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data-analytics-challenge's Introduction

Tech challenge

drawing

Cobify is a company dedicated to people transport just like Uber, Lyft or even Cabify (who clearly stole our name).

Cobify was founded in 1992 coinciding with the Olympic Games hosted in Barcelona. Our company has always been known by:

  • Not having permits to drive people (we do know how to drive)
  • Using tricked-out high-end car

In our home town, Barcelona, VTC licenses have appeared and we have been able to start being a legal company, because we do have licenses now. However, we still keep using tricked-out high-end cars.

We are an old school company and data analysis falls far beyond our reach, and as we do not want to be on the news we want to know how you can help our business.

A bit of history of the gas problem ⛽️

Tricked-out cars use gas with a high cetane index, like unleaded 98 petrol in order to avoid delay/advancing in combustible injection (avoiding connecting rod pitting ), but we have started to embrace petrols that add ethanol in their formula, as they are cheaper and they use the same cetane index as more expensive petrol. Without going into further detail (we could write an actual book about this) we think that going green and being modern can be very expensive, as we have seen that cars use more petrol than they used to for each trip.

Your challenge starts here 📈

Now it is your turn: can you help us find the best combustible? We have saved some consumption data in a .csv, but… it would be very nice if you could add some more data. You can find data in the repo :-)

Show us your abilities and make yourself worth the amount of money you'd like to get paid. You have 3 hours to turn the challenge in starting right now! 💸

What to do?

You should aim for:

Exploratory data analysis

  • Get to know the domain
  • Explore your data
  • Clean your data
  • Take a look and find connections between data

Visualization

  • Plot your data in a meaningful way

Predictions

  • Do you have any hypothesis?
  • Can you make any kind of prediction: regression and/or classification?

Storytelling

  • What metrics are you obtaining?
  • Explain your conclusions
  • Shape your new data and conclusions in such a way that is appealing to the listener and tells a story

Extra:

Enrich your dataset

  • Add value: obtain related data by web scraping or with APIs.

Database

  • Load the processed information into a database

Submission

To deliver your proposal make a fork of the repo and when you are done make a pull request. 🤯

How to do a pull request
  1. Fork this repository
  2. Clone it
  3. Work on it
  4. Push the changes to your fork
  5. From your fork, click on Contribute
  6. Open pull request
  7. Name it: [Name FamilyName] Tech challenge

Do not forget to add any PDF document, slides or anything you can think of.

You can grab ideas from our instructors or create something with streamlit 🚀

Go bezerk if you want to get this job, you will set the limits!

PD: even though this has an informal tone, this challenge is serious and very similar to those you will encounter in real life.

data-analytics-challenge's People

Contributors

breogann avatar iamlex006 avatar

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