The video above is the trailer for my new online class: Mapmaking for Journalists.

It starts Monday, July 11, 2022 and runs for four weeks. It's all online, and you can go at your own pace. I'll be in the class forums and even host a couple of (optional) live chats.

Along the way, you'll learn how to make maps using Datawrapper, Mapbox, and Mapshaper.

No prior coding experience is needed, and you get to keep all of the code I share with you.

It's run by the Knight Center for Journalism in the Americas at the University of Texas at Austin. The cost is $95, and you can register at journalismcourses.org. 

Hope you'll join me!

Note: This post was originally published April 29, 2011, and updated in June 2020. In February 2022, I updated it again using 2020 Census data. 

Anyone doing population analysis by NYC police precinct might find this post helpful, especially if you're interested in race and/or ethnicity analysis by precinct.

Back in 2011, I wanted to compare the racial and ethnic breakdown of low-level marijuana arrests — reported by police precinct — with that of the general population. The population data, of course, is available from the US Census, but it's not provided by police precincts, which also don't follow any major census boundaries like census tracts. Instead, they generally follow streets and shorelines. Fortunately, census blocks (which in New York, are often just city blocks) also follow streets and shorelines.

So I used US Census block maps and precinct maps from the city to figure out which blocks are in which precincts. Since population data is available at the block level, that data can then be aggregated into precincts.

In this, the third version of this post, I've updated the counts now that the 2020 population data is available.

The 2020 data

• nyc_precinct_2020pop.csv is the 2020 Census population, race, and ethnicity (Hispanic/non-Hispanic) data by NYPD police precinct. The column headers from the US Census are a little cryptic, but you can translate them using the P1 table metadata file and the P2 table metadata file.

• nyc_block_precinct_2020pop.csv — every populated block in NYC is identified by its ID (called "GEOID20"), is matched to the police precinct it sits within, and contains the block's race/ethnicity information. Use the same metadata tables to translate the column headers. Also be sure to read about the caveats below.

• nyc_precincts.geojson depicts the geographic boundaries of the NYPD precincts I used for the files above, as they existed in February 2022. As of this post, the information on the NYC Open Data portal indicates it was last updated on Nov 24, 2021.

Caveats for the 2020 data

The biggest caveat is that the US Census has introduced data fuzziness, or "noise," to make it difficult to identify individuals based on census data. This fuzziness is more pronounced at smaller geographies — the smallest being census blocks, which I've used for these calculations. Hansi Lo Wang did a great primer on these data protections for NPR, and the US Census Bureau has put out a lot of material on how it uses "differential privacy."

Read more »

I've been both awed and terrified by the transmissibility of Omicron and the speed at which it's spread. As the case curves hockey-sticked upward and the maps all turned red, I thought it'd be interesting to visualize the spread of this new twist on the coronavirus.

So the other day, while doing some work mapping Covid-19 data by US counties, I realized it wouldn't take much to generate a map for each day of the pandemic ... and make those maps into a movie.

It almost seems like cheating to use a work project as one of my "Make Every Week" projects, but I'm lucky to have a job where creative tinkering is celebrated. When I shared a tinker-made movie of six months of case data with colleagues Kaeti Hinck and Sean O'Key, they thought it would make a good data feature for CNN.

While truly a horrible topic — nearly every county is now reporting more than 100 cases per 100,000 people — the process of turning that case data into a movie was a worthy project. I learned a lot, and I did it almost entirely from the command line (the text-only interface that is my Mac's "Terminal" program).

Read more »

Do you want to ...

  Inform the citizens of New York?

  Help people understand their world?

  Root out corruption?

  Make a mark on society?

  Craft beautiful online projects and visualizations?

  ( Like this diversity map, this stop & frisk project and this election tracker? )

WNYC is growing our Data News Team to make high-impact visualizations and projects, and to help WNYC reporters and producers present the facts, expose corruption and explain our world. We've been pioneers in the field of crowdsourcing, data journalism and mapping -- even winning some prestigious awards for our work.

Now we're kicking it up a notch. Like to join us? 

