diff --git a/.DS_Store b/.DS_Store
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diff --git a/introduction/what.md b/0.1-what.Rmd
similarity index 74%
rename from introduction/what.md
rename to 0.1-what.Rmd
index adcfce85b..5c74ecb4e 100644
--- a/introduction/what.md
+++ b/0.1-what.Rmd
@@ -1,26 +1,23 @@
-# What is Data Visualization?
-*by [Jack Dougherty](introduction/who.md), last updated February 28, 2017*
+## What is Data Visualization? {#what}
+*last updated February 28, 2017*
Data visualization is broadly defined as a method of encoding quantitative, relational, or spatial information into images. Classic examples include [Charles Menard's figurative map](https://en.wikipedia.org/wiki/Charles_Joseph_Minard) of Napoleon's defeat and retreat during the Russian campaign of 1812, and [John Snow's dot map](https://en.wikipedia.org/wiki/John_Snow) of cholera cases during the London epidemic of 1854.
-
+
This free online introductory book focuses on selected topics in data visualization:
-**Charts and maps:** Despite the growing variety of visualization types, this book features chapters on creating [charts](../chart) and [maps](../map), and a wide range of ways to communicate with these classic models.
+**Charts and maps** Despite the growing variety of visualization types, this book features chapters on creating [charts](chart) and [maps](map), and a wide range of ways to communicate with these classic models.
**Reusable tools and templates:** Unlike infographics created for one-time use, all of the tools and templates in this book are recyclable, and allow you to upload a new dataset to display your story.
**Free and easy-to-learn:** We have selected data visualization tools that are free to use (or work on a freemium model, where advanced features or higher usage requires payment), and searched for those that we believe are easy-to-learn, based on our teaching experience with undergraduate students and non-profit community organizations.
-**Interactive on the open web:** Many books assume that you will deliver your data visualizations to in-person audiences on printed paper or presentation slides. But in this book, we show how to [embed interactive charts and maps on your website](../embed), to share with the wider public.
+**Interactive on the open web:** Many books assume that you will deliver your data visualizations to in-person audiences on printed paper or presentation slides. But in this book, we show how to [embed interactive charts and maps on your website](embed), to share with the wider public.
-**Storytelling:** Data visualization is more than pretty pictures. In this book, the best visualizations are those that [tell your data story](../story) -- and pull readers' attention to what really matters -- by combining images and text, and offering exploration with explanation.
+**Storytelling:** Data visualization is more than pretty pictures. In this book, the best visualizations are those that [tell your data story](story) -- and pull readers' attention to what really matters -- by combining images and text, and offering exploration with explanation.
-## Learn more
+#### Learn more {-}
- Michael Friendly and Daniel J. Denis, “Milestones in the History of Thematic Cartography, Statistical Graphics, and Data Visualization,” 2001, http://www.datavis.ca/milestones/
- Isabel Meirelles, Design for Information: An Introduction to the Histories, Theories, and Best Practices Behind Effective Information Visualizations (Rockport Publishers, 2013), http://isabelmeirelles.com/book-design-for-information/
- Edward Tufte, The Visual Display of Quantitative Information (Graphics Press, 1983), and subsequent works at https://www.edwardtufte.com
-
-{% footer %}
-{% endfooter %}
diff --git a/introduction/why.md b/0.2-why.Rmd
similarity index 94%
rename from introduction/why.md
rename to 0.2-why.Rmd
index 34b110c95..9870c1e57 100644
--- a/introduction/why.md
+++ b/0.2-why.Rmd
@@ -1,9 +1,9 @@
-# Why this book?
-*by [Jack Dougherty](introduction/who.md), last updated February 20, 2017*
+## Why this book? {#why}
+*last updated February 20, 2017*
*Data Visualization for All*, an open-access online textbook, seeks to help you tell your story -- and show your data -- through the power of the public web.
-This open-access book reflects what I've learned while teaching data visualization [to undergraduate students at Trinity College](http://commons.trincoll.edu/dataviz), and now [to a global online class on the Trinity edX platform](https://www.edx.org/school/trinityx). Over the past few years, Trinity students and I have built interactive charts and maps in partnership with non-profit organizations in Hartford, Connecticut, to help them share their stories with data on the public web. Also, my students and colleagues have used these tools to create [On The Line: How Schooling, Housing, and Civil Rights Shaped Hartford and its Suburbs](http://ontheline.trincoll.edu), an open-access book-in-progress that features interactive historical maps of urban-suburban change. Students and colleagues who wrote tutorials, designed learning exercises, or developed code templates for *Data Visualization for All* are listed as [co-authors](introduction/who.md).
+This open-access book reflects what I've learned while teaching data visualization [to undergraduate students at Trinity College](http://commons.trincoll.edu/dataviz), and now [to a global online class on the Trinity edX platform](https://www.edx.org/school/trinityx). Over the past few years, Trinity students and I have built interactive charts and maps in partnership with non-profit organizations in Hartford, Connecticut, to help them share their stories with data on the public web. Also, my students and colleagues have used these tools to create [On The Line: How Schooling, Housing, and Civil Rights Shaped Hartford and its Suburbs](http://ontheline.trincoll.edu), an open-access book-in-progress that features interactive historical maps of urban-suburban change. Students and colleagues who wrote tutorials, designed learning exercises, or developed code templates for *Data Visualization for All* are listed as [authors and contributors](authors).
Although my outstanding colleagues have professional training, do not confuse them with me, the proverbial "Jack of all trades, master of none." I do not consider myself an expert in data visualization, nor should anyone mistake me for a computer scientist or data scientist. Inspect my higher education transcripts and you'll see only one computer science class (something called FORTRAN77 back in 1982), and not a single course in statistics, sadly. Instead, my desire to learn data visualization was driven by my need as an historian to tell stories about urban-suburban places and change over time. If you've ever watched me teach a class or deliver a presentation on these topics -- always talking with my hands in the air -- you'll understand my primal need to create charts and maps. Stories become more persuasive when supported with data, especially well-crafted images that convey data relationships more clearly than words. Furthermore, these data stories become more powerful when we share them online, where they reach broader audiences who can interact with and evaluate our evidence.
@@ -14,9 +14,5 @@ All of these data visualization lessons I learned have been **so valuable** -- t
If this free book is valuable for your education, then join us by sharing and supporting it for future readers:
- Tell your friends about the book and share the link via social media, text, or email
- Improve the book by adding comments or suggesting new chapters on our GitBook platform
-- [Donate to support DataViz students at Trinity College](../donate) to expand the book and continue work with community partners
Try out the tutorials, explore the online examples, share what you've learned with others, and dream about better ways to tell your data stories.
-
-{% footer %}
-{% endfooter %}
diff --git a/0.3-authors.Rmd b/0.3-authors.Rmd
new file mode 100644
index 000000000..1b6b633a6
--- /dev/null
+++ b/0.3-authors.Rmd
@@ -0,0 +1,31 @@
+## Authors and Contributors {#authors}
+
+UPDATE THIS: Contributors to *Data Visualization for All* are credited in the byline to specific pages they authored (or co-authored), hold the copyright to those pages (jointly if co-authored), and have agreed to freely share the work as an open-access book. *Data Visualization for All* is copyrighted by Jack Dougherty and contributors and distributed under a [Creative Commons BY-NC 4.0 International License](http://creativecommons.org/licenses/by-nc/4.0/). You may freely share and modify this content for non-commercial purposes, with a source credit to: http://DataVizForAll.org
+
+| Co-Authors | About Us |
+| --------------- | ------------- |
+|  | [Jack Dougherty](http://bit.ly/jackdougherty) is Professor of Educational Studies at Trinity College in Hartford, Connecticut. He and his [DataViz students](http://commons.trincoll.edu/dataviz) partner with community organizations to help tell their data stories on the web. Follow him on [Twitter](https://twitter.com/doughertyjack) and [on GitHub](https://github/com/jackdougherty).|
+|  | [Ilya Ilyankou](https://www.linkedin.com/in/ilya-ilyankou-a64675ab) is completing a double major in Computer Science and Studio Arts in the Class of 2018 at Trinity College. He developed Leaflet and Highcharts code templates for this book. Follow [ilyankou on GitHub](https://github.com/ilyankou). |
+| Contributors | |
+|  | [Veronica X. Armendariz](https://www.linkedin.com/in/veronica-armendariz-4b814899) earned her bachelor's degree in Educational Studies in 2016 from Trinity College, where she also served as a teaching assistant for the [DataViz internship seminar](http://commons.trincoll.edu/dataviz). She contributed tutorials for this book. |
+|  | Stacy Lam is a co-instructor for the [Data Visualization for All online course](http://www.datavizforall.org/enroll) at Trinity College, where she is a prospective Engineering major in the Class of 2019. She contributed to chapters for this book.|
+|  | [David Tatem](http://www.trincoll.edu/LITC/its/about/Pages/Learn.aspx) is a co-instructor for the [Data Visualization for All online course](http://www.datavizforall.org/enroll) at Trinity College, where he is an Instructional Technologist who specializes in the Social Sciences. He contributed to chapters for this book.|
+
+Funding for student contributions to this book was generously provided by the [Community Learning Initiative](http://www.trincoll.edu/urbanglobal/cugs/students/cli/Pages/default.aspx) and [Information Technology Services](http://www.trincoll.edu/LITC/its/Pages/default.aspx) at [Trinity College in Hartford, Connecticut](http://www.trincoll.edu).
+
+Live videos were produced with Trinity College Information Technology staff and friends: Angie Wolf, Sean Donnelly, Ron Perkins, Samuel Oyebefun, Phil Duffy, and Christopher Brown.
+
+#### Trademarks {-}
+Any use of a trademarked name without a trademark symbol is for readability purposes only. We have no intention of infringing on the trademark.
+
+- BatchGeo is a registered trademark of BatchGeo, LLC
+- CARTO is a registered trademark of CartoDB, Inc.
+- GitBook is a registered trademark of FriendCode, Inc.
+- GitHub and the GitHub logo are registered trademarks of GitHub, Inc.
+- Google and the Google logo are registered trademarks of Google Inc.
+- Highcharts is a registered trademark of Highsoft, Norway
+- Social Explorer is a registered trademark of Social Explorer, Inc.
+- WordPress is a registered trademark of the WordPress Foundation
+
+#### Disclaimer {-}
+The information is this book is provided without warranty. The lead author, contributors, and publisher have neither liability nor responsibility to any person or entity related to any loss or damages arising from the information contained in this book.
diff --git a/introduction/how.md b/0.4-how.Rmd
similarity index 59%
rename from introduction/how.md
rename to 0.4-how.Rmd
index f6b8e8b6d..7f0901ad4 100644
--- a/introduction/how.md
+++ b/0.4-how.Rmd
@@ -1,56 +1,55 @@
-# How to Read and Comment
-*by [Jack Dougherty](introduction/who.md), last updated February 28, 2017*
+## How to Read and Comment {#read}
+*last updated February 28, 2017*
-*Data Visualization for All* refers to both this open-access digital book and a [free online course](../enroll) by the same name. We refer to them as "the book" and "the course."
