Book Bans in the U.S. during the 2021-2022 School Year

My current research question is looking at the overall story behind censorship of books in libraries and classrooms during the trend of political, religious, and parental organizations banning books in the aftermath of the Black Lives Matter movement. What are the top 10 books are being banned from July 1, 2021 to June 30, 2022? Which authors were being banned against the most? Where did the most bans occur geographically across the U.S.?

Librarians, bibliophiles, and children of the future and present would benefit from an answer to this research topic because books open up new worlds for growing learners. Some children only have limited access to the books that are in their public libraries or classrooms, and the censorship of such books affects how they learn about certain topics, such as racism and sexual abuse. Additionally, people who are interested in reflecting how certain books changed their lives in any form may be able to relate to this. In my own childhood, books were one of the avenues that gave me perspective in viewing the world in a nuanced light. It’s a political subject of gray area: how do we determine when children should/can learn about these topics? 

I am using the dataset titled “Pen America’s Index of School Book Bans (July 1, 2021 – June 30, 2022)”, which was procured through the “Data is Plural – Structured Archive” link found within Datasets webpage of the “Introduction to Data Visualization” Academic Commons website. Here is the dataset: PEN America’s Index of School Book Bans (July 1, 2021 – June 30, 2022)  I downloaded the CSV file from the publicly shared Google Sheets document. It contains 3 sheets: Sorted by Author & Title, Sorted by State and District, and Methodology. The first sheet, “Sorted by Author & Title” is formatted with the following columns in consecutive (left to right) order: Author, Title, Type of Ban, Secondary Author, Illustrator(s), Translator(s), State, District, Date of Challenge/Removal, Origin of Challenge.

The Tableau story opens up with a personal reflection in order to hook the audience with some warm memories with books. 

I tried joining data on the names of the school districts from the Public School District File for 2021-2022 from The National Center for Education Statistics, as this dataset contained the latitude and longitude that would be necessary for mapping spatial data. However, only approximately 50 school bans showed up on the table, probably due to different school district names being used on each dataset. Another limitation was being unable to find a dataset with authors, their ethnicities, their gender, and their headshot images.More complex next steps would include cleaning the dataset, “Pen America’s Index of School Book Bans (July 1, 2021 – June 30, 2022)”. I would make sure that the school district names matched with those listed in the Public School District File for 2021-2022 from The National Center for Education Statistics. Additionally, I would look for a method to compile a dataset about the banned books, authors, and various metadata.


Trying New Activities

Does trying new things, or doing anything that deviates from my established practices of habit, improve my wellness? Additionally, does the answer to the question, “How are you?” affect the number and duration of new activities? Do I gravitate towards planned or spontaneous new activities? I drew my inspiration for these questions from Giorgia Lupi and Stefanie Posavec’s Dear Data project, specifically “week 43”.

I am the primary audience for my work, but I also anticipate interest from my family and friends, as well as people who would like to do activities that veer off from their typical schedules. I am a human who generally follows an unvarying routine, but daydreams about doing “out-of-the-ordinary” activities to improve my sense of fulfillment. This project self-servingly explores how trying new things affects the eight dimensions of my wellness (mental, physical, social, vocational, financial, spiritual, environmental, and intellectual). As a person who has social anxiety and dysthymia (persistent depressive disorder), I would like to discover which new activities I gravitate toward that provide fulfillment.

I collected data from Monday (March 27) to Friday (March 31) using a small notebook and pen. Originally, I tried to carry the notebook with me wherever I went, but my own limitation of forgetfulness prevented me from doing so. Thus, I wrote down some details from memory, which has been affected by a past concussion. I wrote the action I took that deviated from my normal routine, the location where it took place, the duration of time I took to complete the action, the time I finished the action, the emotions I felt, and which dimension/s of wellness this action belongs to. Also, I rated the level of difficulty of completing the action, and noted the qualitative reason behind the action’s difficulty. Additionally, I used a Likert scale to rate the following: “I strongly feel that this activity has improved the dimension of wellness it was categorized by.” and “This action has genuinely given me a sense of fulfillment.”

