Chart
Unanswered Question
The dataset I used is quite comprehensive, but it is missing one data point that could lead to some very interesting analysis: the location of the issued ticket. One question that I would be very curious to see an answer to is related to the subset of tickets issued for 'Street Traffic' bylaws - Where in Port Moody are you the most likely to receive a parking ticket? Given the depth of the data that I already have, the analysis could go even deeper. Further topics like when you are the most likely to receive a parking ticket at a specific location, or why certain areas see more tickets than others could also be explored.
How would you get the data?
It is very likely that Port Moody already stores the ticket location alongside the rest of the bylaw ticket information that they have publicly available. I believe that it would be possible to obtain the location information as an addition to the existing dataset that I am using. Bylaw enforcement in Port Moody is carried out by their Bylaw division. As such, they would likely be the best place to initially reach out to regarding that addition to the dataset. Failing that, Port Moody is subject to Freedom of Information requests, so one could be submitted using the information provided on their website.
Hello Philip,
ReplyDeleteThe research you did on how you would obtain more data regarding bylaw enforcement in Port Moody is quite detailed. Great work! The only suggestion I have is to perhaps consider greying out the bars that aren't part of the summer months to highlight the point of your visualization.
Hello Philip,
ReplyDeleteThe question you raised about your crime dataset regarding its missing dimension of “where” is a great point. I agree with you that location definitely makes crime data easier to interpret. As with Wilson’s point, I think greying out or using a different colour to make the summer months stand out in your visualization could improve your post since not everyone agrees or is clear on which specific months are classified as “summer” months.
Hi Philip, your graph looks good and I think adding location information would help your report be more detailed. As mentioned by others, coloring the bars/text for the summer months would help them stand out on your graph.
ReplyDeleteHello Philip,
ReplyDeleteI like how detailed you were about where to obtain more information and data for Port Moody parking tickets. Like others have mentioned, I also think that highlighting the summer months will make them stand out more.
Hey Philip,
ReplyDeleteI very much agree that obtaining location data would be great to figure out why the warmer months yield such a consistently higher rate of tickets.
Though, I'm not sure if I agree with everyone else here about labelling the "Summer" months. I think incorporating a temperature line chart would be more fitting.
Hello Philip! You mention some really good points in your update 3 here, and you provide a really good plan of how to go about with obtaining additional information. I do agree that location would make this dataset far more interesting with its unanswered questions. My only suggestion here is to maybe add in some colour to highlight the main finding of your dataset (eg. adding colour to the summer months in your chart so that it instantly draws more attention).
ReplyDelete