What we have:

• An award-wining staff of reporters and producers
• A committed, innovative digital staff
• A mission to conduct journalism in the public interest
• Millions of engaged, passionate and active listeners and readers

What you have:

• A passion for news
• An attention to detail, a respect for fairness and a hatred of inaccuracy
• A user-centered approach to exploring information
• An appreciation for clean lines, clear stories and use of white space
• A genuine and friendly disposition, and an honest spirit of collaboration
• A bias toward sharing what you know, and helping others build on it

What you'll do:

• Huddle with reporters to figure out how we might help their stories with data, design and web technology
• Work as a team to turn ideas into realities in days or weeks, tops
• Learn from and build on successes and mistakes along the way
• Have your work consumed online and talked about on air to millions of New Yorkers

Head over to our official aplication for Interaction Designer and tell us all about you.

The Guardian pushed the limits of election-night data display this week with a relief map of the Florida primary vote. 

They didn't push far enough.

As promised: Live election results in True 3-D.

(To avoid blog lag, I've put the live version here.)

You need a current browser to see it. Recent versions of Chrome and Firefox work. Safari does, too, if you nudge it.

With any luck, the counties shall grow as the vote rolls in tonight.

For those interested, I built it in Processing and use Processing.js to put it on the web. You're welcome to embed it if you wish. Just drop me a note or comment that you did.

UPDATE: My data-fetching code is a little wonky. Refresh the page to ensure the latest results!

UPDATE 2: I actually don't believe this is the best way to present numeric data. Representing numeric scale with a 3D drawing on a 2D surface is exceptionally tricky and should probably be avoided. Also, there are no rollovers or other clarifying information -- like county names and vote counts.

That said, I like the idea that some data sets might be worth spinning, touching and flying through. So maybe this is my first step in that direction.

Plus, it was fun.

UPDATE 3: By request, here is the Processing sketch upon which this was built. 

For the second time -- the first being Iowa -- WNYC's It's A Free Country has a map that uses free, live election data. 

And that means you can have it, too.

Just use the embed link at the bottom of the map.

And if you want to make your own, check out some tips in my next post.

UPDATED in two key spots below.

Election geeks, you are in luck. For the second time, Google plans to offer free, real-time election results, allowing anyone to tinker and play with hard-to-get voting numbers.

It's for the Nevada Republican caucuses this Saturday, February 4, and even if you have no connection to Nevada, it's a chance to experiment with live results like the Big Guys. Make a map. Mash up some data. Have fun.

The first time Google did this, we made this Iowa caucuses results map at WNYC, mashing up Patchwork Nation community types with the live vote tally. And since we've been through it once, I've got some tips and tricks for making your own project.

My only request: Send me a link to whatever you make. I'd love to see it.

Setting the Fusion Table

Updated: The Google folks are providing live tallies from the Nevada GOP in two Fusion Tables -- one by county and one by precinct -- which will be updated with new data throughout the evening. 

This means means you get all of the functionality of those tables, including simple charts and cool maps. Check out these posts to get started with Fusion Tables, if you're not already familiar.

Urge to Merge

My favorite part of Fusion Tables is that you can easily merge (or join, in SQL-speak) two separate tables of data. In this case, you'll be able to merge any data organized by Nevada's 17 counties (one's actually an independent city). Unemployment figures, Social Security recipients and any U.S. Census designation you can think of are just a few of the possibilities.

Updated 11:39 a.m. 2/2/2012: This section originally talked about merging on the county's unique FIPS code -- which turns out to be tricky, since the results table doesn't have those codes. But if your data has the Nevada county names, you can merge using the name as the key (provided they are identical lists in both tables). Or you can add the county names to your data by adding a column and entering them by hand.

For reference, or to map the shapes of the Nevada counties, you can use this table I built merging data from the U.S. Census (which calls the FIPS codes "GEOID10") and the live election data.

No matter how you do it, once merged, you'll end up with a larger table containing all of your mashup data -- unemployment, number of children, etc. -- lined up next to the live vote data. Even though it's a new table, it'll update in real time with the underlying vote table.

Welcome, Json

If you're a JavaScripter, it is super easy to get the data you want from Google's results table, or a merged table you built with it.

