The data used for this visualization was acquired from the U.S. Census Bureau’s 2014 American Community Survey 1-Year Estimates on Comparative Demographic Estimates. The measured values represent the percentage of the total population comprised of each given age group from 2010 to 2014. The total population has seen small fluctuations in size between 2010 and 2014. While age group 5-years and below have experienced decreases between 2010 and 2014, age groups 55-years and older have seen increases in total population composition between 2010 and 2014.
This visualization, created for a presentation at the Connecticut Association of Boards of Education‘s Annual Summer Leadership Conference on July 27 includes data from the Connecticut State Data Center’s Population Projections for school districts in Connecticut, along with demographic, socioeconomic, and enrollment data from the U.S. Census Bureau’s American Community Survey and the CT Department of Education CEDAR data portal. This dashboard was created by Steve Batt, Zachary Guarino and Qiwei Zheng.
This visualization uses data from the U.S. Census Bureau’s 2013 Annual Survey of Public Pensions State-Administered Defined Benefit Pensions Systems downloaded from American FactFinder. The thematic map indicates the ratio of pension obligations to each state’s total cash and investment holdings in its state-run public pension system at the close of fiscal year 2013. Bar graphs indicate FY13 pension fund net investment earnings, and overall pension fund investments by category (i.e. stocks, Treasury bonds, etc). Locally administered (e.g. municipal) public pension data is excluded from the graphs.
States have remarkably diverse approaches to taxes; the U.S. Census Bureau’s Annual Survey of State Government Tax Collections collects data on revenue derived from five tax categories for 2014: Income taxes, Property taxes, License taxes, Sales and gross receipts taxes, and Other taxes. This visualization compares the relevant importance of each of these categories in contributing to the tax base of each state.
This visualization uses data from the American Community Survey to display distressed census tracts, which is a tract at 60% or less of the state median household income level. This study ranges from the year 2010 to 2013.
In the state of Connecticut, the number of people born in-state who went on to get a bachelor’s, graduate, or professional degree made up a sizable fraction of the people who possessed one of those degrees during the years 2012 and 2013, though they made up a much smaller percentage of the Connecticut population as a whole. In 2012, these people were approximately 77% of the state’s degree holders fell within this category while making up just 14% of the state’s total population. In 2013, both of these percentages increased: now, native Connecticut residents with bachelor’s, graduate, or professional degrees made up 78% of its degree holders while making up approximately 15% of the entire population within the state.
The provided tables and charts break these percentages down by county and year. Interestingly, though the total percentage for the state went up, the county breakdown reveals that this increase was not necessarily reflected by the individual counties. Middlesex County, for example, saw a 3% increase in the number of native Connecticut residents who possessed bachelor’s degrees but a 1% decrease in the number native Connecticut residents who possessed graduate or professional degrees instead. Windham County, on the other hand, saw a 4% increase in the number of native Connecticut residents with bachelor’s degrees as well as a 1% increase in those with graduate or professional degrees.
Introduction: This project focuses on comparing the annual percentage of workers at home for primarily the State of Connecticut in comparison to the United States National average from the years 2010 to 2013.
Data: The data is derived from the American Community Survey Means of Transportation to Work by Age 1-Year Estimates from 2010 to 2013. The age breakdowns were aggregated together for this analysis because the focus in on the average for the State and not each age grouping. The workers at home percentage was calculated by dividing the number of workers at home by the total number of workers. Utilizing Tableau software I was able to create visualizations for this data set. There is a wide range of interactive visualizations including line and bar graphs. Most of the Dashboard space is used to show comparisons withe Connecticut and the U.S. workers at home percentage, but I went t a step further to also show how Connecticut compared to other states in New England. Several features on the Dashboard can be altered according to a specific year of interest, allowing for closer comparison in a given year. The trend lines also tell a story of how many workers at home there are over the 3 year span of 2010 to 2013.
Findings: Through the data visualizations I was able to come to the conclusion that Connecticut has had an increase in people who work from home, increasing about 0.39% from 2010 to 2013. There was a slight drop in 2012 but the overall trend is increasing. The percentage of people working at home for the National average had a much more gradual trend line, only increasing by 0.03% from 2010 to 2013. Connecticut has never been higher then the National average yet but is approaching closer every year. In 2013, Connecticut was at 4.33% workers from home the National average only was slightly higher at 4.36%. In comparison to New England, Connecticut although not having the highest percentage of workings at home ranks pretty well given its increasing trend. States like New Hampshire and Rhode Island appear to be on a decrease in people working at home. Vermont’s percentage has been fluctuating a lot, however Connecticut, Maine, and Massachusetts all have positive slopes. A closer look at the trend line shows that Maine has the greatest increase, followed by Connecticut and Massachusetts. So I would rank Connecticut 2nd in percentage of workers at home in New England. The visualization for New England on the Dashboard has a year by year comparison bar graph to allow for analysis at the annual level and the line graphs have been omitted for conservation of space.
Sources:
Means of Transportation to Work by Age, American Community Survey 1-Year Estimates, 2010 – 2013
The above map, based on table B19080: “Household income quintile upper limits” from the 2013 American Community Survey, displays income amounts which would put a household among the wealthiest 5% in their state. The stacked bars adjacent to the map display household income distribution within a state by quintiles, providing an overview of household income distribution.
For Connecticut, New Jersey, and District of Columbia, table B19080 from the 2013 ACS reports that the top 5% of households by income have lower income limits of “250,000+”, while more precise estimates are provided for all other states. Connecticut reached this apparent “250,000+” reporting ceiling in the 2011 American Community Survey report. The top 5% of households in District of Columbia surpassed this threshold several years earlier. Interestingly, in 2009 the American Community Survey reported that the lower limit of the top 5% of households in D.C. was $279,845; in this year’s report the figure is reported simply as being “$250,000+”, obscuring the true estimate. Table B19083 from the 2013 ACS indicates that the District of Columbia has a greater level of income inequality than any state; New York and Connecticut have the highest Gini index among states.
The American Community Survey 2009-13 ACS 5-Year dataset, released today by the U.S. Census Bureau, provides new economic and demographic data for smaller geographic areas including all 169 Connecticut towns. The visualization below provides a snapshot of just a few measures from one report within this dataset, “DP03 – Selected Economic Characteristics” – just one of the more than 2,000 tables of new data for Connecticut towns, Congressional districts, school districts, Census Tracts, and other areas. To browse for more detailed economic data on any town, follow the link that appears when you hover over any map in the visualization – or start browsing American FactFinder with some of the links below:
