Data Critique

Data Critique

© “Atlanta BeltLine” by Gene Phillips

Atlanta Zip Codes: Racial Data

Years Film Count Running Count
1974 1 1
1975 0 1
1976 0 1
1977 2 3
1978 0 3
  • The information in this dataset was sourced from a Wikipedia page titled “Category:Films shot in Atlanta” which lists movies that have been filmed in Atlanta, Georgia. Wikipedia lists all the original sources of this information in the reference sections of the specific movie articles linked from the page.
  • The data was generated using the BeautifulSoup package in Python. BeautifulSoup scraped the release dates of all the movies listed on the page, which was then put into Python to generate a histogram.
  • This dataset contains the number of films shot in Atlanta for each year over the period of 1974 – 2025. The dataset also includes a running total number of movies filmed in Atlanta over time.
  • This dataset can outline the trend in the number of movies shot in Atlanta over time. We can see whether this figure has increased, decreased, or remained the same, reflecting the overall growth and development of the city’s film industry.
  • By looking over the timeline of the dataset, 1974 – 2025, we can investigate the effects that major events (government policies, recession, COVID-19) had on the number of movies filmed in Atlanta. The data can reveal which events had a positive or negative impact on the growth of the film industry.
  • This dataset cannot reveal the exact reason why many movies chose to film in Atlanta. While Wikipedia does point out some of the motivators for filming in Atlanta, many of the linked articles don’t talk about the reason filmmakers chose those sets. Several of the production sections of the pages are limited to a single sentence verifying that filming took place in Atlanta.
  • This dataset cannot reveal the community impact of filming movies in Atlanta. While the data can visualize the growth of the film industry in Atlanta, it does not discuss in any way, shape, or form, the socioeconomic effects these movies had on the city they were made in. This is important to our project and reduces the effectiveness of the data as a tool to explore this relationship.
  • The dataset is not a complete or comprehensive list of every movie that has ever been made and shot in some part in Atlanta. Many films have used Atlanta as a set, whether to a small or large effect. The Wikipedia page merely has the most complete and most comprehensive iteration of the data we were interested in. 
  • This dataset also doesn’t list every production shot in Atlanta; the list is limited to theatrical releases, despite Georgia offering tax credits to television shows and other media productions.

Click here to explore the historical background behind the topic of gentrification and the film industry in Atlanta.

Year Total Employment
2012 41,230
2013 42,890
2014 44,480
2015 49,490
2016 50,920

Films in Atlanta Data

Years Film Count Running Count
1974 1 1
1975 0 1
1976 0 1
1977 2 3
1978 0 3
  • The information in this dataset was sourced from a Wikipedia page titled “Category:Films shot in Atlanta” which lists movies that have been filmed in Atlanta, Georgia. Wikipedia lists all the original sources of this information in the reference sections of the specific movie articles linked from the page.
  • The data was generated using the BeautifulSoup package in Python. BeautifulSoup scraped the release dates of all the movies listed on the page, which was then put into Python to generate a histogram.
  • This dataset contains the number of films shot in Atlanta for each year over the period of 1974 – 2025. The dataset also includes a running total number of movies filmed in Atlanta over time.
  • This dataset can outline the trend in the number of movies shot in Atlanta over time. We can see whether this figure has increased, decreased, or remained the same, reflecting the overall growth and development of the city’s film industry.
  • By looking over the timeline of the dataset, 1974 – 2025, we can investigate the effects that major events (government policies, recession, COVID-19) had on the number of movies filmed in Atlanta. The data can reveal which events had a positive or negative impact on the growth of the film industry.
  • This dataset cannot reveal the exact reason why many movies chose to film in Atlanta. While Wikipedia does point out some of the motivators for filming in Atlanta, many of the linked articles don’t talk about the reason filmmakers chose those sets. Several of the production sections of the pages are limited to a single sentence verifying that filming took place in Atlanta.
  • This dataset cannot reveal the community impact of filming movies in Atlanta. While the data can visualize the growth of the film industry in Atlanta, it does not discuss in any way, shape, or form, the socioeconomic effects these movies had on the city they were made in. This is important to our project and reduces the effectiveness of the data as a tool to explore this relationship.
  • The dataset is not a complete or comprehensive list of every movie that has ever been made and shot in some part in Atlanta. Many films have used Atlanta as a set, whether to a small or large effect. The Wikipedia page merely has the most complete and most comprehensive iteration of the data we were interested in. 
  • This dataset also doesn’t list every production shot in Atlanta; the list is limited to theatrical releases, despite Georgia offering tax credits to television shows and other media productions.