First, construct a query url according to the Google Fusion Tables documentation. This can be a little tricky, but with some tinkering you can make it work. Be sure to encode commas, greater-than signs and other symbols. Here's a nifty URL encoder if you need to convert all or part of the URL. Also, surround with single-quotes any column name containing dashes, such as 'VoteCount-Paul'.

For a simple example, take a peek at this "shoes" table. Then try this URL:

https://www.google.com/fusiontables/api/query?
sql=SELECT+Product%2C+Inventory+FROM+274409&jsonCallback=foo

A little decryption here: The + signs are spaces, and the %2C codes are commas. The table number we're looking at is 274409. So the syntax is "SELECT Product, Inventory FROM 274409." Append &jsonCallback=foo and you get back JSON. If you're using a jQuery AJAX call, as you'll see below, make it &jsonCallback=?

You should get a text file that looks like this:

foo({"table":{"cols":["Product","Inventory"],"rows":[["Amber Bead",1.251500558E9],["Black Shoes",356],["White Shoes",100]]}})

Voila! JSON.

To get the statewide total for Iowa, I made a crazylong URL that requests sums of the columns I wanted.

Pro-tip: If you try sorting the data within Fusion Tables using Options->Filter or Options->Aggregate the "query" you're using appears above the results. Use that to help form the URL after the query?sql= part.

Inside the JavaScript map application, I used jQuery's $.getJSON() function to hit that URL and load in the data, and setTimeout() to do it every two minutes. You can see and use the code here.

Try and Learn

If you've ever dreamed of making your own election-night results map, or just like the thrill of a new challenge, don't let this opportunity pass you by. It's lucky that we get a chance to play with free, live and well-structured voting information. And no matter what you learn in the process, I bet it'll be valuable down the road.

Maybe even in November.

As always, don't hesitate to contact me -- or post a comment -- with questions, clarifications and ideas. And if you're inspired to make something for Nevada's primary, definitely drop me a note and a link!

[ Map detail: Patchwork Nation - Votes for Barak Obama in 2008, by county ]

This post is for journalists who use (or would like to use) election data from the Associated Press -- which is a paid service the AP provides. If that describes you, read on!

When Google gave away free, live election data for the Iowa Caucuses, something struck me right away: It was easy.

Data provided by the Associated Press, which drives almost every election site you've ever seen, is notoriously tricky to manage -- a statement I'm confident making based on talks with many election-night veterans and on my own experience.

But Google's results were posted in a public Google Fusion Table, which is basically a spreadsheet on steroids. That meant I could get the data I wanted simply by constructing the correct URL. Votes by county, sorted by county? No problem. Candidate totals for the entire state? Sure. Votes mashed with other data I had? Yup. Formatted in JSON? Bring it.

Instantly. Easily.

(Here are the URLs I used above, and here's the documentation from Google on how to construct them. Hard-to-find tip: Append &jsonCallback=anything to get the json. And if you're using jQuery AJAX calls, make it &jsonCallback=?)

A week later, for the New Hampshire Primary, there were no free Google data. So I made an AP data-fetcher-and-wrangler based on code by Al Shaw. Through no fault of Al's code, my adaptation was slow, complicated and crashed every couple of hours. It worked, but just barely.

Next up was South Carolina, and I was determined to make AP's data friendlier by putting in a Google Fusion Table.

And it worked.

How I did it

In the interest of time and clarity -- and to spark discussion before the primaries are over (or irrelevant) -- I'm leaving out a bunch of the nitpicky details. If you're an AP Elections subscriber and want to try this, contact me at john (at) johnkeefe.net. I'll help you any way I can.

AP provides data in several formats, including a "flat file," which basically is a huge, semicolon-delimited spreadsheet. Each row represents a county, and each column the latest stats for that county, such as precincts reporting and each candidate's total votes.

The flat file doesn't have column headers, though. So I first uploaded AP's South Carolina test table to Google Spreadsheets and added the column names I needed.

I then imported the spreadsheet into a non-public Google Fusion Table.

