vdmitriyev / data-analysis-notebooks

An own collection of a various data analysis results done mainly with Python, IPython and Jupyter

About

Collection of the different sort of own data analysis performed with help of IPython and it's amazing Notebook (now known as Jupyter Notebook).

Dependencies

• Install one of the following
  • Python 2.7 + Packages
  • Anacoda
• Update Anaconda
  • How to update already installed anaconda

  •   conda update conda
      conda update anaconda
      conda update --all
    

Data Analysis

• Plotting data from the weather web site tutiempo.net
  • Check this analysis at the nbviewer or at github
• Sample analysis of Iris with sklearn
  • Check this analysis at the nbviewer or at github
• Repeating data analysis of energy efficiency dataset previouslt done in publication
  • Check
  • Based on publication 'Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools' by A. Tsanas and A. Xifara published in Energy and Buildings, Vol. 49, pp. 560-567, 2012.
• Plotting irradiance data gathered by Solar Measurement Grid, Oahu, Hawaii provided by NREL
  • To download data you may want to use script "download_nrel_oahu_solar.py" provided inside "nrel-oahu-solar/data" folder

Starting

• Start Jupyther Notebook with Anacoda

jupyter notebook

• Start IPython with Anaconda on machine with Windows for github repository

activate analysis
ipython notebook --ip='*' --notebook-dir=D:\git\data-analysis-ipython\

Data Analytics Materials

• Data Preprocessing

  • Preprocessing in Data Science (Part 1): Centering, Scaling, and knn
  • Kaggle bulldozers: Basic cleaning

• Jupyter Notebooks from Books

  • Python Data Science Handbook by Jake Vanderplas

• Tutorials and Videos

  • Reproducible Data Analysis in Jupyter
    • Very short, but descriptive video colletion by Jake Vanderplas, git repository is here - JupyterWorkflow

Author

• Viktor Dmitriyev