+** TO DO: update section **
-## Recommended: Read the online edition
-We designed the book to be read online, in any modern web browser, on desktops, laptops, or mobile devices. The online edition features interactive charts and maps that you can explore, and video tutorials that you can view at your own pace. If desired, readers can freely download any of the ebook editions--[PDF](https://www.gitbook.com/download/pdf/book/jackdougherty/datavizforall) or [ePUB](https://www.gitbook.com/download/epub/book/jackdougherty/datavizforall) or [Mobi/Kindle](https://www.gitbook.com/download/mobi/book/jackdougherty/datavizforall)--but these do not include the interactive features in the online web edition. Learn more about [how GitBook works](../gitbook) and publish your own book.
+*Data Visualization for All* refers to both this open-access digital book and a free online course by the same name. We refer to them as "the book" and "the course." **TO DO: add link to course**
-## Open links in new tabs
+#### Recommended: Read the online edition {-}
+We designed the book to be read online, in any modern web browser, on desktops, laptops, or mobile devices. The online edition features interactive charts and maps that you can explore, and video tutorials that you can view at your own pace. If desired, readers can freely download any of the ebook editions--but these do not include the interactive features in the online web edition. Learn more about [how GitBook works](../gitbook) and publish your own book.
+
+#### Open links in new tabs {-}
Keep your place when reading online and moving between pages.
- Two-finger trackpad click
- or Control + click (Mac)
- or Alt + click (Chromebook)
- or right-click (Windows and others)
-
+
-## Use a second monitor
+#### Use a second monitor {-}
If you have a small screen, consider connecting a second monitor, or work next to a second computer or tablet. This allows you to view tutorials in one screen and build visualizations in the other screen.
-
+
-## Refresh browser
+#### Refresh browser {-}
To view the most up-to-date content in your web browser, do a "hard refresh" to [bypass any saved content in your browser cache](https://en.wikipedia.org/wiki/Wikipedia:Bypass_your_cache).
- Ctrl + F5 (most Windows-Linux browsers)
- Command + Shift + R (Chrome or Firefox for Mac)
- Shift + Reload button toolbar (Safari for Mac)
-## Comment on any paragraph
+#### UPDATE Comment on any paragraph {-}
- Requires a free account on GitHub http://github.com
- Select text and click the plus symbol (+) in margin.
- GitBook section headers and lists cannot accept comments.
- View other comments in the margins, or all in [Discussions](https://www.gitbook.com/book/jackdougherty/datavizforall/discussions).
- Constructive criticism and suggestions are welcome.
-
+
-## Suggest revisions on any page
+#### UPDATE Suggest revisions on any page {-}
- Click "Edit on GitHub" at top of any page, which opens new tab.
- 
+ 
- To view the code behind the page, click Raw button.
- To suggest revisions, click Editor button (pencil symbol). Requires free [GitHub account](http://github.com).
- 
+ 
- After entering revisions, scroll down to click Propose File Change.
- On next screen, click Create Pull Request to submit proposed changes to the book owner.
- On next screen, click Create Pull Request again to confirm.
- The book owner will review your suggested revisions, and you will receive automatic notification on any changes.
-## Propose additional chapters
-- [Contact the lead author](who.md) with a summary of your proposed chapter.
-- On the [book GitHub repository](https://github.com/JackDougherty/datavizforall), fork a copy to your own GitHub account (requires free signup).
-- Create your proposed chapter following the book's existing folder/file structure, in GitHub/GitBook Markdown format, as described in this chapter [about GitBook](../gitbook).
+#### Propose additional chapters {-}
+- [Contact the authors](introduction.html#who) with a summary of your proposed chapter.
+- On the [book GitHub repository](https://github.com/datavizforall), fork a copy to your own GitHub account (requires free signup).
+- Create your proposed chapter following the book's existing folder/file structure.
- If accepted, the contributing author retains the copyright to their work but agrees to publish it under the Creative Commons BY-NC license. Authors do not receive royalties, but enjoy the eternal rewards of sharing knowledge.
-
-{% footer %}
-{% endfooter %}
diff --git a/choose/README.md b/01-choose.Rmd
similarity index 58%
rename from choose/README.md
rename to 01-choose.Rmd
index 4289c1e4b..934ff28a1 100644
--- a/choose/README.md
+++ b/01-choose.Rmd
@@ -1,14 +1,13 @@
-# Choose Tools to Tell Your Data Story
-*by [Jack Dougherty, Stacy Lam, and David Tatem](../introduction/who.md), last updated February 10, 2017*
+# Choose Tools to Tell Your Data Story {#choose}
+*by [Jack Dougherty with Stacy Lam and David Tatem](authors), last updated February 10, 2017*
Do you feel overwhelmed by the enormous range of data visualization tools? There's been so many different tools released in recent years that anyone would have a hard time deciding which ones to use. Even if you limit your choices to the dozen or so tools specifically mentioned in this book, how do you make wise decisions?
- [Draw and Write Your Data Story](draw) reminds us to start with the most important item in your toolkit: ***your story***. Begin by drawing pictures and writing questions or sentences to capture your ideas on paper, and then choose the most appropriate tools to create your vision.
-- [Ask Questions When Choosing Tools](ask) lists several criteria to consider when making software decisions. Many of us look for free or affordable tools in the perfect sweet spot -- easy-to-learn, yet powerful -- and that's the focus of this book.
+- [Ask Questions When Choosing Tools](ask) lists several criteria to consider when making software decisions. Many of us look for free or affordable tools in the perfect sweet spot---easy-to-learn, yet powerful---and that's the focus of this book.
- [Rate Three Simple Map Tools](rate) invites readers to create a basic interactive point map using three different online tools, and to evaluate each one using selected criteria from the chapter above.
-**[Enroll in our free online course](../../enroll)**, which introduces these topics in the brief video below, and offers more exercises and opportunities to interact with instructors and other learners.
-{%youtube%}SS1BGp_lxnU{%endyoutube%}
+Enroll in our free online course **TO DO add link**, which introduces these topics in the brief video below, and offers more exercises and opportunities to interact with instructors and other learners.
-{% footer %}
-{% endfooter %}
+#### Watch the YouTube Video {-}
+
diff --git a/choose/draw/README.md b/01.1-draw.Rmd
similarity index 90%
rename from choose/draw/README.md
rename to 01.1-draw.Rmd
index 73da530de..31d4806eb 100644
--- a/choose/draw/README.md
+++ b/01.1-draw.Rmd
@@ -1,14 +1,16 @@
-## Draw and Write Your Data Story
-*by [Jack Dougherty, Stacy Lam, and David Tatem](../../introduction/who.md), last updated February 20, 2017*
+## Draw and Write Your Data Story {#draw}
+*last updated February 20, 2017*
Before you dive deeply into software, think about the most important item in your toolkit: **your story**. The primary reason we're designing visualizations is to improve how we communicate our data story to other people, so let's begin there.
Push away the computer and pick up some old-school tools:
+
- colored markers or pencils
- lots of blank paper
- your imagination
First, at the top of the page, write down your data story.
+
- Is it in the form of a question? If so, figure out how to pose the question.
- Or maybe it's in the form of an answer to that question? If so, spell out your clearest statement.
- If you're lucky, perhaps you already can envision a full story, with a beginning, middle, and end.
@@ -20,6 +22,3 @@ Further down the page (or on a separate sheet), draw quick pictures of the visua
- Will your visualization be interactive? Insert arrows, buttons, whatever.
Finally, share your data story with someone else and talk through your preliminary ideas. Does your sketch and sentences help to convey the broader idea that you're trying to communicate? If so, this is one good sign that your data story is worth pursuing, with the visualization tools, templates, and techniques in other chapters of this book.
-
-{% footer %}
-{% endfooter %}
diff --git a/choose/ask/README.md b/01.2-ask.Rmd
similarity index 93%
rename from choose/ask/README.md
rename to 01.2-ask.Rmd
index a6f71f8d5..7e18e89b5 100644
--- a/choose/ask/README.md
+++ b/01.2-ask.Rmd
@@ -1,9 +1,9 @@
-# Ask Questions When Choosing Tools
-*by [Jack Dougherty, Stacy Lam, and David Tatem](../../introduction/who.md), last updated February 6, 2017*
+## Ask Questions When Choosing Tools {#ask}
+*last updated February 6, 2017*
When each of us decides which digital tools best fit our needs, we often face trade-offs. On one hand, many of us prefer easy-to-learn tools, especially those with a drag-and-drop interface, but they often force us to settle for limited options. On the other hand, we also favor powerful tools that allow us to control and customize our work, yet most of these require higher-level coding skills. The goal of this book is to find the best of both worlds: that "sweet spot" where tools are both friendly and flexible.
-
+
Before testing out new tools, try listing the criteria that guide your decision-making process. What are the most important factors that influence whether or not you add another item to your digital toolkit? Here's the list that came to our minds:
@@ -37,7 +37,7 @@ Before testing out new tools, try listing the criteria that guide your decision-
That's a long list! It's even longer than the number of tools we'll mention in this book. But don't let it overwhelm you. The diagram at the top of the page illustrates the two most important criteria for the many free tools that are currently available: easy-to-learn and powerful features.
-## Learn more about choosing tools
+#### Learn more about choosing tools {-}
Carl V. Lewis, Dataviz.tools: A curated guide to the best tools, resources and technologies for data visualization, http://dataviz.tools
@@ -48,6 +48,3 @@ Lisa Charlotte Rost, “What I Learned Recreating One Chart Using 24 Tools,” S
Lisa Spiro and colleagues, DiRT: Digital Research Tools Directory (formerly Bamboo), http://dirtdirectory.org
Audrey Watters, “‘The Audrey Test’: Or, What Should Every Techie Know About Education?,” Hack Education, March 17, 2012, http://hackeducation.com/2012/03/17/what-every-techie-should-know-about-education
-
-{% footer %}
-{% endfooter %}
diff --git a/choose/rate/README.md b/01.3-rate.Rmd
similarity index 63%
rename from choose/rate/README.md
rename to 01.3-rate.Rmd
index b1b0dadf1..defc4e43c 100644
--- a/choose/rate/README.md
+++ b/01.3-rate.Rmd
@@ -1,5 +1,5 @@
-# Rate Three Simple Map Tools
-*by [Jack Dougherty, Stacy Lam, and David Tatem](../../introduction/who.md), last updated March 16, 2017*
+## Rate Three Simple Map Tools {#rate}
+*last updated March 16, 2017*
Let's explore criteria from the previous chapter by comparing three different tools, and reflecting on which factors you feel are most important when making decisions about your toolkit. We'll test three drag-and-drop tools to transform sample address data into a simple interactive point map.