Click here to explore the historical background behind the topic of gentrification and the film industry in Atlanta.

hpi_type hpi_flavor frequency level place_name place_id yr period index_nsa index_sa
traditional purchase-only monthly USA or Census Division East North Central Division DV_ENC 1991 1 100.00 100.00
traditional purchase-only monthly USA or Census Division East North Central Division DV_ENC 1991 2 100.89 100.95
traditional purchase-only monthly USA or Census Division East North Central Division DV_ENC 1991 3 101.30 100.92
traditional purchase-only monthly USA or Census Division East North Central Division DV_ENC 1991 4 101.69 100.99
traditional purchase-only monthly USA or Census Division East North Central Division DV_ENC 1991 5 102.31 101.36

The above table shows the first five rows of the Housing Market Price Dataset. Click the link below to download the full csv.

  • The original source of this dataset is a government organization called Federal Housing Finance Agency.
  • The data was collected through the United States Census over the span of 32 years(1991-2023) for each city, state, and region in the United States.
  • The following dataset includes information about the change in the value of the U.S. residential housing market for each region, state, and city in the United States from 1991 – 2023. The data is then broken down into different periods, for instance quarterly or monthly. The variables index_nsa and index_sa show the non-seasonally adjusted and seasonally adjusted housing price change, respectively.
  • Since the following dataset outlines the change in the value of the U.S residential housing market from 1991 – 2023, it can reveal the change in the housing market over time in Atlanta, Georgia. This could reveal long-term patterns such as overall appreciation or depreciation trends.
  • The dataset enables the comparison of housing price changes across different regions, states, and cities. This analysis can reveal disparities in housing market performance and identify regions that have experienced significant growth or decline over the 32-year period.
  • Using the broad timeline of the dataset, 1991 – 2023, we can investigate the effects that major events (government policies, recession, COVID-19) had on the housing market.
  • Due to a lack of qualitative data in the dataset, we are unable to contextualize the economic trends that it reveals. Based on the data present in the dataset alone, we cannot discover the reasoning behind why certain changes in the housing market occur. We are also unable to understand the true impact of the housing market on a specific city. This dataset cannot reveal possible gentrification or community displacement brought about by changes in the housing market.
  • Because the dataset is solely focused on housing market price data, it leaves out valuable information on the lived experience of communities like the racial demographic of the city and the average income which can be used to characterize the city and evaluate the human impacts of housing market changes.

Georgia Entertainment Employment Data

  • The original source is from the US Bureau of Labor Statistics.
  • The data was generated from the US Bureau of Labor Statistics. The original data included the total employment for every sector, but we reduced the data to only contain the total employment of the Arts, Design, Entertainment, Sports, and Media Occupations in Georgia from 2012 to 2022.
  • The dataset contains information about the total employment numbers for Arts, Design, Entertainment, Sports, and Media Occupations in Georgia from 2012 to 2022.
  • The dataset can reveal the trend of employment in the Arts, Design, Entertainment, Sports, and Media sectors over the decade of 2012 – 2022. By visualizing the data, we can see whether employment has increased or decreased in general and the minute changes from year to year.
  • By exploring the timeline of the dataset, 2012 – 2022, we can investigate the effects that major events, like the COVID-19 pandemic, had on the number of entertainment employees in Georgia.
  • The dataset cannot reveal the impacts of entertainment employment on Georgia communities and residents. For example, this dataset cannot reveal any evidence that entertainment employment contributes to gentrification or community displacement solely based on its own data. 
  • This dataset also cannot reveal the historical context behind why entertainment employment has increased or decreased. This is why we have included other datasets like the “Films shot in Atlanta” data to supplement this information.
  • As is, the data also cannot reveal employment trends on a local scale. It is unclear whether the employment figures are distributed across the state of Georgia or concentrated in Atlanta. Gentrification typically occurs in specific neighborhoods within cities rather than at the state level, so more detailed data would be necessary to understand local impacts.
  • The data is for the state of Georgia as a whole, so information on the distribution of these jobs across different areas within Georgia, particularly Atlanta, is left out. This information would be necessary to analyze local employment patterns in comparison to statewide patterns.
  • The dataset leaves out information regarding the representation of women, racial and ethnic minorities, LGBTQ+ individuals, and individuals with disabilities within the field of entertainment employment. This information could have shed a light on issues of workforce diversity and inclusion and revealed exactly what type of person is benefiting from the introduction of the film industry in Georgia.
  • The dataset does not include information regarding the level of employment in the entertainment sector. It could potentially under-represent the contributions of informal or part-time workers such as independent artists, freelancers, or performers.

