Agenda 8/20; Assignments 8/25


  1. Last Data Stories/ Flowing Data/ Source
  2. Discus final project details
    1. Tagging
    2. Splash image
    3. How presentations will work
  3. Go over how addresses work with Mapbox map
    1. Use this site for geocoding:
  4. Create Mapbox map using address points – hand in
  5. Go over text readings
    1. Word clouds: Case for avoiding them –
    2. Intro to “text mining” –
  6. Explore text tools:


  1. Based on what you hand in today, you will hear back from me with both edits, and comments on how everything is displaying on WordPress over the weekend, hopefully Saturday, but possibly early Sunday. Content must be in WordPress by 6pm on Monday, so I can get back to you on any display issues Monday night.
    1. Text and embedded visualizations all published, after final approval by me, on Medill DC site. All stories should have a cover image selected with a strong visual, and your story should be tagged with the data_projects topic.
    2. Memo as outlined in syllabus describing your decisions
    3. Be prepared to give a 5-10 minute presentation describing your work and decisions, as outlined in the syllabus
    4. Second critique should be handed in, if it isn’t already.
    5. Congrats!

Agenda 8/13; Assignments 8/20

Agenda 8/13

  1. Data stories
  2. Flowing Data/Source review
  3. Go over readings
  4. Make choropleth map with shapes – make sure QGIS is downloaded
    1. Download Tilemill
    2. Find shapes to match up – find US states here
    3. Confirm columns match
    4. Merge shapefile data with your original csv, save, so we can refer back to it in Tilemill
    5. Create Mapbox account
    6. Get Tilemill/hook up account –
      1. If not working, try this
    7. Use Tilemill to load shapes
    8. Customize colors
    9. Customize popup
    10. Upload
      1. Upload map from Tilemill
      2. Go to data section on mapbox site
      3. Click to get details
      4. Create new project
      5. Add title/description
      6. Send Michelle share link
  5. Make point map with addresses
    1. Format spreadsheet
    2. Geocode addresses, using Geocodio
    3. Load CSV into Tilemill
    4. Color (adjust points conditionally using marker-width, marker-color attributes)
    5. Popups
    6. Discuss styling of background
    7. Follow Upload process as explained above

Assignments 8/20

  1. Complete rough draft of project – text and visualization – must be handed in by next class
  2. Hand in two completed Mapbox maps, which we started in class
  3. Read:

Final Project Details – Summer 2015

  • The final project is 30% of your final grade.
  • The final project includes a text story, interactive visualization using techniques we’ve learned in class, a memo explaining the choices behind the final project and an oral presentation discussing your work.
  • On Thurs., Aug. 20, I am expecting you to have work you are happy with turned in as a rough draft for both the text and visual components of your story, based on what we’ve discussed in individual meetings. The memos explaining your work are NOT due at this point. I am not expecting anyone to have edited the story by this point.
  • By the last class, Tues. Aug. 25, you will have received edits from me by Aug. 22 (Sun). Those should be implemented, your entire project should be uploaded to the WordPress site, and have gone through a final review edit with Michelle. These projects will be uploaded into the normal system, but you will have to check a special category for our class, so that all of this class’ stories show up by clicking on one tab on the website. By final presentations, these stories should all be live and final on the site. By 6pm on Aug. 25, I will expect to have a copy of your memo detailing your work in my email, and you will present your work — that presentation is graded as well. After your presentation, be prepared for me or your classmates to follow up with questions.
  • Also, on Tues., Aug. 25 (our last class), our second critique of a professional data visualization or story is due.
  • The grading breakdown for the project is as follows:
    • Quality of visuals (20%)
      Are your visuals easy to understand? Are they interesting and enlightening? The visuals should be professional and polished.
    • News value (20%)
      Is your story relevant to your beat? Is it an original story idea? This is also where you will score points on good reporting and writing that complement and explain the visuals.
    • Text story (20%)
      Storytelling using words, that make good use of the data you have found, and analyzing it using techniques you learned in class to back up your story. Should have strong narrative throughout the piece, and make use of at least 2 human sources.
    • Appropriate use of visuals (15%)
      Is it a story that is strengthened by your choice of visuals? Did you choose the right visuals to tell the story?
    • Design (10%)
      Does your story have appropriate fonts, colors, alignment and hierarchy? Is there a clear sense of order on the page?
    • Presentation (10%)
      On the last day of class, you will be expected to give a 5-10 minute presentation to the rest of the class on why you chose your topic, how you found/cleaned your data, how you turned it into a story and why you made the visual storytelling decisions that you did. Let the memo you need to write (details below) serve as a guide. Presentation should show what you learned, show the reasoning behind your decisions, and be clear enough that others can learn from the lessons you learned.
    • Memo (5%)
      • A 1-3 page memo detailing why you did the following:
  1. Picked the story you did. What is interesting or newsworthy about it?
  2. Which columns of data did you use for the text components? Which for the interactive? Why?
  3. What human sources did you use? What category do they fall into (expert, person on the street, etc?) Why did you pick that category and that specific person? Is there another “side” of the story you would have liked to cover, or made sure to pay particular attention to?
  4. What techniques did you use for your analysis? Sorting/filtering/grouping? What questions did your data help you to answer? Did those answers surprise you?
  5. What story form did you use for the visual components of your story? What made you decide to use that type of chart or visualization?
  6. What colors did you use in your visualization? Do they reflect sequential, diverging or categorical data? Why did you choose those types of colors?
  7. Defend choices for your axes, if you have any charts. What are the minimum and maximum numbers on your scale? Do you feel they paint a complete picture of the story? Are your axes labeled? If so, what choices are behind those names? If not, why aren’t they labeled?
  8. What shapes did you use to mark different points in your visualization (bars, lines, map markers, etc.? Why?
  9. What other customization did you add to your interactive component? What were your decisions behind making those choices?
  10. What decisions did you make about integrating the text and visual components of your story? Why?
  11. What do you hope a user gains by reading/interacting with your story? What should he/she learn?
  12. What have you learned, from the content and the experience of putting this together, that you hope to apply to your future work?