@@ -7,23 +7,24 @@ Each tool can **geocode** address data by looking up a location (such as 500 Mai
For our sample data, we'll use this table of 9 locations in North America, with 3 intentional mistakes to test for geocoding errors.
-
+
-First, click this link and Save to download the sample file to your computer: [sample-address-data in CSV format](https://www.datavizforall.org/choose/rate/sample-address-data.csv). CSV means comma-separated-values, a generic spreadsheet format that many tools can easily open. If you need help with downloading, see this [short video tutorial](https://www.youtube.com/watch?v=-04PQldP9HQ).
+First, click this link and Save to download the sample file to your computer: [sample-address-data in CSV format](data/sample-address-data.csv). CSV means comma-separated-values, a generic spreadsheet format that many tools can easily open. If you need help with downloading, see this [short video tutorial](https://www.youtube.com/watch?v=-04PQldP9HQ).
Next, build a point map with the sample data, by following the tutorials for the three tools below.
| Tool | Step-by-step tutorial in this book |
| :---- | :---- |
-| [BatchGeo](http://batchgeo.com) | [BatchGeo tutorial](../../map/batchgeo/) |
-| [Google My Maps](https://www.google.com/maps/d/) | [My Maps tutorial](../../map/mymaps/) |
-| [Carto Builder](http://carto.com) | [Carto tutorial](../../map/carto/) |
+| [BatchGeo](http://batchgeo.com) | [BatchGeo tutorial](batchgeo) |
+| [Google My Maps](https://www.google.com/maps/d/) | [My Maps tutorial](mymaps) |
+| [Carto Builder](http://carto.com) | [Carto tutorial](carto) |
Finally, rate your experience using each tool with these selected criteria:
+
- Easy-to-learn: Which tool was the simplest for creating a basic point map?
- Price: Which of these free tools provided the most services at no cost?
- Customization: Which tool enabled you to modify the most details about your map?
- Data Migration: Which tool most easily allowed you to import and export your data?
- Error-friendly: Which tool geocoded most accurately or signaled possible errors?
-**Recommended: [Enroll in our free online course](../../enroll)** to compare your ratings to other students.
+Recommended: Enroll in our free online course **LINK TO DO** to compare your ratings to other students.
diff --git a/spreadsheet/README.md b/02-spreadsheet.Rmd
similarity index 87%
rename from spreadsheet/README.md
rename to 02-spreadsheet.Rmd
index dadc2f657..be90f6a42 100644
--- a/spreadsheet/README.md
+++ b/02-spreadsheet.Rmd
@@ -1,5 +1,5 @@
-# Improve Your Spreadsheet Skills
-*by [Jack Dougherty](../introduction/who.md), last updated March 1, 2017*
+# Improve Your Spreadsheet Skills {#spreadsheet}
+*by [Jack Dougherty](authors), last updated March 1, 2017*
Spreadsheets are wonderful tools to organize data into tables of rows and columns. With a spreadsheet, you can sort, filter, calculate, aggregate, and reorganize information to help you find the stories buried inside.
@@ -13,14 +13,15 @@ Four common spreadsheet tools:
| [LibreOffice](http://www.libreoffice.org) | Free, open-source alternative to Microsoft Office desktop. Donation requested during download. |
Which spreadsheet tool should you use? That depends on how you wish to share and store data for your project.
+
- If you are the **only person** working on a data project, use any spreadsheet tool.
- If you need to **protect private data**, avoid online tools and use any desktop spreadsheet.
- If you need to **share live data** with others, use Google Sheets.
-
This introductory online book features Google Sheets because it's a free and easy-to-learn tool for collaborating and sharing data with others. The basic spreadsheet methods shown here are very similar across all spreadsheet tools. But advanced users may need more complex tools to manage very large datasets, or relational databases, or to perform deeper analysis.
If you're new to spreadsheets or want to refresh your skills, see the following chapters:
+
- [Upload and Convert to Google Sheets](upload)
- [Make a Copy with Google Sheets](copy)
- [Share with Google Sheets](share)
@@ -31,7 +32,4 @@ If you're new to spreadsheets or want to refresh your skills, see the following
- [Match Data with VLookup](vlookup)
- [Collect and Share Survey Data with Google Forms](forms)
-**[Enroll in our free online course](../../enroll)**, which offers more spreadsheet exercises and opportunities to interact with instructors and other learners.
-
-{% footer %}
-{% endfooter %}
+Enroll in our free online course] which offers more spreadsheet exercises and opportunities to interact with instructors and other learners.
diff --git a/spreadsheet/upload/README.md b/02.1-upload.Rmd
similarity index 72%
rename from spreadsheet/upload/README.md
rename to 02.1-upload.Rmd
index a3c812188..63525c00b 100644
--- a/spreadsheet/upload/README.md
+++ b/02.1-upload.Rmd
@@ -1,35 +1,32 @@
-# Upload Files and Convert to Google Sheets
-*by [Jack Dougherty](../../introduction/who.md), last updated March 2, 2017*
+## Upload Files and Convert to Google Sheets {#upload}
+*last updated March 2, 2017*
Google Drive can convert many file types into [Google Sheets format](https://www.google.com/sheets/about/):
+
- Microsoft Excel (.xls and .xlsx)
- OpenDocument Spreadsheet (.ods)
- Comma-separated values (.csv)
- Tab-separated values (.tab)
- Text files (.txt) into Google Sheets format
-## Tutorial
+#### Tutorial {-}
1) Sign in to your free Google Drive account (http://drive.google.com)
2) To convert files into Google Sheets format, open the Settings (upper-right gear symbol), and **check the box** to Convert uploaded files to Google Docs.
-
+
3) To upload your file, use the New > File Upload menu OR drag-and-drop it into your Google Drive screen.
-
+
4) When your file is successfully converted, the Google Sheets icon will appear. Recommended: Right-click to rename the file and remove the old extension (.xlsx or .csv or other), since it is no longer in this old format.
-
+
5) Google Drive files that display different icons have **not** been converted into Google Sheets format.
-
+
**Beware**: A different way to convert spreadsheets into Google Sheets format is the File > Import menu, but this creates two files in your Google Drive (such as data and data.csv), which is confusing.
-
-
-{% footer %}
-{% endfooter %}
diff --git a/spreadsheet/copy/README.md b/02.2-copy.Rmd
similarity index 59%
rename from spreadsheet/copy/README.md
rename to 02.2-copy.Rmd
index 929ac786e..9bd8a5be9 100644
--- a/spreadsheet/copy/README.md
+++ b/02.2-copy.Rmd
@@ -1,25 +1,22 @@
-# File > Make a Copy with Google Sheets
-*By [Jack Dougherty](../../introduction/who.md), last updated March 17, 2017*
+## Make a Copy with Google Sheets {#copy}
+*last updated March 17, 2017*
In this book, you will open links to Google Sheets that allow you to view -- but not edit -- the contents. How can you quickly make your own version that you can edit?
-
+
-## Best solution
+#### Best solution {-}
1) Sign in to your Google account in the upper-right corner. Requires a free account.
-2) Go to File > Make a Copy to save a duplicate of the spreadsheet to your Google Drive. By default, your copy will be private to you. Go to the [Share Data with Google Sheets](../spreadsheet/share) chapter in this book to allow others to view, comment, or edit your spreadsheet.
+2) Go to File > Make a Copy to save a duplicate of the spreadsheet to your Google Drive. By default, your copy will be private to you. Go to the [Share Data with Google Sheets](spreadsheet.html#share) chapter in this book to allow others to view, comment, or edit your spreadsheet.
Highly recommended: Create folders in your Google Drive to keep your files organized and easily findable.
-
+
-## Alternate solution
+#### Alternate solution {-}
Another option is to File > Download As into a different format, such as:
- Microsoft Excel (.xlsx)
- OpenData System (.ods), a generic multi-tab spreadsheet
- Comma-separated values (.csv), a generic single sheet
No Google account is required.
-
-{% footer %}
-{% endfooter %}
diff --git a/spreadsheet/share/README.md b/02.3-share.Rmd
similarity index 83%
rename from spreadsheet/share/README.md
rename to 02.3-share.Rmd
index c5beb0cb9..006f2be42 100644
--- a/spreadsheet/share/README.md
+++ b/02.3-share.Rmd
@@ -1,12 +1,11 @@
-# Share Data with Google Sheets
-*by [Jack Dougherty](../../introduction/who.md), last updated March 1, 2017*
+## Share Data with Google Sheets {#share}
+*last updated March 1, 2017*
To share live spreadsheet data with other people, use Google Sheets (https://www.google.com/sheets/about/). Requires a free Google
Drive account.
-## Video with step-by-step tutorial
-
-{%youtube%}PoLhyld3KLo{%endyoutube%}
+#### Video with step-by-step tutorial {-}
+
1) Sign in to your Google Drive (http://drive.google.com), and in the New menu, select Google Sheets.
@@ -32,9 +31,6 @@ Below those settings, select the Access level:
**Tip:** To avoid sending a long Google Sheets link to others, use a free link-shortening service such as Bit.ly (http://bit.ly). Requires a free account.
-## Learn more:
+#### Learn more {-}
- "Share Files from Google Drive," Google help page, https://support.google.com/docs/answer/2494822
- Jack Dougherty, "How to Co-Author and Peer Edit with Google Docs," Web Writing: How and Why for Liberal Arts Teaching and Learning, (2015), http://epress.trincoll.edu/webwriting/chapter/how-to-google-docs
-
-{% footer %}
-{% endfooter %}
diff --git a/spreadsheet/csv/README.md b/02.4-csv.Rmd
similarity index 55%
rename from spreadsheet/csv/README.md
rename to 02.4-csv.Rmd
index 860591c82..1ee3a3a13 100644
--- a/spreadsheet/csv/README.md
+++ b/02.4-csv.Rmd
@@ -1,43 +1,41 @@
-# Save Spreadsheets in CSV or ODS Formats
-*By [Jack Dougherty](../../introduction/who.md), last updated March 2, 2017*
+## Save Spreadsheets in CSV or ODS {#csv}
+* last updated March 2, 2017*
To transfer spreadsheet data to another platform, or import it into a visualization tool, you may need to convert your file into a different format. Consider two options:
-## Comma-separated values (.csv)
+#### Comma-separated values (.csv) {-}
- to transfer only one sheet of data, with no formulas or formatting, into a wide range of spreadsheet and visualization tools
-## OpenDocument Spreadsheet (.ods)
+#### OpenDocument Spreadsheet (.ods) {-}
- to transfer multiple sheets, with basic formulas and formatting, into many spreadsheet tools (Excel, Google Sheets, LibreOffice)
-## Convert to CSV or ODS with Google Sheets
+#### Convert to CSV or ODS with Google Sheets {-}
In the File > Download As menu, select either ODS (to convert a Google Sheets file with multiple tabs, formulas, and formatting) or CSV (to capture only the data in the current sheet).
