Overview
In this week's independent project, you will be working as a data scientist working for an electric car-sharing service company. You have been tasked to process stations data to understand electric car usage over time by solving for the following research question;
Identify the most popular hour of the day for picking up a shared electric car (Bluecar) in the city of Paris over the month of April 2018. Bonus Questions (Optional)
What is the most popular hour for returning cars? What station is the most popular? Overall? At the most popular picking hour? What postal code is the most popular for picking up Blue cars? Does the most popular station belong to that postal code? Overall? At the most popular picking hour? Do the results change if you consider Utilib and Utilib 1.4 instead of Blue cars? Your final deliverable will be a data report which will comprise the following sections;
Business Understanding Data Understanding Data Preparation Analysis Recommendation Evaluation You can get the data and the dataset description for this Independent project here [http://bit.ly/autolib_dataset (Links to an external site.)] and here respectively [Link] (Links to an external site.). The dataset contains data collected for a period of 9 days. The dataset may take a bit of some time to load [~ 10 minutes].
Hint:
To compute usage, we will need to understand that we have to join successive (in time) measures/counters for a given station, as the difference will tell whether a car was picked up, returned, or nothing happened.
The CRISP-DM methodology will guide you while working on the Data Report. Your Data Report will also need to have an objective account, with insights majorly coming from the dataset. However, you can refer to external information for supporting information.
You can use either SQL/Python for this project.
this work was done in a google collaboratory notebook from which the codes were executed.
import pandas as pd
import numpy and np
from google.colab import filespull requests are on hold at the moment until after the repository is reviewed by my TM