Agenda 8/6; Assignments 8/13

Agenda 8/6

  1. Review data stories spreadsheet
  2. Review Flowing Data/Source blogs
  3. Go over readings for this week:
    1. Data viz tips –
    2. Data art vs. data visualization –
  4. Discuss final project requirements
    1. Examples
    2. Detailed list here
  5. Discuss Tableau – when is it a better alternative to DataWrapper?
  6. How do I decide what to visualize?
  7. How and when do I combine chart types to tell a better story?
  8. What is the role of chart types when integrated with a text story?
  9. More in-depth look at other types of Tableau charts:
  10. Basic mapping introduction
  11. Classwork
    1. Make a Tableau chart that isn’t a bar, line or map – play with the alternatives (ex: treemap, bubble, etc).
    2. Write a super short story (less than 500 words) about your findings, and write around the graphic in the way we discussed. You can include more than one chart if you want.

Assignments 8/13

  1. Read these posts:
    1. Ethics of privacy in data journalism –
    2. When Maps Shouldn’t Be Maps –
  2. Bring in two data sets to map – send both to Michelle by NOON on Thurs. 8/13:
    1. One should feature specific addresses/locations, or columns for latitude and longitude (for a point map)
    2. One should feature information that features numbers categorized by either specific countries or states (for a choropleth map)
      1. Make sure full names or abbreviations are used – no extra spaces or weird casing
      2. Let Michelle know if your data is for a unit besides counties, states or countries
    3. Be sure all data has headers for all columns
  3. Install QGIS before class – there are four parts – three things to install that it depends on. Go through installation process in order.
    1. GDAL
    2. NumPy
    3. MatPlotLib
    4. QGIS itself – finally!

Agenda 7/30; Assignments 8/6

Agenda 7/30

  1. Review data stories in spreadsheet
  2. Go over readings from Tuesday
    1. Role of visualization in finding story in data –
    2. Directory of visualization types –
    3. Visual math mistakes –
    4. Stacked area chart vs. line chart –
  3. Basics of Tableau/how different from DataWrapper
    1. Download Tableau
  4. Demo exercise: Treemap across time
    1. Resource for changing years
    2. Dataset
    3. Sample workbook
  5. Classwork/Individual memo review:
    1. I’ll meet with each of you individually outside the classroom. While I’m doing that, please complete the following:
      1. Use Tableau to make a chart based off of a data set of your choice, using rules we’ve set out in previous classes about careful color choices, axis labeling, etc. Send me the completed chart.
      2. Dip your toe into mapping by following this tutorial and send me the result:
        1. (You may encounter some bits you can’t do, in fact you will, when this happens, note what steps caused you problems, and what the issues were.)