-
+
-## Convert to ODS with Microsoft Excel
+#### Convert to ODS with Microsoft Excel {-}
In the File > Save As menu, select ODS format.
-
+
-## Convert to CSV with Microsoft Excel
+#### Convert to CSV with Microsoft Excel {-}
1) Note that CSV format will save only the first sheet of a multi-sheet Excel workbook. If you have source information or other data in other tabs, keep your original Excel file for backup purposes. You can give them parallel file names:
+
- data.csv
- data.xlsx
2) In the Excel file, select the File > Save As menu, and select CSV format.
-
+
3) Older versions of Excel may warn you that some features (such as formulas and formatting) will not be saved in a generic CSV data file. Be sure to keep a backup Excel version, then click Continue to save your data into CSV format.
-
-
-4) In older versions of Excel, when you quit the appliation, another screen will ask if you wish to save the CSV file a second time. **Don't let Excel confuse you.** If you have not made any changes to the Excel file since the step above, click Don't Save, because you already saved the file in CSV format.
+
-
+4) In older versions of Excel, when you quit the application, another screen will ask if you wish to save the CSV file a second time. **Don't let Excel confuse you.** If you have not made any changes to the Excel file since the step above, click Don't Save, because you already saved the file in CSV format.
-{% footer %}
-{% endfooter %}
+
diff --git a/spreadsheet/sort/README.md b/02.5-sort.Rmd
similarity index 66%
rename from spreadsheet/sort/README.md
rename to 02.5-sort.Rmd
index 7f129ec92..74db03bc4 100644
--- a/spreadsheet/sort/README.md
+++ b/02.5-sort.Rmd
@@ -1,5 +1,5 @@
-# Sort and Filter Data
-*By [Jack Dougherty](../../introduction/who.md), last updated January 13, 2017*
+## Sort and Filter Data {#sort}
+*last updated January 13, 2017*
**TO DO**
- write intro on the title concepts
@@ -7,16 +7,12 @@
- redo visuals: Google Sheets with better example
- add Filter data
-## Sort data by columns
+#### Sort data by columns {-}
To sort data rows by a column, select the entire spreadsheet (top-left corner icon), then right-click or look for the sort menu. Be sure to select the entire sheet to avoid accidentally sorting one column without the adjacent ones.
-
+
-## Filter data by columns
+#### Filter data by columns {-}
-To come *
-
-
-{% footer %}
-{% endfooter %}
+TO DO
diff --git a/spreadsheet/calculate/README.md b/02.6-calculate.Rmd
similarity index 79%
rename from spreadsheet/calculate/README.md
rename to 02.6-calculate.Rmd
index cd88c3d0f..fd7640687 100644
--- a/spreadsheet/calculate/README.md
+++ b/02.6-calculate.Rmd
@@ -1,5 +1,5 @@
-# Calculate with Formulas and Functions
-*By [Jack Dougherty](../../introduction/who.md), last updated March 16, 2016*
+## Calculate with Formulas and Functions {#calculate}
+*last updated March 16, 2016*
**TO DO**
- when possible, start text by posing a common problem, and how this method can solve it
@@ -8,13 +8,13 @@
Simple formulas can save you lots of time. The big advantage of spreadsheet tools is the ability to insert simple formulas to calculate numbers, or combine columns of text, for entire rows and columns.
-## Write a simple formula
+#### Write a simple formula {-}
In most spreadsheets, begin writing a simple formula with an equal sign, and refer to specific cells and functions, such as:
- = A2 + B2 + C2
-## Write formulas with built-in functions
+#### Write formulas with built-in functions {-}
**TO DO** rewrite to show how this is same as above
@@ -24,23 +24,23 @@ In most spreadsheets, begin writing a simple formula with an equal sign, and ref
- = Average(A2:C2)
-## Copy and paste, or drag formulas
+#### Copy and paste, or drag formulas {-}
If you've inserted a formula into one row, how can you quickly do the same calculation across all rows?
Spreadsheets can magically automate calculations across rows or columns. In most cases, you can copy and paste a formula into new cells. Sometimes you can click-and-drag the lower-right corner of a formula cell (which may appear as a cross-hair) to automate calculations.
-
+
-## Copy and Paste > Special > Values to replace formulas with data
+#### Copy and Paste > Special > Values to replace formulas with data {-}
After inserting calculations in a spreadsheet, sometimes dynamic formulas must be replaced with static data before the results can be visualized. One solution is to select and copy a column (or the entire sheet), then paste > special > values to replace the formula with numerical results.
-
+
Remember that if you need to check or run the calculations again at a later point, click (or right-click) the tab to save a copy to the spreadsheet as a backup.
-## Create a column of consecutive numbers
+#### Create a column of consecutive numbers {-}
To quickly create a column of consecutive numbers, such as unique ID numbers, in most spreadsheet tools:
@@ -49,8 +49,4 @@ To quickly create a column of consecutive numbers, such as unique ID numbers, in
- On a Mac, hold down the Option key and drag the cross-hair down to create consecutive numbers
- **TO DO** insert equivalent commands for Windows, Chromebook
-
-
-
-{% footer %}
-{% endfooter %}
+
diff --git a/spreadsheet/pivot/README.md b/02.7-pivot.Rmd
similarity index 71%
rename from spreadsheet/pivot/README.md
rename to 02.7-pivot.Rmd
index 12d1b1e4a..4477c6389 100644
--- a/spreadsheet/pivot/README.md
+++ b/02.7-pivot.Rmd
@@ -1,20 +1,20 @@
-# Group Data with Pivot Tables
-*By [Jack Dougherty](../../introduction/who.md), last updated March 16, 2017*
+## Group Data with Pivot Tables {#pivot}
+*last updated March 16, 2017*
Here's a common problem: You open a large spreadsheet with many rows of data, such as a list of students. Your goal is to count students by categories, such as the number of students by each year of birth. What's the most efficient way to do this?
-
+
A solution: Create a pivot table to aggregate (or group together) and summarize data in another spreadsheet tab.
-
+
While pivot tables may look different across spreadsheet tools, the concept is the same.
-## Video with step-by-step tutorial for Google Sheets
-{%youtube%}3sK7-g0otGM{%endyoutube%}
+#### Video with step-by-step tutorial for Google Sheets {-}
+
-1) Click this link and Save to download to your computer: [sample-students in CSV format](https://www.datavizforall.org/spreadsheet/pivot/sample-students.csv). CSV means comma-separated values, a generic spreadsheet format that most tools can easily open.
+1) Click this link and Save to download to your computer: [sample-students in CSV format](data/sample-students.csv). CSV means comma-separated values, a generic spreadsheet format that most tools can easily open.
2) Sign into [Google Drive](http://drive.google.com) (requires free account) and drag-and-drop the sample CSV file to instantly upload. Before you do this, make sure your Settings (gear symbol) is set to Convert Uploads to Google Docs editor format (the default setting).
@@ -28,16 +28,13 @@ While pivot tables may look different across spreadsheet tools, the concept is t
7) Change Summarize by SUM to Summarize by COUNTA (to count alphabetical or numerical entries), or COUNT (to count only numeric values).
-## More Advanced Pivot Table with Google Sheets
+#### More Advanced Pivot Table with Google Sheets {-}
In addition to grouping by rows, you can create more advanced pivot tables by grouping by columns and filtering results. For example, the pivot table shown below shows rows by birth year, columns by gender (blank, female, male, other), and filters results to show only 18 students from one country: US.
-
+
-## Learn More
+#### Learn More {-}
- Google, Create and Use Pivot Tables Help Page https://support.google.com/docs/answer/1272898
- LibreOffice, Creating Pivot Tables Help Page https://help.libreoffice.org/Calc/Creating_Pivot_Tables
- Andrew Ba Tran, "Tutorial: How to Make Pivot Tables in Google Sheets," TrendCT, September 4, 2015, http://trendct.org/2015/09/04/tutorial-how-to-make-pivot-tables-in-google-sheets
-
-{% footer %}
-{% endfooter %}
diff --git a/spreadsheet/vlookup/README.md b/02.8-vlookup.Rmd
similarity index 61%
rename from spreadsheet/vlookup/README.md
rename to 02.8-vlookup.Rmd
index 37718a83c..b2e58a3dc 100644
--- a/spreadsheet/vlookup/README.md
+++ b/02.8-vlookup.Rmd
@@ -1,25 +1,26 @@
-# Match Columns with VLOOKUP Function
-*By [Jack Dougherty](../../introduction/who.md), last updated March 16, 2017*
+## Match Columns with VLOOKUP {#vlookup}
+*last updated March 16, 2017*
Here's a common problem: Sheet 1 contains a long roster of students enrolled in our *Data Visualization For All* course, with a two-letter code for their nation. Sheet 2 contains the list of codes for each nation. How can we quickly match up this information in one sheet, so that each row contains the nation for each student?
-
+
One solution: Spreadsheets contain a VLOOKUP function, which "looks up" data across two or more vertical columns, and automatically fills in matching entries. This tutorial demonstrates how to set up this calculation in Google Sheets and Excel
-
+
-## Video with step-by-step tutorial for Google Sheets
-{%youtube%}qrzKzts3mV0{%endyoutube%}
+#### Video with step-by-step tutorial for Google Sheets {-}
+
-1) Click this link and Save to download to your computer: [sample-students-nations in .ODS format](sample-students-nations.ods). ODS means OpenDocument System, a generic multi-tab format that most spreadsheet tools can easily open.
+1) Click this link and Save to download to your computer: [sample-students-nations in .ODS format](data/sample-students-nations.ods). ODS means OpenDocument System, a generic multi-tab format that most spreadsheet tools can easily open.
-2) To upload the downloaded file to Google Sheets, see the [Upload Files and Convert tutorial](../upload) in this book, and remember that Settings (gear symbol) must be set to Convert files to Google format. Or, open the file with Microsoft Excel or LibreOffice, and the directions below will be similar.
+2) To upload the downloaded file to Google Sheets, see the [Upload Files and Convert tutorial](upload) in this book, and remember that Settings (gear symbol) must be set to Convert files to Google format. Or, open the file with Microsoft Excel or LibreOffice, and the directions below will be similar.
2) In the students sheet, type "nation" as a column header into cell E1.
