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Prediction of number of users that will rent D.C. Bikesharing's bikes in the 4th quarter of 2012

Jupyter Notebook 29.25% Python 0.30% HTML 70.45%

python-d.c-bikesharing-forecast's Introduction

Python_group_project

Washington DC Biking data

Libraries

  • seaborn
  • gplearn
  • pep8
  • astral
  • plotly
  • xgboost

Note: You can find updated env file is in the repo

To install to environment

conda install --name intro_python seaborn

Please note that the graphs can be seen in the HTML

python-d.c-bikesharing-forecast's People

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