Assignments 8/6

  1. Read:
    1. Data viz tips –
    2. Data art vs. data visualization –
  2. Hand in complete memo describing your story, using following guidelines. You should have touched on some of these in your initial pitch, but please incorporate the feedback I send you over the weekend.
    1. What is the overall topic of your story?
    2. Why is this story important?
    3. What benefit does structured data bring to this story? What can numbers tell you that people cannot?
    4. Ideas of at least three people-sources (types of people, if not specific names) who you can interview for your story (you will be required to have three sources besides the data in your final project as well. If these don’t pan out, that’s fine, but start thinking about it now.
    5. Three ideas of what a reader will learn from your story, and how it will impact them.
    6. What non-data, non-human interview research work you need to do to flesh out your idea. I imagine more will come up as you go, but explain where you plan to start.
    7. Another data source that would help that you wish you had, which would bring better context to your story.

Agenda 7/28; Assignments 7/30

Agenda 7/28:

  1. Go over spreadsheet data stories
  2. Review Flowing Data/Source for this week
  3. Review articles we read
    1. Why Data Viz Matters –
    2. Principles of viz design –
    3. History of viz –
  4. Importance of white space –

  5. Visual hierarchy –
  6. Colorbrewer –
  7. Bar graph or line graph –
  8. Classwork
    1. Create account on DataWrapper –
    2. Make practice bar graph together
    3. Make practice line graph together
    4. Use your own data set to do the following:
      1. Pick one trend from the data set you’ve been working with (can be from last week, or another you are playing with)
      2. Is it a bar or line graph?
      3. Make it in Datawrapper following ideas we’ve talked about
      4. Think about how chart will be displayed, and mock up the layout of the graphic in an editing program on the computer (Photoshop, etc), or draw it on a piece of paper. Hand in chart by taking a screenshot (either Command-Shift 4, or go to Publish tab, print to PDF and send me PDF).
      5. Write memo (at least 500 words) commenting on:
        1. Chart
          1. why you used a certain chart type
          2. color
          3. white space
          4. axis labels
        2. Overall layout
          1. What information you wanted to include
          2. Why you placed it where you did
          3. How you designated what info is most important

Chart, overall layout and memo, you can finish either in class, or at home, for next week.

Assignments 4/30:

  1. Finish classwork (see above)
  2. Hand in critique of a data story (see syllabus for more detail on this)
  3. Hand in rough idea for your final project (should be at 2-3 paragraphs)
    1. What is the overall topic of your story?
    2. Why is this story important?
    3. What benefit does structured data bring to this story? What can numbers tell you that people cannot?
  4. Read:
    1. Role of visualization in finding story in data –
    2. Directory of visualization types –
    3. Visual math mistakes –
    4. Stacked area chart vs. line chart –

7/16 Agenda; 7/23 Assignments

Agenda 7/16

  1. Overview
    1. Review data story spreadsheet
    2. Review blogs (Flowing Data, Source)
    3. Go over scraping readings for this week:
      1. Ethics of scraping –
      2. Getting data from the Web – challenges –
  2. What is Web scraping?
  3. Scrape a website with programming: Dataset
    1. Download Python (If you are on a Mac, just go to the Terminal and hit python.
    2. In the terminal, run pip install Beautiful Soup, pip install requests, pip install csv
    3. Discuss how to identify what we want to scrape
    4. Go over parts of a webpage, how they work together.
    5. Grab the file I created, and run it successfully:
    6. Comment out/remove various parts of the file and talk about what makes it work.
  4. Scrape a website w/out programming (this tutorial may become homework)
    1. Download data set and Scraper extension: Dataset | Scraper
      1. Learn how to make a list into a spreadsheet
    2. Introduce with above dataset, a more flexible option.
    3. More advanced techniques with Outwit Hub, using same data set
      1. Pull specific links/images
      2. Use knowledge of how the Web works to write more complex before/after scraper. –

Assignments (due 7/23)

  1. Finish scraping without programming tutorial from the blog.
  2. Readings:
    1. Role of visualization in finding story in data –
    2. Directory of visualization types –
    3. Visual math mistakes –
    4. Stacked area chart vs. line chart –
    5. Why data viz matters –
    6. Principles of visual design –
    7. History of visualization –
    8. Importance of white space –
  3. Submit final project idea by next week.