3) Click in cell E2, start typing "=VLOOKUP" and the spreadsheet tool will suggest that you complete the formula in this format:
-```
+
+```markdown
VLOOKUP(search_key, range, index, [is_sorted])
```
- search_key = the Sheet 1 cell we are trying to match
@@ -28,6 +29,3 @@ VLOOKUP(search_key, range, index, [is_sorted])
- [is_sorted] = if the first column of the range is sorted, enter "true" to find the closest match; otherwise enter "false" to return exact matches only
4) You can type in the formula, or fill it out by clicking on cells, columns, and sheets as shown in the video above.
-
-{% footer %}
-{% endfooter %}
diff --git a/spreadsheet/forms/README.md b/02.9-forms.Rmd
similarity index 61%
rename from spreadsheet/forms/README.md
rename to 02.9-forms.Rmd
index d54306d6c..c85b8a5a1 100644
--- a/spreadsheet/forms/README.md
+++ b/02.9-forms.Rmd
@@ -1,6 +1,3 @@
-# Collect and Share Survey Data with Google Forms
+## Collect and Share Data with Google Forms {#forms}
**TO DO ** write simple tutorial for Google Forms and explain how to share the spreadsheet; also mention other web form services
-
-{% footer %}
-{% endfooter %}
diff --git a/find/README.md b/03-find.Rmd
similarity index 74%
rename from find/README.md
rename to 03-find.Rmd
index c235be1c2..df8a587c3 100644
--- a/find/README.md
+++ b/03-find.Rmd
@@ -1,6 +1,7 @@
-# Find and Know Your Data
+# Find and Know Your Data {#find}
+*by [Jack Dougherty](authors), last updated March 1, 2017*
-## Searching for Open Data
+#### Searching for Open Data {-}
Increasing numbers of governmental agencies and non-profit organizations are publicly sharing *open data* on the web. When starting a new data visualization project, ask yourself these questions:
- Do I have the most relevant data for my project?
@@ -9,14 +10,15 @@ Increasing numbers of governmental agencies and non-profit organizations are pub
- Which organizations might have collected data for my topic?
- Which open data repositories might have published this data?
-## What features do open repositories offer?
+#### What features do open repositories offer?
- View and export: At minimum, most open data repositories allow users to view their data and export it into common spreadsheet formats. Some also provide geographical boundaries for polygon maps.
- Built-in visualization tools: Some repositories offer built-in tools for users to create interactive charts or maps on the platform site. Some also provide code snippets for users to embed these built-in visualizations into their own websites.
- Static and Live data: Most repositories offer static datasets for a specific time period, but some also provide "live" data that is continuously updated.
- Application Programming Interface (APIs): Some repositories provide endpoints with code instructions that allow users to pull data directly from the platform into an external sites or online visualization, which is ideal for continuously updated data.
-## Know Your Data
+#### Know Your Data
Before starting to create charts or maps, get to know your data.
+
- Where did it come from?
- Who compiled the data, and for what purpose?
- What do the data labels really mean?
@@ -36,15 +38,9 @@ Closely examine your data files to understand their meaning, sources of origin,
1) Always ask: Am I using the best available data?
-Compare the HFS list to the City of Hartford’s current list of food establishments:
+- Compare the HFS list to the City of Hartford’s current list of food establishments:
https://data.hartford.gov/browse
-go to Public Health Category
-click on the “dataset” version (updated 10 Feb 2016), which is same data but different view than the “map” version
-click on light blue “export” button into any format you wish to compare with the HFS list (see screenshot)
-decide which list is best for your organization’s goal
-
-In this week’s seminar, one of our guests is Brett Flodine, who manages City of Hartford open data repository, and he can answer your questions about this data, as well as the pros/cons of his map version.
-
-
-{% footer %}
-{% endfooter %}
+- go to Public Health Category
+- click on the “dataset” version (updated 10 Feb 2016), which is same data but different view than the “map” version
+- click on light blue “export” button into any format you wish to compare with the HFS list (see screenshot)
+- decide which list is best for your organization’s goal
diff --git a/find/us/README.md b/03.1-census.Rmd
similarity index 94%
rename from find/us/README.md
rename to 03.1-census.Rmd
index 68a4342e1..de4f0be54 100644
--- a/find/us/README.md
+++ b/03.1-census.Rmd
@@ -1,4 +1,5 @@
-# United States and Census Bureau open data
+## US and Census Bureau Open Data {#census}
+*last updated March 1, 2017*
**The U.S. Census Bureau** (http://census.gov) collects and shares population, housing, and economic data on its open repositories.
- American FactFinder (http://factfinder.census.gov) provides quick facts for a specific location, or links to download more detailed datasets
@@ -18,13 +19,13 @@ Census areas are geographic divisions in this *general format*:
Common census areas, as shown in [American FactFinder download tool](http://factfinder.census.gov/faces/nav/jsf/pages/download_center.xhtml).
-
+
**TO DO** Create interactive map of hierarchical census areas in the Hartford region, with buttons to display colors as panes with z-levels
Learn more: Explore this visual interactive of US Census geographic areas and definitions (http://www.census.gov/geo/reference/webatlas/)
-See also in this book: [Geocode addresses with the US Census Geocoder](../geocode/index.html)
+See also in this book: [Geocode addresses with the US Census Geocoder](geocode)
**Social Explorer** public version (http://socialexplorer.com) is another reputable source for census and related demographic data, past and present. The platform allows users to create data maps that may be exported as static images or presentation slides. Several academic institutions subscribe to the professional version with additional features.
@@ -35,11 +36,8 @@ See also in this book: [Geocode addresses with the US Census Geocoder](../geocod
**National Center for Education Statistics (NCES)** (http://nces.ed.gov/) is the primary federal agency for collecting and reporting education data.
- Elementary/Secondary Information System (ELSi) (http://nces.ed.gov/ccd/elsi) - create custom tables and charts from the Common Core of Data (CCD) and Private School Survey
-## Boundaries
+#### Boundaries {-}
** TO DO **
- link and source files and scale
- http://mapstarter.com/
-
-{% footer %}
-{% endfooter %}
diff --git a/find/source/README.md b/03.2-source.Rmd
similarity index 81%
rename from find/source/README.md
rename to 03.2-source.Rmd
index 11226fc8e..e4fad14a9 100644
--- a/find/source/README.md
+++ b/03.2-source.Rmd
@@ -1,8 +1,9 @@
-# Source Your Data Files
+## Source Your Data Files {#source}
+*last updated March 1, 2017*
Source your data. Spell out exactly where it came from, so that someone other than you, several years in the future, could understand its origin.
-## Label the file name
+#### Label the file name {-}
Everyone has seen examples of bad file names:
- data.xls
@@ -12,15 +13,15 @@ Everyone has seen examples of bad file names:
Write a short but meaningful file name. If different versions of the data are floating around, add the current date at the end, in YYYY-MM-DD format, perhaps like this:
- town-demographics-2016-03-08.xls
-## Save source data in separate sheet
+#### Save source data in separate sheet {-}
If you have doubts when cleaning up columns, click (or right-click) on the spreadsheet tab to copy the sheet to another tab as a backup, to avoid destroying any data.
-
+
Add a *source* tab, after the data, with notes to remind you and others about its origins and when it was last updated.
-
+
** TO DO **
@@ -29,6 +30,3 @@ Source your data
- open-source and creative commons
- credit sources and collaborators on dataviz products and readme files
- Whose perspectives does your data privilege? Whose stories remain untold?
-
-{% footer %}
-{% endfooter %}
diff --git a/find/public-private/README.md b/03.3-public.Rmd
similarity index 95%
rename from find/public-private/README.md
rename to 03.3-public.Rmd
index 888eccc6d..a317f20a2 100644
--- a/find/public-private/README.md
+++ b/03.3-public.Rmd
@@ -1,4 +1,4 @@
-# Public or Private Data?
+## Public or Private Data? {#public}
Many of the free web-based tools in this book require that your publicly share your data. Check each tool and decide whether it is appropriate for your data, which may have some privacy restrictions.
@@ -12,6 +12,3 @@ In other cases, individual data is not private. For example:
- When individuals contribute to political campaigns, most US and state laws require that the donor name, address, and amount is public data.
- When an individual buys home in Connecticut, the owner's name, address, purchase amount, and other details about the home are public data.
-
-{% footer %}
-{% endfooter %}
diff --git a/find/good-bad/README.md b/03.4-know.Rmd
similarity index 93%
rename from find/good-bad/README.md
rename to 03.4-know.Rmd
index 59afd91be..b6b41ff8c 100644
--- a/find/good-bad/README.md
+++ b/03.4-know.Rmd
@@ -1,4 +1,4 @@
-# Know Your Data: Is It Good or Bad?
+## Know Your Data: Is It Good or Bad? {#know}
Before starting to create charts or maps, get to know your data.
- Where did it come from?
diff --git a/find/ct/README.md b/03.5-ct.Rmd
similarity index 58%
rename from find/ct/README.md
rename to 03.5-ct.Rmd
index aa0875844..e7e03d9f7 100644
--- a/find/ct/README.md
+++ b/03.5-ct.Rmd
@@ -1,9 +1,9 @@
-# Connecticut Open Data and Boundaries
-*By [Jack Dougherty](../../introduction/who.md), last updated April 5, 2017*
+## Connecticut Open Data {#ct}
+*last updated April 5, 2017*
Since this book was created in Hartford, Connecticut, we include state and municipal open data repositories and boundary files.
-**Connecticut Open Data** (http://data.ct.gov), the official portal for state government agencies, is hosted on the Socrata platform, which offers built-in data visualization tools and APIs. See also how to create a [filtered point map with Socrata](../../map/socrata/index.html) in this book.
+**Connecticut Open Data** (http://data.ct.gov), the official portal for state government agencies, is hosted on the Socrata platform, which offers built-in data visualization tools and APIs. See also how to create a [filtered point map with Socrata](filtered-point-map-socrata) in this book.
See also separate repositories for individual state agencies:
- Office of the State Comptroller (http://www.osc.ct.gov/openCT.html)
@@ -19,7 +19,7 @@ See also separate repositories for individual state agencies:
**Connecticut Data Collaborative** (http://ctdata.org) is a public-private partnership that advocates for open data access to drive planning, policy, budgeting and decision making in Connecticut at the state, regional and local levels. We democratize public data through custom data exploration tools and a dynamic town profile tool, hosted on the open-source CKAN platform. Users can find state and federal data on topics such as public health, education, crime, municipal data, and racial profiling data.
