Today’s data set took us deep into the life of Americans. The American Bureau of Labor Statistics publishes data about how American spent their daily time. By the minute, the days are broken down into major categories e.g. Household Activities or Work & Work-related activities. These categories are then further broken down into sub-categories.
The most time consuming activity was to make sense of the data. The survey results were encoded, so the data looked like this:
The column names and its values first had to be deciphered using the data dictionary. For example, the column PTDTRACE refers to the race of the survey respondent. The values in this column (1 & 2) stand for the race. So 1 could mean Hispanic, 2 could mean White and so on...I came up with the following workflow in Alteryx to rename the headers and to replace its containing values with the respective values of the data dictionary.
The workflow filters on the most recent year 2017, renames the columns of the with the headers form the data dictionary and also replaces the activity codes with its corresponding values. The find and replace tools replace the codes in each column with the values form the data dictionary. (Hispanic for 1, etc.)
After having cleaned the data I could finally go into Tableau and visualise the data. In the end, I decided to focus on how men and women spend their time differently. I opted for a stacked bar chart which shows the percentage of total time spent per major category for both, men and women.
The values on right side represent the difference of time spent between men and women.