Healthy Ride is a system that can be used year round. Even during winter months when people wouldn’t normally assume it’s conducive to bike riding. The analysis will look into those days in winter where the assumption would be ridership would be nonexistent in order to either prove this as true or debunk it.
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Dataset
Within the dataset assigned I looked at the following data, Total number of bikes used, trip stations statistics, trip duration statistics, and time statistics.
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Initial Analysis
First was an analysis of the data to see what were the starting and end points of the data (January 1st-March 31st). From here I baked tracked into 2017 meteorological data to find those days where the weather was inclement and mild.After dates were selected, an analysis of the data set information was conducted using SQL search queries.
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From this graph analysis, 5 dates stand out as being points of interest, of high ridership.
January 21st, February 19, February 20th, February 24, and March 25
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Exploration
A final representation/visualization of the dataset is included here. Using some of the knowledge of the SQL codes in class balanced with GUI, this map was produced.
Overall, the winter was mild, overall there were only 22 days below freezing (32°F) during the three-month span of the data and 19 days over 60°F
16 days had a noticeable amount of participation (snow/rain) of more than 0.20 inches.
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Future Work
Having a better mastery of SQL would have lead to a better map representation. If time can be spared learning a bit know on SQL, I would revise the map accordingly to pull more easily the information I would like to query.
A deeper look into the 5 dates where ridership spikes should also be my next investigation.
