This post focuses on Traffic Accidents on the year 2019 excluding the months of January, February and March. These months were excluded because of numerous cases or items with missing values thus making avoiding bias when comparing traffic behavior or trends months in the year 2019. This implies comparisons here are made only for traffic accidents between April to December.
The two charts above uses the height of the vertical bars to represent the counts of traffic accident while the horizontal axis of the left and right chart represent different levels of period of the day and months respectively. The left chart indicates that, about twice the number of traffic accidents occur during the day as compared to the night while the chart on the right shows that the months of October and November dominate with the highest number of traffic accidents. Also the month of April shows the least number of traffic accidents.
The chart above uses the height of the vertical bars to represent the counts of traffic, the horizontal axes to represent the day of the week (which are represented by different colors). The day with the longest height is Friday while other days such as Monday, Tuesday, Wednesday and Thursday all show similar height levels. Sunday appears with the least height, thus the smallest traffic accident counts.
The chart above uses the height of the vertical bars to represent the counts of traffic, the horizontal axes to represent the hour of the day (which are represented by different colors). The hour with the longest height is 9:00 thus representing the hour with the highest traffic accident counts. Also hours like 18:00, 17:00,16:00 and 8:00 are closely related to 9:00 while hour 2:00 and 3:00 show the least counts of traffic accidents
The plot above shows two attributes in the form of points distinguished by the day of the week . Points of the length of road affected (in meters) and the duration of the traffic accident (in mins) seem to gather within a particular range. This implies both attributes are similar irrespective of the day of the week, however outlying points can be found on the plot. Some points or days of the weeks have extremely different values either towards the horizontal or vertical axis.
The plot above shows two attributes in the form of points distinguished by the weather condition . Points of the length of road affected (in meters) and the duration of the traffic accident (in mins) seem to gather within a particular range. This implies both attributes are similar irrespective of the weather conditions, however outlying points can be found on the plot. Some points or weather conditions have extremely different values either towards the horizontal or vertical axis. Furthermore the points on the graph are mostly dominated by cloudy and fair weather conditions with rainy and snow points mostly found outlying. Implying traffic accident duration and length of road affected by accident tend to vary a lot from the rest when rainy or snowing.
The plot above describes three attributes. The left vertical axis contains values of the average traffic duration(mins), the right vertical axis contains values of the average length of road(m) and the horizontal axis shows the months of the year. The line in the plot is used to show the change in the values of the average length of road (orange line) and change in the values of the average traffic duration (blue line) over time (months). The trend in both attributes over months are similar for the months of July to December where an increase in one attribute leads to an increase in another. However an indifferent trend is observed from April to June with one attribute increasing and another decreasing.
The plot above describes three attributes. The left vertical axis contains values of the average traffic duration(mins), the right vertical axis contains values of the average length of road(m) and the horizontal axis shows the months of the year. The line in the plot is used to show the change in the values of the average length of road (orange line) and change in the values of the average traffic duration (blue line) over time(hours of the day). The trend in both attributes over time really differs. As a result, an increase in average length of road affected by accident does not lead to increase in average duration of traffic. For example a steady increase in average traffic duration was recorded between the hours of 02:00 and 05:00 but the length of road affected dropped steadily. Therefore a steady increase in length of road of affected by traffic accident must not lead to an increase in traffic duration across various hours and vice versa.
The plot above brings together four attributes from the US traffic dataset. The left vertical axis contains values of the average traffic duration(mins), the horizontal axis contains values of the average length of road(m) and the size of each circle represents the count of traffic per day. This plot groups days of the weeks with similar average traffic duration and average length of road affected by traffic accidents. The plot shows Tuesday and Friday having similar values and Thursday and Sunday having little differences from the rest. Furthermore Tuesday and Friday demonstrate the largest number of traffic accidents counts.
The plot above brings together four attributes from the US traffic dataset. The left vertical axis contains values of the average traffic duration(mins), the horizontal axis contains values of the average length of road(m) and the size of each circle represents the count of traffic per month. This plot groups months with similar average traffic duration and average length of road affected by traffic accidents. The plot shows the month of September with the least average duration and average length of road affected. However , a slight shift to the right and upwards is observed with the other months with the month of May and June being a little outlying from the rest.