Year Total Employment
2012 41,230
2013 42,890
2014 44,480
2015 49,490
2016 50,920

Films in Atlanta Data

Years Film Count Running Count
1974 1 1
1975 0 1
1976 0 1
1977 2 3
1978 0 3
  • The information in this dataset was sourced from a Wikipedia page titled “Category:Films shot in Atlanta” which lists movies that have been filmed in Atlanta, Georgia. Wikipedia lists all the original sources of this information in the reference sections of the specific movie articles linked from the page.
  • The data was generated using the BeautifulSoup package in Python. BeautifulSoup scraped the release dates of all the movies listed on the page, which was then put into Python to generate a histogram.
  • This dataset contains the number of films shot in Atlanta for each year over the period of 1974 – 2025. The dataset also includes a running total number of movies filmed in Atlanta over time.
  • This dataset can outline the trend in the number of movies shot in Atlanta over time. We can see whether this figure has increased, decreased, or remained the same, reflecting the overall growth and development of the city’s film industry.
  • By looking over the timeline of the dataset, 1974 – 2025, we can investigate the effects that major events (government policies, recession, COVID-19) had on the number of movies filmed in Atlanta. The data can reveal which events had a positive or negative impact on the growth of the film industry.
  • This dataset cannot reveal the exact reason why many movies chose to film in Atlanta. While Wikipedia does point out some of the motivators for filming in Atlanta, many of the linked articles don’t talk about the reason filmmakers chose those sets. Several of the production sections of the pages are limited to a single sentence verifying that filming took place in Atlanta.
  • This dataset cannot reveal the community impact of filming movies in Atlanta. While the data can visualize the growth of the film industry in Atlanta, it does not discuss in any way, shape, or form, the socioeconomic effects these movies had on the city they were made in. This is important to our project and reduces the effectiveness of the data as a tool to explore this relationship.
  • The dataset is not a complete or comprehensive list of every movie that has ever been made and shot in some part in Atlanta. Many films have used Atlanta as a set, whether to a small or large effect. The Wikipedia page merely has the most complete and most comprehensive iteration of the data we were interested in. 
  • This dataset also doesn’t list every production shot in Atlanta; the list is limited to theatrical releases, despite Georgia offering tax credits to television shows and other media productions.

Click here to explore the historical background behind the topic of gentrification and the film industry in Atlanta.