-**Hartford Data** (http://data.hartford.gov), the official portal of the City of Hartford municipal government, is hosted on the Socrata platform, which features built-in visualizations and APIs. See also how to create a [filtered point map with Socrata](../../map/socrata/index.html) in this book. Also, the Hartford Data site links to the City's ArcGIS Online geographic data (http://gisdata.hartford.gov/) and the City's financial data (http://checkbook.hartford.gov/) and budget (http://budget.hartford.gov/).
+**Hartford Data** (http://data.hartford.gov), the official portal of the City of Hartford municipal government, is hosted on the Socrata platform, which features built-in visualizations and APIs. See also how to create a [filtered point map with Socrata](filtered-point-map-socrata) in this book. Also, the Hartford Data site links to the City's ArcGIS Online geographic data (http://gisdata.hartford.gov/) and the City's financial data (http://checkbook.hartford.gov/) and budget (http://budget.hartford.gov/).
In addition to the official repositories above, Connecticut news organizations that create data visualizations often include links to download data files.
@@ -27,25 +27,25 @@ In addition to the official repositories above, Connecticut news organizations t
**Hartford Courant Data Desk** (http://www.courant.com/data-desk) produces digital visualizations for the *Hartford Courant*, the largest daily newspaper in Connecticut, owned by Tribune Publishing. Many of these data visualizations are published on the Tableau platform, which allows readers to download the underlying data.
-## Boundaries
+#### Boundaries {-}
- Converted from shapefile WGS84 to GeoJSON format
- To download a GeoJSON file, right-click the link and Save to your computer
- If you accidentally open the GeoJSON code in your browser, select File > Save Web Page to download it
- To view or edit, drag files into http://geojson.io or http://mapshaper.org
-- Learn more in the [Transform Your Map Data](../../transform) chapter of this book
+- Learn more in the [Transform Your Map Data](transform.html) chapter of this book
| Geography | Year-Source-Size | Right-click + Save to download GeoJSON |
| :-------- | :------ | :----- | :----- |
-| CT outline  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries)| [ct-outline.geojson](https://www.datavizforall.org/find/ct/ct-outline.geojson) |
-| CT counties  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries)| [ct-counties.geojson](https://www.datavizforall.org/find/ct/ct-counties.geojson) |
-| CT towns  | [2010 Census UConn MAGIC WGS84 simplified to 224k](http://magic.lib.uconn.edu/connecticut_data.html#boundaries)| [ct-towns.geojson](https://www.datavizforall.org/find/ct/ct-towns.geojson) |
-| CT census tracts  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries)| [ct-tracts-2010.geojson](https://www.datavizforall.org/find/ct/ct-tracts-2010.geojson) |
-| Hartford County outline  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries) | [hartfordcounty-outline.geojson](https://www.datavizforall.org/find/ct/hartfordcounty-outline.geojson) |
-| Hartford County towns  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries) | [hartfordcounty-towns.geojson](https://www.datavizforall.org/find/ct/hartfordcounty-towns.geojson) |
-| Hartford County tracts  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries) | [hartfordcounty-tracts-2010.geojson](https://www.datavizforall.org/find/ct/hartfordcounty-tracts-2010.geojson) |
-| Hartford outline  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries) | [hartford-outline.geojson](https://www.datavizforall.org/find/ct/hartford-outline.geojson) |
-| Hartford census tracts  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries) | [hartford-tracts-2010.geojson](https://www.datavizforall.org/find/ct/hartford-tracts-2010.geojson) |
-| Hartford neighborhoods  | [2015 Hartford Open Data 1:50,000](http://gisdata.hartford.gov/datasets/d3deb11bfd9242ce9c927187c512da9e_5) | [hartford-neighborhoods.geojson](https://www.datavizforall.org/find/ct/hartford-neighborhoods.geojson) |
+| CT outline  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries)| [ct-outline.geojson](data/ct-outline.geojson) |
+| CT counties  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries)| [ct-counties.geojson](data/ct-counties.geojson) |
+| CT towns  | [2010 Census UConn MAGIC WGS84 simplified to 224k](http://magic.lib.uconn.edu/connecticut_data.html#boundaries)| [ct-towns.geojson](data/ct-towns.geojson) |
+| CT census tracts  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries)| [ct-tracts-2010.geojson](data/ct-tracts-2010.geojson) |
+| Hartford County outline  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries) | [hartfordcounty-outline.geojson](data/hartfordcounty-outline.geojson) |
+| Hartford County towns  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries) | [hartfordcounty-towns.geojson](data/hartfordcounty-towns.geojson) |
+| Hartford County tracts  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries) | [hartfordcounty-tracts-2010.geojson](data/hartfordcounty-tracts-2010.geojson) |
+| Hartford outline  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries) | [hartford-outline.geojson](data/hartford-outline.geojson) |
+| Hartford census tracts  | [2010 Census UConn MAGIC WGS84 1:100,000](http://magic.lib.uconn.edu/connecticut_data.html#boundaries) | [hartford-tracts-2010.geojson](data/hartford-tracts-2010.geojson) |
+| Hartford neighborhoods  | [2015 Hartford Open Data 1:50,000](http://gisdata.hartford.gov/datasets/d3deb11bfd9242ce9c927187c512da9e_5) | [hartford-neighborhoods.geojson](data/hartford-neighborhoods.geojson) |
**TO DO**
- add Capitol Region Council of Governments (CRCOG) http://www.crcog.org/
@@ -53,6 +53,3 @@ In addition to the official repositories above, Connecticut news organizations t
- add Capitol Region Education Council (CREC) http://www.crec.org/
- add school attendance areas from federal site
- describe Freedom of Information Act (FOIA) data requests in Connecticut
-
-{% footer %}
-{% endfooter %}
diff --git a/clean/README.md b/04-clean.Rmd
similarity index 78%
rename from clean/README.md
rename to 04-clean.Rmd
index 2090f3685..93898d3e7 100644
--- a/clean/README.md
+++ b/04-clean.Rmd
@@ -1,14 +1,11 @@
-# Clean Up Messy Data
+# Clean Up Messy Data {#clean}
+*By [Jack Dougherty](authors), last updated April 2016*
-*By [Jack Dougherty](../../introduction/who.md), last updated April 16, 2016*
+TO DO
-**TO DO**
- write a new intro to match content that I moved into subfolders
- http://trendct.org/2015/08/28/getting-rid-of-duplicate-rows-using-google-sheets/
- Clean up data that contains stray commas, or mistyped entries
- Advanced clean up with Open Refine; see Alvin Chang's CT Mirror guide http://trendct.org/2015/04/24/john-jonathan-and-johnny-how-to-merge-them-in-open-refine/
- rethink formatting data
- see Jake Kara’s “Data Structure Whining” https://github.com/jakekara/publishing-data-for-journalists
-
-{% footer %}
-{% endfooter %}
diff --git a/clean/spreadsheets/README.md b/04.1-clean-spreadsheets.Rmd
similarity index 81%
rename from clean/spreadsheets/README.md
rename to 04.1-clean-spreadsheets.Rmd
index 777352c35..655c1039f 100644
--- a/clean/spreadsheets/README.md
+++ b/04.1-clean-spreadsheets.Rmd
@@ -1,23 +1,25 @@
-# Clean Messy Data with Spreadsheet Tools
-*By [Jack Dougherty](../../introduction/who.md), last updated April 16, 2016*
+## Clean Data with Spreadsheets {#clean-spreadsheets}
+*last updated April 16, 2016*
**TO DO** reorganize this to feature Google Sheets whenever possible, or Excel Online if needed
Sometimes we receive a spreadsheet with problematic data that needs to be cleaned up before we can successfully upload it into a visualization tool.
-## Find and Replace with a blank
+#### Find and Replace with a blank {-}
A common problem with census data is that geographic names contain unnecessary words. For example, when downloading Connecticut county subdivisions (towns), each row appears as:
+
- Andover town
- Ansonia town
- Ashford town
Our goal is to remove the word "town" from each row, to produce a clean spreadsheet that we can match with other data, like this:
+
- Andover
- Ansonia
- Ashford
-Here's one quick solution: In any spreadsheet tool, use the Find and Replace command to remove unwanted characters. Try it! Click this link and Save to download to your computer:[find-replace-town-geonames in CSV format](https://www.datavizforall.org/clean/spreadsheets/find-replace-town-geonames.csv). This tutorial shows screens from Excel, but other tools are very similar.
+Here's one quick solution: In any spreadsheet tool, use the Find and Replace command to remove unwanted characters. Try it! Click this link and Save to download to your computer:[find-replace-town-geonames in CSV format](data/find-replace-town-geonames.csv). This tutorial shows screens from Excel, but other tools are very similar.
1. Open the Find and Replace command.
@@ -27,13 +29,13 @@ Here's one quick solution: In any spreadsheet tool, use the Find and Replace com
4. Press the Replace All button. Since this sample file lists 169 towns, the screen will states that 169 instances of "town" have been replaced.
-
+
-## Split one column into two with Excel
+#### Split one column into two with Excel {-}
One common problem is when multiple pieces of data appear in one column, and your goal is to split them into separate columns. If those data pieces are separated by commas (or similar punctuation), you might be able to fix this with a simple spreadsheet command: split text into columns.
-Try it! Click this link and Save to download to your computer: [split-coordinate-pairs in CSV format](https://www.datavizforall.org/clean/spreadsheets/split-coordinate-pairs.csv), and open with Excel. (**TO DO** test with other spreadsheet tools)
+Try it! Click this link and Save to download to your computer: [split-coordinate-pairs in CSV format](data/split-coordinate-pairs.csv), and open with Excel. (**TO DO** test with other spreadsheet tools)
1. Select the data column you wish to split.
@@ -47,13 +49,13 @@ Try it! Click this link and Save to download to your computer: [split-coordinate
The coordinate pairs column is now split into two separate columns. Relabel the headers: longitude and latitude.
-Animated example from Excel for Windows (thanks @f3mlat):
+Animated example from Excel for Windows (thanks `@f3mlat`):
-
+
**TO DO** write directions to split a single address cell "300 Summit St, Hartford CT 06106" into separate columns for address, city, state, zip
-## Combine separate data columns into one
+#### Combine separate data columns into one {-}
Another common data cleaning problem is when you receive address data in separate columns, like this:
@@ -71,26 +73,22 @@ One easy solution is to write a simple spreadsheet formula to combine (or concat
- =A2 &" " & B2 &" " &C2 &" " &D2
-
+
**TO DO**
- Confirm that Google Fusion Tables geocoder does not require commas between terms
- Clarify what happens with zip code in the example above
-## Convert Connecticut town names with CTNamecleaner
+#### Convert Connecticut town names with CTNamecleaner {-}
In Connecticut, residents often list their village or neighborhood names in their address, but these do not necessarily match the official list of 169 Connecticut town governments (called county subdivisions by the US Census). For example, the Elmwood neighborhood is located in the town of West Hartford, and the Rockville village is located in the town of Vernon.