The chart on the left and right uses the height of the vertical bars to represent the average length of road affected by traffic accident and traffic duration(mins) per period of the day respectively. The horizontal line superimposed refers to the average length of road affected and average accident duration irrespective of being in the night or day category. The plot seeks to compare the average (length of road affected and traffic duration) per day and night to the overall average from the dataset. The plot shows that during the day, the average length of road affected by traffic accident is slightly greater than that at night while the average traffic duration is slightly higher in the night than in the day. This implies in the year 2019, the US traffic dataset shows on average slightly higher length of road accidents during the day and slightly higher traffic duration at night.
The chart on the left and right uses the height of the vertical bars to represent the average length of road affected by traffic accident and traffic duration(mins) per month of the year (excluding January, February and March) respectively. The horizontal line superimposed refers to the average length of road affected and average accident duration irrespective of being in the night or day category. The plot seeks to compare the average (length of road affected and traffic duration) per month to the overall average from the dataset.
The plot shows that the average length of road affected by traffic accident in May, June and November is slightly higher than the overall average in the dataset. Also, the average traffic duration in June, April, May and November is slightly higher than the overall average in the dataset. This implies the Months of June, May and November all had average values of traffic duration and average length of road affected to be greater than the overall dataset averages.
The chart on the left and right uses the height of the vertical bars to represent the average length of road affected by traffic accident and traffic duration(mins) per day of the week respectively. The horizontal line superimposed refers to the average length of road affected and average accident duration irrespective of being in the night or day category. The plot seeks to compare the average (length of road affected and traffic duration) per day to the overall average from the dataset.
The plot shows that the average length of road affected by traffic accident on Sunday, Wednesday and Thursday is slightly higher than the overall average in the dataset. Also, the average traffic duration on Sunday, Monday and Wednesday is slightly higher than the overall average in the dataset. This implies Sundays and Wednesdays both had average values of traffic duration and average length of road affected to be greater than the overall dataset averages.
The chart on the left and right uses the height of the vertical bars to represent the average length of road affected by traffic accident and traffic duration(mins) per hour of the day respectively. The horizontal line superimposed refers to the average length of road affected and average accident duration irrespective of being in the night or day category. The plot seeks to compare the average (length of road affected and traffic duration) per hour to the overall average from the dataset.
The plot shows that the average length of road affected by traffic accident at 04:00 is sufficiently higher than the overall average with other hours like 12:00, 13:00, 20:00, 21:00, 22:00 and 23:00 having slightly higher values than the overall average in the dataset. Also, the average traffic duration at 13:00, 14:00, 15:00, 16:00, 17:00, 19:00, 20:00 still 23:00(most difference) is slightly higher than the overall average in the dataset. This implies 13:00, 20:00, 21:00, 22:00 and 23:00 all have average values of traffic duration and average length of road affected to be greater than the overall dataset averages.
The chart above shows the trend in the average traffic accident duration per hour based on the various weather condition. The area represents the average duration and the split by weather was done to get detailed description by weather conditions. The trend in average traffic duration per hour does not vary much when the weather is either cloudy, clear or rainy. However when the weather is fair between the hours of 04:00 to 06:00 a very sharp increase in duration is noticed. Also when thunderous , very fluctuating trends in average traffic duration is observed with peaks at 09:00, 18:00 and 23:00. Fluctuating trends are also observed when snowing with a steady decrease in traffic duration from 19:00 to 23:00.
The chart above shows the trend in the average length of road affected by traffic accident per hour based on the various weather condition. The area represents the average length and the split by weather was done to get detailed description by weather conditions. The trend in average length of road affected by traffic accident per hour does not vary much when the weather is either cloudy, clear or fair. However when the weather is rainy between the hours of 02:00 to 04:00 a very sharp increase in length of road is noticed. Also when snowing , very fluctuating trends in average length of road affected is observed with peaks between 00:00 and 04:00 , 14:00 and 16:00. Fluctuating trends are also observed when thunderous with a steady increase in average length of road affected from 18:00 to 20:00.
This video shows an interactive view of the US Traffic dataset. It involves linking various attributes to the month and states in order to get more details of traffic trend based on the users interest.
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