Zip Code Year Black Proportion White Proportion Black Count White Count Total Count
30002 2011 0.373946 0.530201 2173 3081 5811
30030 2011 0.238204 0.68111 6179 17668 25940
30032 2011 0.885791 0.092034 42223 4387 47667
30033 2011 0.123384 0.684993 3712 20608 30085
30067 2011 0.304989 0.491196 13493 21731 44241
  • The original source of the data is survey information from the US Census.
  • We built this dataset by hand by compiling data from the US Census website. The dataset is made up of information from 11 separate tables for the years 2011-2022. Using the dplyr package in R Studio, we removed unnecessary information, selected the information we wanted from each table, used regular expressions to extract the numerical code of the zip code, created columns of data by calculating the proportions of residents, and combined this data across all eleven tables to create our final dataset.
  • This dataset includes information regarding the proportion and total number of Black and White Residents per Atlanta zip code over the years 2011-2022. For each of the 41 zip codes that make up the city of Atlanta, it contains the total number of black residents, total number of white residents, proportion of black residents, proportion of white residents, and total number of residents for each year.
  • The dataset can reveal, on a basic level, the racial demographic of each Atlanta zip code over the eleven year period of 2011-2022. By providing the number of black and white residents per zip code per year, we can visualize how large certain neighborhoods are in relation to each other as well as the prevalence of certain races. 
  • On a larger scale, this dataset can also be used to illuminate the phenomena of the movement of racial groups across Atlanta zip codes over time. Analysis of this movement of racial groups can then help identify areas experiencing gentrification by observing changes in the proportion of White residents in historically black areas and shifts in overall population numbers.
  • The dataset cannot reveal the socioeconomic status of the residents that inhabit each Atlanta zip code or the amenities that they have access to which is another significant factor that can contribute to the division and displacement of communities. 
  • While the dataset spans eleven years, it does not fully capture the historical context and systemic factors that influence racial demographics in Atlanta. It cannot reveal the legacy of slavery, segregation, redlining, discriminatory policies, and racial tensions that have shaped the city’s landscape and communities. It is for this reason that we have included a redlining map of Atlanta from the Mapping Inequality project in our historical analysis.
  • Although the dataset can show possible community displacement, it cannot reveal the context and reasoning behind why this movement is occuring. We have included the other three datasets for our analysis in order to supplement this informational gap.
  • As a group, we made the conscious choice to only focus on data that pertained to white Atlanta residents and black Atlanta residents. While we are cognizant of the fact that this racial binary is in no way fully representative of the diversity of racial identity in Atlanta, we felt it would be best to simplify our area of analysis to the two most prominent racial groups. Especially since there is historical precedence of deeply ingrained social, financial, and economical inequality brought about by this racial division. As such, information was left out regarding Atlanta residents of other races or mixed races. 

The above table shows the first five rows of the US Census Dataset. Click the link below to download the full csv.

Housing Market Price Data

hpi_type hpi_flavor frequency level place_name place_id yr period index_nsa index_sa
traditional purchase-only monthly USA or Census Division East North Central Division DV_ENC 1991 1 100.00 100.00
traditional purchase-only monthly USA or Census Division East North Central Division DV_ENC 1991 2 100.89 100.95
traditional purchase-only monthly USA or Census Division East North Central Division DV_ENC 1991 3 101.30 100.92
traditional purchase-only monthly USA or Census Division East North Central Division DV_ENC 1991 4 101.69 100.99
traditional purchase-only monthly USA or Census Division East North Central Division DV_ENC 1991 5 102.31 101.36

The above table shows the first five rows of the Housing Market Price Dataset. Click the link below to download the full csv.

  • The original source of this dataset is a government organization called Federal Housing Finance Agency.
  • The data was collected through the United States Census over the span of 32 years(1991-2023) for each city, state, and region in the United States.
  • The following dataset includes information about the change in the value of the U.S. residential housing market for each region, state, and city in the United States from 1991 – 2023. The data is then broken down into different periods, for instance quarterly or monthly. The variables index_nsa and index_sa show the non-seasonally adjusted and seasonally adjusted housing price change, respectively.
  • Since the following dataset outlines the change in the value of the U.S residential housing market from 1991 – 2023, it can reveal the change in the housing market over time in Atlanta, Georgia. This could reveal long-term patterns such as overall appreciation or depreciation trends.
  • The dataset enables the comparison of housing price changes across different regions, states, and cities. This analysis can reveal disparities in housing market performance and identify regions that have experienced significant growth or decline over the 32-year period.
  • Using the broad timeline of the dataset, 1991 – 2023, we can investigate the effects that major events (government policies, recession, COVID-19) had on the housing market.
  • Due to a lack of qualitative data in the dataset, we are unable to contextualize the economic trends that it reveals. Based on the data present in the dataset alone, we cannot discover the reasoning behind why certain changes in the housing market occur. We are also unable to understand the true impact of the housing market on a specific city. This dataset cannot reveal possible gentrification or community displacement brought about by changes in the housing market.
  • Because the dataset is solely focused on housing market price data, it leaves out valuable information on the lived experience of communities like the racial demographic of the city and the average income which can be used to characterize the city and evaluate the human impacts of housing market changes.

