The United States Census Bureau provides a massive amount of data about the American people, covering topics from demographics to poverty rates to educational attainment, and at geographical levels ranging from the entire country down to city blocks. As a product of the federal government, the data is free to use. But for working journalists—especially those who don't have experience with the particulars of Census data—navigating these datasets on deadline can be a challenge.
Census Reporter's goal is to make it easier for journalists to write stories using Census data. Our focus is on the American Community Survey; we want to help people understand what the survey covers and help them quickly find data from places they care about. Census Reporter received funding from the Knight News Challenge, and primary development took place from March 2013 through June 2014.
The Census Reporter website includes three primary types of pages: geographical profiles, which provide an overview of data indicators from a particular place; data comparisons, which use tabular, map and distribution formats to show information from a table across a group of geographies; and topical overviews, which document the concepts and tables the ACS uses to cover specific subject areas.
Census Reporter is an open-source project, so not only is the data free to use, so is the code. Developers in South Africa forked this repository to build Wazi, for example, a site exploring South African data. We'd love it if you'd fork this repository, too, and maybe you even have features you'd like to contribute back!
Here's what you need to know to get a local version of Census Reporter up and running. These instructions assume you're using virtualenv and virtualenvwrapper to manage your development environments.
You'll need GDAL installed. On Mac OS X, use brew install gdal or on Ubuntu use:
>> sudo apt-add-repository -y ppa:ubuntugis/ubuntugis-unstable
>> sudo apt-get update
>> sudo apt-get install libgdal1-dev
First, clone this repository to your machine and move into your new project directory:
>> git clone git@github.com:Code4SA/censusreporter.git
>> cd <your cloned repo dir>
Create the virtual environment for your local project, activate it and install the required libraries:
>> mkvirtualenv census --no-site-packages
>> workon census
>> pip install -r requirements.txt
If you've upgraded XCode on OS X Mavericks, you may well see some compilation errors here. If so, try this:
>> ARCHFLAGS=-Wno-error=unused-command-line-argument-hard-error-in-future pip install -r requirements.txt
And make sure your development environment knows the proper DJANGO_SETTINGS_MODULE by creating a postactivate script ...
>> cdvirtualenv bin
>> touch postactivate
... and then using your favorite editor to add these two lines to your new postactivate script:
export DJANGO_SETTINGS_MODULE='config.dev.settings'
echo "DJANGO_SETTINGS_MODULE set to $DJANGO_SETTINGS_MODULE"
Save and close the file. Reactivate your development environment so postactivate gets triggered:
>> deactivate
>> workon census
Setup a local Postgres database:
>> psql
create user census with password 'census';
create database census_2011 with owner census encoding 'UTF8' template template0;
Populate the database with census data:
>> cd <your cloned repo dir>
>> fab dev load_api_data
Then fire it up:
>> ./manage.py runserver
The website gets census information from tables stored in Postgres, using the logic in the censusreporter/api package.
For more infromation on how census data is stored, table formats, and importing new data, see censusreporter/api/README.md.
Geographical profile pages provide an overview of important Census (and other) data indicators for a particular place. We've divided these data points into categories: Elections, Demographics, Households, Service Delivery, Economics and Education. Each category includes a mix of figures and charts that help you understand what life is like in a community. Profiles also include comparative data, so you can consider statistics from a city, for example, in the context of the metro area and province they're in.
The Census Reporter website generates profile pages for geographies at the national and provincial levels all the way down to wards. If your browser supports geolocation, you can use your current location to easily profile any of the geographies that you're currently in.
###The profile page back end
Each profile page requires queries against a few dozen Census tables. When the Census Reporter app sees a profile request, the SouthAfricaGeographyDetailView calls a profile generator.
The profile generator at api/controller/census.py gets the appropriate census data and merges it together. It returns a Python dictionary with this processed data from the API. The SouthAfricaGeographyDetail view passes this into an enhance_api_data method to do a couple more things:
- removes extraneous comparisons, limiting data to the profile geography plus at most two parent geographies
- calculates index values, which are figures from the profile geography expressed as percentages of a parent geography's value. (These are ultimately used Madlib-style, for phrases like "a little less than the figure in Gauteng")
- calculates margin of error ratios to determine which data points should be flagged as requiring extra care
Once this is done, the final job is to use SafeString() to hand everything to the template in a format suitable for use as Javascript variables.
This pattern—using a generator script to collect and shape data from multiple tables, then storing the results as flat JSON—is something that could be repeated for new Census Reporter features. We'd like to add deeper category profiles for each of the Demographics, Economics, Families, Housing and Social sections, for example, which could be done by copying and modifying the geo_profile method in profile.py.
###The profile page front end
TODO: adapt for wazimap.co.za
The skeleton of the profile page you see on the Census Reporter website is created by a Django template. The map is filled in by one Javascript library: tilelayer.js, and the charts filled in by another: charts.js.
####Profile map
TODO: adapt for wazimap.co.za
The profile page uses Javascript to call the "geography metadata" endpoint, using the geom=true argument to get boundary coordinates for the chosen place. A tile layer then adds shapes of nearby geographies at the same summary level, which can be used to navigate to their corresponding profile pages. The map will also do some smart centering to account for the box full of place metadata in that part of the page.
####Profile charts
The Django template for the profile page creates empty slots for each chart, which are filled on load by charts.js. These placeholders look something like:
<div class="column-half" id="chart-histogram-demographics-age-distribution_by_decade-total" data-stat-type="scaled-percentage" data-chart-title="Population by age range"></div>
The column-* class isn't really important here; that's just a structural setting that gives the block an appropriate amount of width that can be governed with media queries. What we really care about are the id and data-* attribute values. The data attributes provide a place to pass optional information into the chart constructor, and the id value tells the constructor what type of chart to draw and which data to use.