7/9 Agenda; 7/16 Assignments

Agenda 7/9:

  1. Go over spreadsheet data stories
  2. Review Flowing Data/Source for this week
  3. Discuss how the homework went — what sites were most/least helpful?
  4. Discuss interviewing data article
  5. Useful types of data sets
  6. Converting PDF to spreadsheet –>
    1. Use this dataset
  7. Categorize our questions — are they:
    1. Calculation
    2. Sorting
    3. Filtering
    4. Other
  8. Review how to answer
    1. Calculation
    2. Sorting
    3. Filtering
    4. Other – you may need more info, may not be appropriate as a data question, may need a not-yet-covered bit of Excel

Assignments 7/16:

  1. Hand in completed questions, with answers, about your data set. You may have completed this in class, or you might not be finished, in which case you’ll have a bit of work to do at home.
    1. Includes a spreadsheet of questions
    2. The data set you are using
    3. A memo explaining what process you used to arrive at each of those answers.
  2. Read the following, and be prepared to discuss:
    1. Ethics of scraping –
    2. Getting data from the Web – challenges –
  3. Use what we discussed in class today to carefully consider your final project topic. Can you use any of these insights? Do you need more info? A different data set? Your project idea is due in 2 weeks. Use this process to help you arrive at a topic.

7/2 Agenda; 7/9 Assignments

Agenda for July 2 (This week)

  1. Review data stories
  2. Go over Flowing Data/Source blogs
  3. Discuss Data Journalism documentary
  4. Think about ways to find data –
  5. Review file types –
  6. Go over advanced operators:
  7. Review tips:
  8. Complete and hand in this worksheet:
  9. Use techniques we discussed in class today to find data sources:
    1. What topic do you want to search? Write 5 search terms related to your topic.
    2. Think about your topic and search the Data Hub, World Bank, United Nations and UK Data Archive (all referenced here:, as well as (which we didn’t talk about, just looking for you to explore). Identify 2 data sources of interest from each of those sites, and record them and why they are interesting (should be a total of 10).
    3. Use techniques we discussed in class today to find at least ten different interesting data sources on your beat. At least five should be a form of structured data (xls, csv, xlsx), one should be a pdf and two should be others (listed below). Record how you accessed this information (what you entered into Google search) and write 2-3 sentences for each set describing what you found, and how it might be useful). One search should be by site type, one by link, and at least five by filetype.


csv – comma-separated values
xls/xlsx – Excel

pdf – unstructured data

xml/json – structured data, not spreadsheet
ppt – internal presentations
kmz/kml/shp – geographic data

Assignments for July 9 (Next week)

  1. Read about interviewing data
  2. Create your own data source. Think of a topic you’d like to collect information on for your beat. Lay out at least five columns of info you want to collect, and collect at least five records. Could be info about sources you talk to, to create a rolodex. Could be about different locations (banks, countries, etc).
  3. Complete in-class assignment on finding data sources on a topic you are interested in from Google and data archives if not already done
  4. Choose one of the data sources you found to play with and select it for next week, should be related to a possible final project idea
  5. Look at the headers of that data set you selected and write down 5-10 questions that you would like to know the answers to based on your data (the reading above should help you come up with these)
  6. Send Michelle ( the one data set you have chosen, and the 5-10 questions you want to ask, by Wed. July 8 at midnight.

Welcome! 6/25 Agenda; 7/2 Assignments

Agenda for June 25 (This week)

  1. Introduction to class purpose
  2. Go over syllabus
  3. How to look for data on your beat — an overview (also, thinking about clients, never too early)
  4. Introductions – Professor and students
  5. What is data?
  6. What is the importance of cleaning data?
  7. Classwork exercise, together: Clean up basic facts you filled out in the form, to get consistency across data points

Assignments for July 2 (Next week)

  1. Enter a visualization or data story you would like to discuss in this spreadsheet. The link can always be found on the left-hand side of this site as well:
  2. Read the two blogs we are to keep up with each week — Flowing Data and Source, linked at left.
  3. Clean up the Excel spreadsheet with our class’ info, which you received via email and mail it back to me at
  4. Fill out the introductory survey if you haven’t already, the link is in your email.
  5. Watch All the chapters. It should be about an hour. Then write me at least 500 words (and no more than 1,000) with a reaction to the video — things that were new to you, what you might like to try to do yourself, cited pieces or ideas you found particularly inspiring, and/or questions you have. Send that to
  6. As you engage with your beat in the newsroom, keep your eyes open for data, start thinking about a related project.