Find facts Populations and dollar figures are broken down by category: Demographics, Economics, Families, Housing and Social. Visualize Our library of charts gives you insight into data from the places you research. Look for them on profile pages. You can even embed the charts on your own site. Get context Pre-computed statistics are presented alongside each data point, so you can see how each place fits into a larger context. Explore Census data is massive, and sometimes it's hard to find the table you're looking for. Search by table and column keywords. We want to help you tell great stories. Maps and distribution charts help uncover what's interesting, so you can take it from there. Download From any comparison, save the data you're viewing in CSV, Excel or a variety of geographic data formats. Census Reporter is an independent project to make it easier for journalists to write stories using information from the U. S. Census bureau. Place profiles and comparison pages provide a friendly interface for navigating data, including visualizations for a more useful first look.
Census Data Analysis and Mapping with Python - YouTube
Mapping Census Data with tidycensus and leaflet by Kier O Neil Last updated almost 4 years ago
Census Data Mapper The Census Data Mapper is a web mapping application intended to provide users with a simple interface to view, save and print county-based demographic maps of the United States. The data are from the 2010 Census. Please click on the image or link below to launch the application. Launch the Census Data Mapper Application Requirements: To view this application, you will need the Adobe Flash Player available for free from Adobe. To save and print a map, you will need the Adobe® Reader® available for free from Adobe. To save tabular data, you will need Microsoft Excel or the Microsoft® Excel® Viewer available for free from Microsoft®. Source: U. S. Census Bureau Geography Division Created: June 20, 2012 Last Revised: July 10, 2015
Both strategies involve an extra download. A word on map projections Map of Seattle Census Blocks turned ~15 degrees clockwise I noticed that the Census Block Shapefile is set to a different projection that the Census Places Shapes. You might choose to reorient your map to match the Census Place shape, the other data you're using (eg. from the city), or not. In this case, I'll reorient to the view I'm more accustomed to. You can check the orientation / crs of a file, use geo_object or use the convenient warning message you'll get if you use the Shapely geometric comparisons (ie. contains, touches, etc. ) To set the projection: _crs("EPSG:4269") Coloring the map based on a feature For a basic choropleth, add a column argument to your plot call. You can read more about choropleths on GeoPandas. Or check out my code to create the map with a legend, and grey background to fill in any gaps: # to make nice looking legends from es_grid1 import make_axes_locatable # create the plot for sizing fig, ax = bplots(figsize=(20, 20)) # lay down a background map for areas with no people (ax=ax, color='grey', alpha=.
Add to your applications and Story Maps You can easily use web maps calling to these layers within your dashboards, applications, Story Maps, and more. The example below uses the " ACS Youth School and Work Activity Variables – Centroids " layer within custom-made web maps to tell a story about teen employment within the United States. Add context to the pop-ups in your existing maps Using the new Feature Set capability within the Arcade scripting language you can query data from Living Atlas layers to add context to your own maps. Intersect your data on the fly or query data from the ACS layers using a common FIPS code from your data. This GeoNet post introduces how to use this technique. Use within your custom JavaScript applications Because these ACS layers are hosted feature layers, they are easy to work with in JavaScript applications and scale nicely when your app is used more and more. Query, customize, and perform client-side analytics to enhance any map. This example was shown at the 2019 Developer's Summit Plenary, and uses client-side queries to provide on-the-fly facts about unemployment within the United States as you zoom into the map.
How to access and map population data in Python Photo by Ryan Wilson on Unsplash Today I'm taking a look at the racial composition of Seattle, according to the 2010 Census. Towards this end, I'll use Integrated Public Use Microdata Series ( IPUMS) National Historical Geographic Information System (NHGIS). You can also use, which I found to be much slower (so much pinwheeling! ) than the IPUMS-NHGIS system. Note: scroll to the bottom for a glossary of terms. In order to map census data, we're looking for both the GIS shapefiles at the level of interest, as well as the information tables at the matching levels. From IPUMS: "IPUMS provides census and survey data from around the world integrated across time and space. IPUMS integration and documentation makes it easy to study change, conduct comparative research, merge information across data types, and analyze individuals within family and community contexts. Data and services available free of charge. " Check ou t all the databases here.