CitiBike-Summer

Please see my completed presentation here.

Getting Started

This dataset was very large, with over 1 million rows of data. For the purposes of publishing to Github, and calculating speed of Tableau, I used Python (Pandas) to read in the CSV file and take a sample of the data for visualization purposes. After selecting 30% of the data at random, I wrote the smaller dataset to a new CSV titled CitiBikeoutput. See the process below:

import pandas as pd
import numpy as np

#read in csv
df = pd.read_csv("./2013-07+08 - Citi Bike trip data.csv")

#create sample, random 30%
df_sample = df.sample(frac=0.30, random_state=42)

#write to new csv
df_sample.to_csv("CitiBikeoutput.csv", index=False)

Visualizing the data

The questions I wanted to answer with this data are as follows:

• Who is cycling?
  
• What are the busiest rental hours during summer months (July & August)
  
• What are the most popular locations to end cycling trips?
  
• What bikes are utilized the most? (This could help with maintenance and upkeep)
  
  Additionally I wanted to visualize all of the stations with details, and over a period of time.
  Finally, I created dashboards and a story to summarize my findings.
  

Questions?

Please refer to the following:
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