About Us

Data Processing

The data has been processed through many data visualization programs, the most notable of the bunch being Tableau and Palladio. Initially using Open-Refine to clean the data, we have gone on to further integrate and
break down our data to paint a picture of grocery business activity, education services, and council districts. 

When doing research, we came across information regarding differentiation in grocery store access dependent upon location and socioeconomic status. An article from the American Journal of Public Health, “Associations of neighborhood characteristics with the location and type of food stores,” explains the findings of their own investigative research, “local food environments vary substantially by neighborhood racial/ethnic and socioeconomic composition and may contribute to disparities in health.”  We used our data from the Listing of Active Businesses in L.A. and the L.A. County’s data set regarding income, as well as that article to examine if their findings were true for the Los Angeles area specifically. 

Conversation around whether access to education is dependent upon income levels and status is very important. We found various articles supporting the argument that there is not equal opportunity across all neighborhoods. We were heavily influenced by one study done in Maryland called, “Does Moving to Better Neighborhoods Lead to Better Schooling Opportunities? Parental School Choice in an Experimental Housing Voucher Program.” This article points out that schools in low-income areas had significantly lower test scores, on average, than those in higher income areas. We sought to use our data and look at education services in Los Angeles, starting with access to education. We used the Listing of Active Businesses in LA and tried to see if there was a correlation between income levels and the area in which schools were placed. 

Our data is very council district focused. We wanted to see if there are disparities and unequal opportunities throughout the Los Angeles area, leading to problems of underprivileged youth and unhealthy lifestyles. 

Our raw data has been cleaned in order to account for errors and statistical incongruities, as well as highlighting the most salient data types and values that pertain to businesses and educational services in the Los Angeles area.

Data Presentation

Our data is presented in a multitude of formats in order to help orient users around the scope of this project. 

Bar charts, maps, and line graphs have all been utilized in order to present our findings in a clear and concise manner. 

We hope that in this way, our narrative can be presented in an understandable manner, as well as offer up some interactivity into our design. 


Our team worked heavily to break down the information within the listing of active businesses in Los Angeles. This data consists of all active businesses in L.A. that are currently registered with the Office of Finance and indicates ones that have also ceased operations. The data is updated monthly and includes information regarding the location and category of the business(es).

Further information can be found on the Research Sources page, including information regarding the issues of surrounding underprivileged youth and unhealthy lifestyles. The sources discuss groceries, education, and location. These scholarly articles highlight the problem Los Angeles is facing and take a deeper dive into into how it is an issue on not only a local scale, but a global one. 

We also used data from posted on the L.A. County’s website displaying median household incomes by council districts in order to cross examine it with our findings.


Due to the particular circumstances that we have faced during spring 2020 we are grateful to have come to end of what has been less than a normal quarter. 

The deaths of Breonna Taylor, Ahmaud Arbrey, George Floyd and the countless other lives lost to senseless discrimination and brutality sit with us through these times. 

We also recognize the impact of COVID-19 on the lives of everyone around us and particularly the UCLA community and the greater Los Angeles community. 

At this this time we would like to thank Dr. Albrezzi and our TA, Madison Faulis, for their countless efforts to give us the best feedback and advice for our projects. We also want to thank all guest lectures and staff behind the scenes who contributed to our success during these unprecedented times.