Georgia Entertainment Employment Data

  • The original source is from the US Bureau of Labor Statistics.
  • The data was generated from the US Bureau of Labor Statistics. The original data included the total employment for every sector, but we reduced the data to only contain the total employment of the Arts, Design, Entertainment, Sports, and Media Occupations in Georgia from 2012 to 2022.
  • The dataset contains information about the total employment numbers for Arts, Design, Entertainment, Sports, and Media Occupations in Georgia from 2012 to 2022.
  • The dataset can reveal the trend of employment in the Arts, Design, Entertainment, Sports, and Media sectors over the decade of 2012 – 2022. By visualizing the data, we can see whether employment has increased or decreased in general and the minute changes from year to year.
  • By exploring the timeline of the dataset, 2012 – 2022, we can investigate the effects that major events, like the COVID-19 pandemic, had on the number of entertainment employees in Georgia.
  • The dataset cannot reveal the impacts of entertainment employment on Georgia communities and residents. For example, this dataset cannot reveal any evidence that entertainment employment contributes to gentrification or community displacement solely based on its own data. 
  • This dataset also cannot reveal the historical context behind why entertainment employment has increased or decreased. This is why we have included other datasets like the “Films shot in Atlanta” data to supplement this information.
  • As is, the data also cannot reveal employment trends on a local scale. It is unclear whether the employment figures are distributed across the state of Georgia or concentrated in Atlanta. Gentrification typically occurs in specific neighborhoods within cities rather than at the state level, so more detailed data would be necessary to understand local impacts.
  • The data is for the state of Georgia as a whole, so information on the distribution of these jobs across different areas within Georgia, particularly Atlanta, is left out. This information would be necessary to analyze local employment patterns in comparison to statewide patterns.
  • The dataset leaves out information regarding the representation of women, racial and ethnic minorities, LGBTQ+ individuals, and individuals with disabilities within the field of entertainment employment. This information could have shed a light on issues of workforce diversity and inclusion and revealed exactly what type of person is benefiting from the introduction of the film industry in Georgia.
  • The dataset does not include information regarding the level of employment in the entertainment sector. It could potentially under-represent the contributions of informal or part-time workers such as independent artists, freelancers, or performers.

Year Total Employment
2012 41,230
2013 42,890
2014 44,480
2015 49,490
2016 50,920

Films in Atlanta Data

Years Film Count Running Count
1974 1 1
1975 0 1
1976 0 1
1977 2 3
1978 0 3
  • The information in this dataset was sourced from a Wikipedia page titled “Category:Films shot in Atlanta” which lists movies that have been filmed in Atlanta, Georgia. Wikipedia lists all the original sources of this information in the reference sections of the specific movie articles linked from the page.
  • The data was generated using the BeautifulSoup package in Python. BeautifulSoup scraped the release dates of all the movies listed on the page, which was then put into Python to generate a histogram.
  • This dataset contains the number of films shot in Atlanta for each year over the period of 1974 – 2025. The dataset also includes a running total number of movies filmed in Atlanta over time.
  • This dataset can outline the trend in the number of movies shot in Atlanta over time. We can see whether this figure has increased, decreased, or remained the same, reflecting the overall growth and development of the city’s film industry.
  • By looking over the timeline of the dataset, 1974 – 2025, we can investigate the effects that major events (government policies, recession, COVID-19) had on the number of movies filmed in Atlanta. The data can reveal which events had a positive or negative impact on the growth of the film industry.
  • This dataset cannot reveal the exact reason why many movies chose to film in Atlanta. While Wikipedia does point out some of the motivators for filming in Atlanta, many of the linked articles don’t talk about the reason filmmakers chose those sets. Several of the production sections of the pages are limited to a single sentence verifying that filming took place in Atlanta.
  • This dataset cannot reveal the community impact of filming movies in Atlanta. While the data can visualize the growth of the film industry in Atlanta, it does not discuss in any way, shape, or form, the socioeconomic effects these movies had on the city they were made in. This is important to our project and reduces the effectiveness of the data as a tool to explore this relationship.
  • The dataset is not a complete or comprehensive list of every movie that has ever been made and shot in some part in Atlanta. Many films have used Atlanta as a set, whether to a small or large effect. The Wikipedia page merely has the most complete and most comprehensive iteration of the data we were interested in. 
  • This dataset also doesn’t list every production shot in Atlanta; the list is limited to theatrical releases, despite Georgia offering tax credits to television shows and other media productions.

Click here to explore the historical background behind the topic of gentrification and the film industry in Atlanta.

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