For election night, I set up a script on my computer that does the following steps every two minutes:

1. Logs into AP's servers via FTP and downloads the flat file.

2. Deletes the data from the Google Fusion Table I made earlier and uploads the entire flat file anew. This is accomplished with a little Python program written by the brilliant (and patient) Kathryn Hurley, of the Google Fusion Tables team. I've posted it here with her permission. I don't know Python, but didn't need to. I just needed to make sure the list of columns in the data_import.py exactly matched the columns in my table. So I cut-and-pasted them from the Google spreadsheet. The script executes the command:

python data_import.py [google account username] [flat file filepath] [fusion table id]

3. Next, it hits the Fusion Table with a simple URL request formatted to return the data I want as JSON. This is the URL I used for getting the county totals.

4. Then it sends that JSON as a file, via FTP, to a subdirectory of my map application on WNYC's servers.

Once a minute, the election map running in the user's browser looks at that data file to get the latest info.

In this way, I completely avoided the need to build and maintain a database. I know there are great database folks out there, but I'm not one of them. The Fusion Table became my database.

Technically, I could skip steps 3 and 4 by simply pointing my map application at the Fusion Table to get the data it needs. That's what I did for Iowa, using the free Google data. But the table would be publicly visisble on Google's servers ... and my reading of the AP contract, understandably, doesn't allow that.

I strongly believe that the easier AP's data is to use, the more budding journocoders will make new election-night interactives. And if we can work together to do that, let's. For me, this method was a lot easier than anything else I had tried before.

A final note: If you're a Python-savvy programmer, be sure to check out what the LA Times has shared to make life easier, too. It's pretty slick.

If you need more proof that it's valuable for journalist-programmers to show their work, here's some: WNYC's Live New Jersey Election Map.

Exactly one week after Albert Sun of the Wall Street Journal New York Times shared some of his work, we made this:

(Map isn't embeddable for licensing reasons; the live version is here.)

Here's what happened.

Last month I went to a Hacks/Hackers NYC meetup about mapping. There, Albert showed his WSJ Census Map Maker project and a map I had admired that has dynamic mouse-overs without using Flash. At one point, he showed his project's code repository and welcomed us to use and build on it.

The next day, I downloaded the code and tried to make a rough version of Albert's map, but using the shapes of New Jersey legislative disricts (downladed from the US Census, stored in this Fusion Table, which generates this KML file). After a little tinkering -- which includes a fix I've described in the comments below -- I managed to build one that works. I sent that to stellar coder Jonathan Soma, of Balance Media, who works with me to build interactives for WNYC.

I also reached out to Al Shaw, of ProPublica, who I knew (from another Hacks/Hackers Meetup) had wrestled with live Associated Press election data for Talking Points Memo. He had some great tips, which I passed along to Soma, too.

Also on the case were Balance's Kate Reyes and Adda Birnir, who crafted the map's design and user experience -- a particularly tricky task because each district elects one person for state senate and two people for state assembly.

A week later, as the results rolled in, WNYC's map was live and rockin' -- listing real-time returns for each district, and changing colors when races were called.

In the process, Soma built on Albert's work, and those modifications are now a part of the code base (see Github commits here and here).

And if you need proof that such work is valuable, the map was WNYC's No. 6 traffic-getter for the month -- despite the fact it was truly useful for about 4 hours late on the evening of an off-year election.

One of many redistricting experiments we're working on looks at the effort by some community groups to carve out districts particular to their community.

So we gave it a whirl.

There are many ways to wrestle with this data -- and there is much wrestling yet to come. But by ranking and repeatedly mapping the Asian populations by census tract, we were able to come up with some maps that actually satisfy some of the contraints (except for the one that says you can't draw a district based on race!) For more info, click the "Deeper Data Details" link.

WNYC's Colby Hamilton inspired this map, and has a great post to go with it.

Mostly I worked in Google Spreadsheets and Google Fusion tables, using data from the great census.ire.org site.

I had hoped to create a single shapefile of my new district, but joining all of those census tracts kept choking my computer (and QGIS). So you're actually seeing a bunch of tracts without borders. I did use QGIS to rework some of the shapes so they cross two parks -- allowing me to make a contiguous district.

UPDATE: Here is the list of census tracts I used. And if you're poking around in the code, don't rely on the data in the experiment's fusion table; I mucked with it a lot.The original, intact tract data is here. And the Congressional district map of New York is valid for the 111th Congress.

Random thing I learned: Did you know QGIS can export shapefiles into KML? I didn't. Not used here, but good to know.