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数据结构 ? 11.62M
Data Structure ?
* 以上分析是由系统提取分析形成的结果,具体实际数据为准。
README.md
Context
As the world faces new challenges in the form of global warming and climate changes, the importance to use clean energy has never been felt more before. The world needs to gradually move towards increased use of public transportation and cycling/biking for commute. Not only can biking help move towards a greener environment, it is extremely good for physical health and fitness as well.
Unfortunately, bikers from around the globe (and particularly from cities) face multiple problems - roads conditions might not be suitable for biking, unavailability of dedicated biking lanes, absence of respect from motorists sharing the roads and multiple others. Bikewise.org is doing an wonderful job of collating the details of all such problems faced by bikers from around he world, day to day. This dataset is a small subset of the data collected by Bikewise.org.
Content
The data collected for this dataset is for the duration - Jan 2017 to Feb 2019. I will periodically update the dataset and add the newest data.
The dataset is divided into 2 files:
1. Locations : contains the exact location of the incident along with incident type, date and time etc.
2. Markers : contains more detailed information in addition to locations, most interesting being the description of the incident.
"Id" is the field tying the 2 files together.
Acknowledgements
[https://www.bikewise.org/](https://www.bikewise.org/) is the owner of the data. I would like to take this opportunity to thank them for the effort they have put to collect this data, and for providing APIs to easily access the data.
Inspiration
If we want to solve the climate change problem, clean transportation will play one of the most important contributors to achieve that goal. So, city authorities must step up to make biking easier, which will in turn attract more bikers to use biking as a daily mode of commute.
By analyzing this dataset, we can try to provide some very important and key insights to the authorities. For example:
* Which parts of the cities are having most of the trouble?
* What are the kinds of problems that the bikers are facing today?
* What are the suggestions (if any) coming from bikers themselves?
* Is there a pattern behind the reported incidents - with respect to time of day, festival seasons, weather conditions, crime index in the city etc?
.... and many more ....
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