In this post, I will be going deeper in finding all possible traffic trends in the US traffic dataset.
Here mostly interactive chats which involves interval selection,pointing while be employed. Also i will be linking several plots together to get more insights from choosing particular marks on a plot.
Also as promised on my previous post(getting more insights), I will built further on some of the ideas and plots i mentioned above, in a way to continue to get more understanding of what is happening in the US traffic dataset. Moreover, my data visualization techniques is mainly to find patterns and characteristics which could lead to possible hypothesis questions or findings.
Note: Due to technical difficulties i will simply upload a non-interactive PNG format of the plots but a video recording will be uploaded below explaining how the plot works.
Please stay tuned as I digest the happenings in the US traffic dataset.
A spaghetti plot showing the average duration (in mins) for traffic accident per weather.
A closer look at the various lines shows that when it is thunderous between 20:00 to 23:00, the duration of accidents increases steadily and there are not accidents between 00:00 still 5:00 when it is thunderous.
The plot above shows average traffic duration in minutes vs average distance in miles per month. It illustrates similar trends in distance and minutes of traffic accident for most months. However, the months Feb, Jan, and March are really outlying and have quite different trends.
In the video post more explanation on the ability of this post will be explained. A point on a mark will give more details such as the maximum temperature, and maximum precipitation at that point.
This plot is seeks to explain patterns in average duration and average distance per hour. The plot shows similar values per hour, however some values show a great different or are really outlying with respect to the bunch of points.
This plot shows the count of traffic accidents per state. Here, the count of traffic accidents is superimposed on the section of the map that corresponds to the state.Furthermore, this plot will be developed such that by selecting a particular state, other traffic plots are displayed.
This plot illustrates average traffic duration and average traffic distance per year. The horizontal bar shows the average duration or average distance in the whole dataset. This implies average lines per year found above the horizontal bar are considered to be above the average traffic duration or distance. Also by clicking on a bar corresponding to a particular year, the plot above displays the particular characteristic above.
This gives a multi view by weather. Here the distance is plotted versus the duration and faceted by the various weather.Also a selection interval links all the plots together.
This plot gives a multi view by months.Here the average traffic duration is plotted per hour with the size of the diamonds representing the average distance(which ranges from five still 20). For example during the month of March, in the fifth hour, the average traffic distance and average traffic duration were abnormally higher that others. However, most months tend to show similar patterns or behavior with similar sizes with respect to average traffic hour and average traffic duration per hour.