynb)         | Load nationwide demographic data, compute diversity and integration, and plot.                                                                                                       |\n| [Map Demo.ipynb](../notebooks/Map%20Demo.ipynb)                                                                     | Demonstrate loading at plotting maps of New Jersey at different geographic granularity.                                                                                              |\n| [Map Geographies.ipynb](../notebooks/Map%20Geographies.ipynb)                                                       | Illustrates a large number of different map geogpraphies and how to load them.                                                                                                       |\n| [Population Change 2020-2021.ipynb](../notebooks/Population%20Change%202020-2021.ipynb)                             | Track the change in state population from 2020 to 2021 using ACS5 data.                                                                                                              |\n| [PUMS Demo.ipynb](../notebooks/PUMS%20Demo.ipynb)                                                                   | Load Public-Use Microdata Samples (PUMS) data for Massachusetts and plot it.                                                                                                         |\n| [Querying Available Data Sets.ipynb](../notebooks/Querying%20Available%20Data%20Sets.ipynb)                         | Query all available data sets. A starting point for moving beyond ACS.                                                                                                               |\n| [Seeing White.ipynb](../notebooks/Seeing%20White.ipynb)                                                             | Load nationwide demographic data at the county level and plot of map of the US showing the percent of the population who identify as white only (no other race) at the county level. | \n| [SoMa DIS Demo.ipynb](../notebooks/SoMa%20DIS%20Demo.ipynb)                                                         | Load race and ethnicity data for two towns in Essex County, NJ and compute diversity and integration metrics.                                                                        |\n| [Time Series School District Poverty.ipynb](../notebooks/Time%20Series%20School%20District%20Poverty.ipynb)         | Demonstrates how to work with time series datasets, which are a little different than vintaged data sets.                                                                            |\n\n\n\n## Diversity and Integration Metrics\n\nDiversity and integration metrics from the `divintseg` package are \ndemonstrated in some notebooks.\n\nFor more information on these metrics\nsee the [divintseg](https://github.com/vengroff/divintseg/) \nproject.\n\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["archiving","transforms","routes","conversion","observation","optimize","measur","compose","projection","profiles"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/297044","html_url":"https://ost.ecosyste.ms/projects/297044"}