To solve this problem, the data experts at TrendCT/CT Mirror have openly shared a wonderful tool to convert village/neighborhood names into official towns, called CTNamecleaner.
-
+
1. Open CTNamecleaner with your browser at http://shiny.trendct.org/ctnamecleaner/
-2. Upload a CSV generic spreadsheet. Learn more [about CSV format](../csv/) in this book.
+2. Upload a CSV generic spreadsheet. Learn more about CSV format in this book **TO DO add link**.
3. Select the data column to be converted into town names, and download the results.
Learn more about [CTNamecleaner on GitHub](https://github.com/trendct/ctnamecleaner), and view the [underlying list of Connecticut place names in a public Google sheet](https://docs.google.com/spreadsheets/d/1WqZIGk2AkHXKYvd4uXy5a2nwyg529e7mMU5610Ale0g/edit#gid=0).
-
-
-{% footer %}
-{% endfooter %}
diff --git a/clean/open-refine/README.md b/04.2-open-refine.Rmd
similarity index 70%
rename from clean/open-refine/README.md
rename to 04.2-open-refine.Rmd
index b5bf2f70c..49fefd401 100644
--- a/clean/open-refine/README.md
+++ b/04.2-open-refine.Rmd
@@ -1,6 +1,3 @@
-# Clean Messy Data with Open Refine
+## Clean Data with Open Refine {#open-refine}
-**TO DO ** show basic tutorial with Open Refine; link to Alvin Chang's fabulous [Open Refine tutorial in CT Mirror](http://trendct.org/2015/04/24/john-jonathan-and-johnny-how-to-merge-them-in-open-refine/)
-
-{% footer %}
-{% endfooter %}
+**TO DO ** show basic tutorial with Open Refine; link to Alvin Chang's fabulous [Open Refine tutorial in CT Mirror](http://trendct.org/2015/04/24/john-jonathan-and-johnny-how-to-merge-them-in-open-refine/)
diff --git a/clean/ctnamecleaner/README.md b/04.3-ctnamecleaner.Rmd
similarity index 79%
rename from clean/ctnamecleaner/README.md
rename to 04.3-ctnamecleaner.Rmd
index 7d538e9f8..b6f632f7e 100644
--- a/clean/ctnamecleaner/README.md
+++ b/04.3-ctnamecleaner.Rmd
@@ -1,8 +1,7 @@
-# Fix Connecticut Town Names with CTNamecleaner
+## Fix Connecticut Town Names with CTNamecleaner {#ctnamecleaner}
+*last updated April 16, 2016*
-*By [Jack Dougherty](../../introduction/who.md), last updated April 16, 2016*
-
-**TO DO** update this page
+**TO DO** update this page; avoid duplication in main chapter text
Here's a wonderful data-cleaning tool that's specific to Connecticut, but the idea (and open-source code from TrendCT/CT Mirror) may inspire others to create similar tools for other locations.
@@ -10,13 +9,10 @@ In Connecticut, residents often list their village or neighborhood names in thei
To solve this problem, the data experts at TrendCT/CT Mirror have openly shared a wonderful tool to convert village/neighborhood names into official towns, called CTNamecleaner.
-
+
1. Open CTNamecleaner with your browser at http://shiny.trendct.org/ctnamecleaner/
-2. Upload a CSV generic spreadsheet. Learn more [about CSV format](../csv/) in this book.
+2. Upload a CSV generic spreadsheet. Learn more about CSV format in this book **TO DO** fix link
3. Select the data column to be converted into town names, and download the results.
Learn more about [CTNamecleaner on GitHub](https://github.com/trendct/ctnamecleaner), and view the [underlying list of Connecticut place names in a public Google sheet](https://docs.google.com/spreadsheets/d/1WqZIGk2AkHXKYvd4uXy5a2nwyg529e7mMU5610Ale0g/edit#gid=0).
-
-{% footer %}
-{% endfooter %}
diff --git a/05-chart.Rmd b/05-chart.Rmd
new file mode 100644
index 000000000..c134d0419
--- /dev/null
+++ b/05-chart.Rmd
@@ -0,0 +1,33 @@
+# Chart Your Data {#chart}
+*by [Jack Dougherty](authors), last updated March 21, 2017*
+
+Charts pull readers deeper into your story. Even if your data contains geographical information, sometimes a chart tells your story better than a map. But designing meaningful, interactive charts requires careful thought about how to communicate your data story with your audience. In this chapter, you will learn how to:
+
+- Practice [principles of chart design](chart-design). Learn to identify good charts from bad ones.
+- Choose a chart type that matches your story and data format, and follow tutorials in the table below. Beginners may start with easy-to-learn tools such as [Google Sheets](chart-google-sheets) or [Tableau Public](tableau-public), then move up to more powerful tools, such as [Highcharts](highcharts), which require you to [Modify and Host Code Templates with GitHub](github) or another web host.
+
+See also related chapters in this book:
+
+- [Draw and write your data story](draw) to capture your ideas on paper
+- [Improve spreadsheet skills](spreadsheet), [Find and know your data](find), and [Clean your data](clean)
+- [Embed your interactive chart on your website](embed)
+- [Detect bias in data stories](detect), including [How to lie with charts](how-to-lie-with-charts)
+- [Tell your data story](story), including its most meaningful insights and limitations
+
+| Basic chart types | Best use and tutorial chapters |
+| --- | --- |
+| Grouped column or bar  | Best to compare categories side-by-side. Vertical columns, or horizontal bars for long labels. Easy tool: [Google Sheets bar and column tutorial](column-bar-google) Power tool: [Highcharts templates](highcharts) |
+| Separated column or bar  | Best to compare categories in separate clusters. Vertical columns, or horizontal bars for long labels. Easy tool: [Google Sheets bar and column tutorial](column-bar-google) Power tool: [Highcharts templates](highcharts) |
+| Stacked column or bar  | Best to compare sub-categories, or parts of a whole. Vertical columns, or horizontal bars for long labels. Easy tool: [Google Sheets bar and column tutorial](column-bar-google) Power tool: [Highcharts templates](highcharts) |
+| Histogram  | Best to show distribution of raw data, with number of values in each bucket. Easy tool: [Google Sheets bar and column tutorial](column-bar-google) Power tool: [Highcharts templates](highcharts) |
+| Pie chart  | Best to show parts of a whole, but hard to estimate size of slices. Easy tool: [Google Sheets pie chart tutorial](pie-line-area-google) Power tool: [Highcharts templates](highcharts) |
+| Line chart  | Best to show continuous data, such as change over time. Easy tool: [Google Sheets line chart tutorial](pie-line-area-google) Power tool: [Highcharts templates](highcharts) |
+| Filtered line chart  | Best to show multiple lines of continuous data, with on-off toggle buttons. Easy tool: [Tableau Public filtered line chart tutorial](filtered-line-chart-tableau) |
+| Stacked area chart  | Best to show parts of a whole, with change over time. Easy tool: [Google Sheets stacked area tutorial](pie-line-area-google) Power tool: [Highcharts templates](highcharts) |
+| Scatter chart  | Best to show relationship between two sets of data. Also called an XY chart. Easy tool: [Google Sheets scatter chart tutorial](scatter-bubble-google) or [Tableau Public scatter chart tutorial](scatter-chart-tableau) Power tool: [Highcharts templates](highcharts) |
+| Bubble chart  | Best to show relationship between three or four sets of data, using bubble size and color. Easy tool: [Google Sheets bubble chart tutorial](scatter-bubble-google) Power tool: [Highcharts templates](highcharts) |
+
+#### For more advanced chart types and tutorials {-}
+- [Google Sheets Chart types help page](https://support.google.com/docs/answer/190718)
+- [Tableau Public resources page](https://public.tableau.com/en-us/s/resources)
+- [Highcharts demo page](http://www.highcharts.com/demo)
diff --git a/chart/design/README.md b/05.01-chart-design.Rmd
similarity index 84%
rename from chart/design/README.md
rename to 05.01-chart-design.Rmd
index 350bf904f..e40a98b1d 100644
--- a/chart/design/README.md
+++ b/05.01-chart-design.Rmd
@@ -1,5 +1,5 @@
-# Chart Design Principles
-*by [Jack Dougherty](../../introduction/who.md), last updated March 9, 2017*
+## Chart Design Principles {#chart-design}
+*last updated March 9, 2017*
Spot the difference between good and bad charts, based on this compilation of design principles from leading experts, with citations listed below to learn more.
@@ -7,17 +7,17 @@ Spot the difference between good and bad charts, based on this compilation of de
2) Before you begin, ask yourself: Do I really need a chart to tell this data story? Or would a table or text alone do a better job?
-3) Decide if the best way to communicate with your audience is with static charts (such as images printed on paper) or interactive charts (embedded in a website, with tooltip details and source links). Most of these principles apply to both types, but [this book features tools and tutorials](../../chart) to create interactive charts.
+3) Decide if the best way to communicate with your audience is with static charts (such as images printed on paper) or interactive charts (embedded in a website, with tooltip details and source links). Most of these principles apply to both types, but [this book features tools and tutorials](chart) to create interactive charts.
4) Understand basic chart vocabulary: title, labels, horizontal x-axis and vertical y-axis, data series, tooltip, source and credits. *image to come*
-5) Identify the [chart type](../../chart) that best matches your story and data format.
+5) Identify the [chart type](chart) that best matches your story and data format.
6) Draw visual comparisons that are easy for readers to understand, rather than confusing them (adapted from Gourley p. 19). *image to come*
7) Do the math for your readers. Based on your data story, decide if you should show absolute numbers, percentages, or percent change (Wong pp. 23-25, 104-107). *image and link to come*
-8) Order categories logically -- either alphabetically, by value, or sequentially -- depending on your data story (Gourley, p. 19; Wong pp. 70-71). *image to come*
+8) Order categories logically---either alphabetically, by value, or sequentially---depending on your data story (Gourley, p. 19; Wong pp. 70-71). *image to come*
9) For long labels, use horizontal bar charts instead of vertical column charts (Wong p. 66). *image to come*
@@ -35,9 +35,9 @@ Spot the difference between good and bad charts, based on this compilation of de
14) On static charts, label items directly when possible. (On interactive charts, designers may need to rely on tooltips and text.) Insert a legend in a logical place for readers (Wong, p. 56).
-15) Add source credits and bylines -- with links to view data tables and details -- to build credibility and accountability.
+15) Add source credits and bylines---with links to view data tables and details---to build credibility and accountability.