At the bottom of the profile page, we trigger all the charts at once. Profile data is assigned to a Javascript variable:
profileData = {{ profile_data_json }};
And we grab all the chart placeholders with:
chartContainers = $('[id^=chart-]')
The makeCharts() function then loops through those containers, empties each one of any contents, and builds the variables required for a chart:
chartDataKey = chartID.replace('chart-','').replace('alt-','')
chartDataID = chartDataKey.split('-') #temporary variable
chartType = gracefulType(chartDataID[0])
chartData = profileData[chartDataID[1]]
geographyData = profileData['geography']
#####Required variables
chartDataKey: This tells us everything we need to know to recreate this particular chart from a given set of profile data, and we'll use it to populate embed code if a user asks for it. In the example above, this value would be histogram-demographics-age-distribution_by_decade-total.
chartType: The first bit of our chartDataKey, in this case histogram, represents the type of chart we want. The charts.js library currently supports:
- pie
- column
- grouped_column
- histogram
- bar
- grouped_bar
You'll note that we actually pass this value through a function called gracefulType, which allows us to change chart types based on screen width. More on that in a moment.
chartData: The rest of our chartDataKey provides the path to the data that should fill this chart. We start by assigning this variable a top-level item from profileData, in this case demographics. Then we use a loop to drill down based on the rest of our keys: demographics > age > distribution_by_decade > total. That's where we'll find the data to pass into the chart constructor.
geographyData: We also reach into profileData for names and summary levels of the chosen place and its parent geographies.
#####Optional variables
Placeholder containers can also use data attributes to pass optional information to the chart constructor. Our example container uses data-stat-type and data-chart-title:
<div class="column-half" id="chart-histogram-demographics-age-distribution_by_decade-total" data-stat-type="scaled-percentage" data-chart-title="Population by age range"></div>
The makeCharts() function will recognize:
data-chart-title: A title to place above the chart elements, passed to the chart constructor as chartChartTitle. Defaults to null, although most charts on Census Reporter's profile pages do assign a value here.
data-initial-sort: Used only by pie charts. Determines which category to highlight when the chart is initialized. A placeholder container with data-initial-sort="-value" will display the highest data value in the chart on load. Otherwise the first value in the chart will serve as the default state.
data-stat-type: Provides formatting hints for the chart's language and display. Standard chart behavior may be overriden with these values:
- percentage: Adds a "%" character after figures in the chart. Sets chart domain to 0-100. Uses "rate" in comparison sentences.
- scaled-percentage: Does the same things as "percentage," but also scales the chart so that the highest category value takes up the full vertical space available.
- dollar: Adds a "$" character before figures in the chart. Uses "amount" in comparison sentences.
data-qualifier: Adds a trailing line below the chart, prepended with an "*" character. This is useful when charts require a little extra context. For example, the profile page's "Race & Ethnicity" column chart adds this explanation: "Hispanic includes respondents of any race. Other categories are non-Hispanic."
####Responsive design
The charts on Census Reporter's profile pages are responsive to browser width. They use a combination of CSS media queries and Javascript to accommodate various screen sizes. Media queries take care of changes like column widths and legend placements, and they help arrange the interactive hovercards that provide extra data when a user mouses over or taps a chart element.
Javascript comes into play so we can completely change chart types that won't read well at certain widths. There are a couple functions at the bottom of the profile template that make this happen:
lazyRedrawCharts: This function updates window.browserWidth and window.browserHeight variables whenever a page is resized, then triggers makeCharts() to redraw any charts on the page according to their new available widths. (This is why makeCharts() empties out the contents of each container first. So they can be filled again, maybe even with a different chart format.) Realistically, this most likely gets triggered by a user turning a phone or tablet from portrait to landscape orientation, but just in case, the redraw is debounced to avoid a crazy number of events firing off.
var lazyRedrawCharts = _.debounce(function() {
window.browserWidth = document.documentElement.clientWidth;
window.browserHeight = document.documentElement.clientHeight;
makeCharts();
}, 50);
$(window).resize(lazyRedrawCharts);
gracefulType: This function checks window.browserWidth, and if it's too narrow to reasonably display a column chart, flips it to a bar chart. This is called by each chart inside the makeCharts() function, which is triggered on page load as well as resize thanks to lazyRedrawCharts.
var gracefulType = function(chartType) {
if (browserWidth <= 640) {
if (chartType == 'column' || chartType == 'histogram') {
return 'bar'
} else if (chartType == 'grouped_column') {
return 'grouped_bar'
}
}
return chartType
}
Between media queries and this Javascript, charts should be useful on phones as much as desktops.
TODO: adapt for wazimap.co.za (not currently supported on wazimap)
Tabular view, map view, distribution view. Docs soon.
The charts on censusreporter are made available for embedding on 3rd party sites through the use of iframes. These embedded charts rely on static content and json data files that are hosted in an AWS S3 bucket.
The S3 bucket contains many of the static files found in apps/census/static, so the same
rendering logic is used for the site's graphs and the embedded graphs. The data files that are
needed for rendering embedded graphs are automatically pushed to the S3 bucket each time a
new profile is accessed on the censusreporter site.
Censusreporter is designed to be deployed on Heroku or a Heroku-like environment like Dokku. Deployments are done simply by pushing to your remote branch:
git push dokku
Follow the instructions to setup either a new Dokku host or a new Heroku app. You'll also need a PostgreSQL database.
Then set some settings, filling in the details where necessary:
dokku config:set DJANGO_SETTINGS_MODULE=config.prod.settings \
PYTHONPATH=/app/censusreporter:/app/censusreporter/apps
dokku config:set DATABASE_URL=postgres://username:password@host/databaseFinally, push to the remote branch:
git push dokku