From the visualizations, approximately 73% of the new activities were completed at home, and the locations of the rest of the activities were split evenly between Bayside and Flushing. Additionally, it appears that my poor physical and mental health on Wednesday affected the duration and number of activities.

Kindly use the following link to my Public Tableau site for increased viewing quality:

Across all the visualizations, I used the “Ink Free” font to convey a handwritten aesthetic. I chose to make a pie chart to show the distribution of the locations where the new activities happened. The tree map was made to show the distribution of dimensions of wellness. I used the tooltips to provide some textured details. One limitation of this project is not being able to make the Likert scale visualization with my collected data, due to not finding a suitable online tutorial with a similar dataset. I tried to add PNG icons into my tree map from The Noun Project, but I wasn’t able to able to find the icons I saved in the Repository folder.

Additionally, I was unsure of how to transfer the knowledge from Lab 7 to organize my dataset to make stacked bar charts across the weekdays. Another limitation is not making a visualization to convey which activities provided the highest rating of fulfillment. Also, I intentionally binned the activities into one dimensions of wellness each, even though some activities could fall under two or more. Finally, the last limitation I noted was not knowing how to make a story with several different data sources. I could not drag a sheet from one file to another file where I intended to make a story. Next steps would include making the aforementioned visualizations.



Project 1

NYC 311 Air Quality Complaints

Which NYC boroughs and zip codes have the most air quality complaints from 2010 to 2012?

Regarding this research question, my audience would include NYC residents and the following NYC Departments: Department of Housing Preservation and Development, Department of Health and Mental Hygiene, and the Department of Environmental Protection. Air quality matters because it influences people’s physical and holistic health. The following are my personal motivations for the question: my own experiences as having childhood asthma, which may have been influenced by the air quality, and my paranoia regarding the fine particles and fumes from various sources (e.g. secondhand and thirdhand smoke, health aftereffects of 9/11, construction projects) that are in the air we breathe.

Lastly, the health complications of the plan to demolish Manhattan Detention Complexes in Chinatown, NYC to build a new megajail has personally weighed on my mind, as I am emotionally and culturally connected with its community, and there is great concern regarding the release of asbestos in both buildings as the plan is put into action, as well as the Volatile Organic Compounds (VOCs), Polychlorinated biphenyls (PCBs), and heavy metals detected in the soil below. By better understanding where air quality complaints spatially congregate, the named NYC Departments can better focus their resources on those areas.

Kindly use the following link to my Public Tableau site for increased viewing quality:






The zipcodes with the most air quality complaints from 2010 to 2012 are all located in Manhattan: 10025 (Upper West Side), 10024 (Manhattan Valley), and 10003 (East Village).

This section should illustrate what you did and why you did it. Why did you choose the type of chart/graph/visualization that you did? How does that choice best represent the data and address your question? Through this explanation, you will illustrate that the decisions you made were intentional and how they contribute to the project. You should also explain any limitations you encountered and any subsequent compromises you made with the data or your design.

Honestly, I chose to use the dot density maps because I did not know how to create a heat map with number of complaints and zip code interactivity, which was in my original proposal. The line graph with small multiples was created to convey which borough has the most air quality complaints, while the bar graph was made to show which zip codes (and boroughs) had the most air quality complaints.

An essential limitation that hindered me from addressing the research question was the slow speed of my computer and its tendency to crash when working with large amounts of data. The computer was not capable of downloading air complaint data from 2010 to 2022, so the lower sample size that I was able to download from 2010 to 2012 may undermine the validity of the study. Additionally, I had technical trouble with lowering the size of the dots within the map, “Air Quality Complaints by Borough”, as the size slider seemed to not work. 

An alteration in scope I would make if I was able to attain access to a computer that could handle large amounts of data is increasing the scope of 311 data from January 1, 2010 12:00 AM to December 31, 2022 11:59 PM. Unfortunately, 311 data is not available from the 1990-2009, as it would have been helpful to compare the air quality complaints in all NYC boroughs years before and after 9/11. This would better address the health complication concerns of the demolishment and mega-jail building plans.