-16) Avoid “chart junk” -- such as 3D perspective, shadows, and unnecessary ornaments -- which distract readers from your data story. Never use 3D unless you are plotting three-dimensional data (Tufte p. *to come*, Wong p. 62, Knaflic p. 65). *image to come*
+16) Avoid “chart junk”--such as 3D perspective, shadows, and unnecessary ornaments---which distract readers from your data story. Never use 3D unless you are plotting three-dimensional data (Tufte p. *to come*, Wong p. 62, Knaflic p. 65). *image to come*
17) De-clutter charts (Knaflic pp. 91-98, 130-135).
@@ -47,9 +47,9 @@ Spot the difference between good and bad charts, based on this compilation of de
- Use contrast (such as color vs gray) to call attention to your data story (Knaflic pp. 87-88)
- *image to come*
-See also [Map Design Principles](../../map/design) and [Tell Your Data Story](../../story) chapters in this book.
+See also [Map Design Principles](map-design) and [Tell Your Data Story](story) chapters in this book.
-## Learn more
+#### References {-}
Stephanie D. H. Evergreen, Effective Data Visualization: The Right Chart for the Right Data, (Los Angeles: SAGE Publications, Inc, 2016)
diff --git a/chart/google-sheets/README.md b/05.02-chart-google-sheets.Rmd
similarity index 66%
rename from chart/google-sheets/README.md
rename to 05.02-chart-google-sheets.Rmd
index 2ca61c4b3..097f1ab02 100644
--- a/chart/google-sheets/README.md
+++ b/05.02-chart-google-sheets.Rmd
@@ -1,9 +1,9 @@
-# Google Sheets Charts
-*By [Jack Dougherty](../../introduction/who.md), last updated February 12, 2017*
+## Google Sheets Charts {#chart-google-sheets}
+*last updated February 12, 2017*
Use Google Sheets (http://sheets.google.com), an easy drag-and-drop tool, to create basic interactive charts that you can embed in your website.
-## Tool Review
+#### Tool Review {-}
- Pros:
- Free and easy-to-learn tool on the collaborative Google Drive platform.
- Edit, share, and publish interactive charts from your data, all in one spreadsheet.
@@ -13,20 +13,17 @@ Use Google Sheets (http://sheets.google.com), an easy drag-and-drop tool, to cre
- Bubble charts cannot show small, uniform bubbles.
- Cannot cite or link to source data inside the chart.
- Cannot add annotations to highlight items inside charts.
- - For more powerful tools that require more skills, see tutorials in this book on [Tableau Public](../scatter-chart-tableau/) and [Highcharts](../../highcharts/).
+ - For more powerful tools that require more skills, see tutorials in this book on [Tableau Public](scatter-chart-tableau/) and [Highcharts](highcharts).
-## Tutorials
+#### Tutorials {-}
Follow the Google Sheet Chart tutorials in this book to create:
-- [Column and Bar Charts](../column-bar-google)
+- [Column and Bar Charts](column-bar-google)
- Grouped
- Separated
- Stacked
- Histograms
-- [Pie, Line and Area Charts](../pie-line-area-google)
-- [Scatter and Bubble Charts](../scatter-bubble-google)
+- [Pie, Line and Area Charts](pie-line-area-google)
+- [Scatter and Bubble Charts](scatter-bubble-google)
-## Learn more
+#### Learn more {-}
- [Google Sheet chart types help page](https://support.google.com/docs/answer/190718)
-
-{% footer %}
-{% endfooter %}
diff --git a/chart/column-bar-google/README.md b/05.03-column-bar-google.Rmd
similarity index 83%
rename from chart/column-bar-google/README.md
rename to 05.03-column-bar-google.Rmd
index 9d72b8c87..d84df7567 100644
--- a/chart/column-bar-google/README.md
+++ b/05.03-column-bar-google.Rmd
@@ -1,13 +1,14 @@
-# Column and Bar Charts with Google Sheets
-*By [Jack Dougherty](../../introduction/who.md), last updated April 4, 2017*
+## Column and Bar Charts with Google Sheets {#column-bar-google}
+*last updated April 4, 2017*
+
+Follow these tutorials to create different types of column and bar charts with Google Sheets on the Google Drive platform. Requires free account.
-Follow these tutorials to create different types of column and bar charts with Google Sheets http://sheets.google.com on the Google Drive platform. Requires free account.
- Grouped
- Separated
- Stacked
- Histograms
-## Grouped Column and Bar Charts
+#### Grouped Column and Bar Charts {-}
Best to compare categories side-by-side. Vertical columns, or horizontal bars for long labels.
**Try it:** This grouped column chart shows differences in obesity between men and women in each age bracket. Float your cursor over columns to view data details.
@@ -22,35 +23,35 @@ Best to compare categories side-by-side. Vertical columns, or horizontal bars fo
3) Select File > Make a Copy to save your own version to your Google Drive.
-
+
4) To remove the current chart from your copy of the spreadsheet, select it and press the delete.
5) Format your data in a similar way as shown below. Each row is a data series, which displays as a separate color in the chart.
-
+
6) Use your cursor to select only the data you wish to chart, then select Insert > Chart.
-
+
7) In the Chart Editor > Recommendations tab, choose your preferred Column chart (or horizontal Bar chart for longer labels), or see more options in Chart Types tab. Press the Insert button.
-
+
8) To customize title, labels, and more, click the editing controls in the upper-right corner.
-
+
9) To make your data public, select the blue Share button > Advanced, then Change from Private to Public On the Web, with Anyone Can View.
-
+
-10) To embed your chart in another website, click the upper-right chart editing controls, select Publish Chart, select Embed, and press the Publish button. Copy the iframe code and see the [Embed on Your Web](http://www.datavizforall.org/embed/) chapter in this book.
+10) To embed your chart in another website, click the upper-right chart editing controls, select Publish Chart, select Embed, and press the Publish button. Copy the iframe code and see the [Embed on Your Web](embed.html) chapter in this book.
11) Reminder: Currently, there is no easy way to cite or link to your source data inside a Google Sheets chart. Instead, cite and link to your source data in the text of the web page, as shown in the example at the top.
-## Separated Column and Bar Charts
+#### Separated Column and Bar Charts {-}
Best to compare categories in separate clusters. Vertical columns, or horizontal bars for long labels.
**Try it:** This separated bar chart shows calorie counts of fast food items, separated by restaurant chains. The horizontal bar offers more space for longer labels. Float your cursor over bars to explore data details.
@@ -65,11 +66,11 @@ Best to compare categories in separate clusters. Vertical columns, or horizontal
3) Format your data in a similar way as shown below. Each column is a data series, which displays as a separate color in the chart.
-
+
4) In the Chart Editor > Recommendations tab, choose your preferred Bar chart, or see more options in Chart Types tab.
-## Stacked Column and Bar Charts
+#### Stacked Column and Bar Charts {-}
Best to compare sub-categories, or parts of a whole. Vertical columns, or horizontal bars for long labels.
**Try it:** This stacked column chart compares the percentage of overweight residents across nations. Float your cursor over columns to view data details.
@@ -84,11 +85,11 @@ Best to compare sub-categories, or parts of a whole. Vertical columns, or horizo
3) Format your data in a similar way as shown below. Each column is a data series, which displays as a separate color in the chart.
-
+
4) In the Chart Editor > Recommendations tab, choose Stacked column chart (or Stacked bar chart if you prefer a horizontal orientation), or see more options in Chart Types tab.
-## Histograms
+#### Histograms {-}
Best to show the distribution of raw data, with number of values in each bucket. Typically displayed in vertical columns.
**Try it** to come*
@@ -98,6 +99,3 @@ Best to show the distribution of raw data, with number of values in each bucket.
- Format data into two columns
- data labels in the first column
- numeric values in second column
-
-{% footer %}
-{% endfooter %}
diff --git a/chart/pie-line-area-google/README.md b/05.04-pie-line-area-google.Rmd
similarity index 84%
rename from chart/pie-line-area-google/README.md
rename to 05.04-pie-line-area-google.Rmd
index 75159cfe4..4910ef51e 100644
--- a/chart/pie-line-area-google/README.md
+++ b/05.04-pie-line-area-google.Rmd
@@ -1,14 +1,14 @@
-# Pie, Line, and Area Charts with Google Sheets
-*By [Jack Dougherty](../../introduction/who.md), last updated February 12, 2017*
+## Pie, Line, and Area Charts with Google Sheets {#pie-line-area-google}
+*last updated February 12, 2017*
-## Pie Chart
+#### Pie Chart {-}
Best to show parts of a whole, but hard to estimate size of slices.
Try it -- to come
Tutorial - to come
-## Line Chart
+#### Line Chart {-}
Best to show change over time with continuous data.
**Try it:** In this line chart, the level of chicken (shown in orange) rises steadily and surpasses beef (red) and pork (blue). Float your cursor over lines to view data details.
@@ -16,13 +16,14 @@ Best to show change over time with continuous data.
**Tutorial:**
+
- Begin by opening this link in a new tab: [Google Sheet Line chart template](https://docs.google.com/spreadsheets/d/1wkWxxZ2-N5hqkcp7in8bxwdEcT1-XMnt1A8qUXxUSjw/)
- Follow most of the same steps in first tutorial above.
- Format your data in a similar way as shown below. Each column is a data series, which displays as a separate color in the chart.
-
+
- In the Chart Editor > Recommendations tab, choose Line chart, or see more options in Chart Types tab.
-## Stacked Area Chart
+#### Stacked Area Chart {-}
Best to show part-to-whole relationships that change over time.
**Try it:** to come
diff --git a/chart/scatter-bubble-google/README.md b/05.05-scatter-bubble-google.Rmd
similarity index 86%
rename from chart/scatter-bubble-google/README.md
rename to 05.05-scatter-bubble-google.Rmd
index fd59c37fd..23770ba84 100644
--- a/chart/scatter-bubble-google/README.md
+++ b/05.05-scatter-bubble-google.Rmd
@@ -1,8 +1,9 @@
-# Scatter and Bubble Charts with Google Sheets
+## Scatter and Bubble Charts with Google Sheets {#scatter-bubble-google}
+*Last updated Spring 2017*
Follow these tutorials to create different types scatter and bubble charts with [Google Sheets](http://sheets.google.com)
-## Scatter chart
+#### Scatter chart {-}
Best to show relationships between two series of data. Also called an XY chart, because each point represents a coordinate value plotted along the horizontal x-axis and the vertical y-axis.
**Try it:** This scatter chart reveals a downward slope: nations with lower fertility also tend to have higher life expectancy. But remember that a data correlation does not necessarily show causation. Float your cursor over points to view data details. However, the Google Sheet scatter chart only displays static labels for each country, rather than interactive tooltips. See alternative tools below.
@@ -10,16 +11,17 @@ Best to show relationships between two series of data. Also called an XY chart,