Getting insights from visual and interactive representations and co-relations of gathered data.
Minute by minute
With U.S. Census Bureau data from the 2010-2013 American Time Use Survey and the American Community Survey; I attempted to visually understand the relationship between time commuting to work and emotions to see if the visualization would highlight some insights. The hypothesis was that longer commutes have a negative impact in your emotions, but the data sets were rich and I was able to compare the duration of commute in minutes across different variables like mode of transportation, sex, income, county location, and level of happiness, sadness, tiredness, and stress. I used time as the controllable variable that ran through the different interactive charts. Mode of transportation is color-coded for easy recognition across all charts and details about specific data points are shown on hover.
Data cleaning and filtering
Cleaning of cvs extraction files in excel.
Charts are also filterable by transportation mode, highlighting the data you want to focus on.
An overview of all charts running through duration of commute in minutes. Being able to watch them simultaneously allows to spot patterns across the diverse variables.
Zoom into the chart by level of feelings to understand how sad, happy, tired or stressed people feel during their commute in relation to the transportation mode (color code) and duration of commute in minutes (x axis)
Enlarge the selection by county to spot patterns across the nation.
The data set: American Time Use Survey
The U.S. Bureau of Labor Statistics publishes the results and data sets of the American Time Use Survey. This data sets contains information about the many different activities Americans do. It includes time of the day and feeling during and prior the activity records, as well as details related to the activity, like company during the activity or duration of the activity. This survey also contains important information about the respondents like gender, race, age, location, etc. I used a special database extract from the ATUS-X project of the University of Maryland, Minneapolis that collected data from 3 years 2010-2013.
Sandra L. Hofferth, Sarah M. Flood, and Matthew Sobek. American Time Use Survey Data Extract Builder: Version 2.7 [dataset]. College Park, MD: University of Maryland and Minneapolis, MN: IPUMS, 2018. https://doi.org/10.18128/D060.V2.7 https://www.atusdata.org/atus/index.shtml