Exploratory Data Analysis Course

Table of Content

• data: A csv file with data.
  • 2018_Central_Park_Squirrel_Census_-_Squirrel_Data.csv
  • o-ring-erosion-only.data
• documents: pdf files
  • Data_in_Support_of_Enhancing_Metabolomics_Research_Through_Data_Mining.pdf
  • Robinson-icebreaker.pdf
• images: images for presentation
• ipynb: Jupyter notebbok and slides
  • presentation.ipynb
  • presentation_slides.html
• notes:
  • nbconvert.txt: command to generate the html slides
• scripts: Python scripts and R scripts
  • boxplot_simetria.py
  • dataframe_outlier_pca.py
  • dataframe_outlier.py
  • dealing_with_missing_data_example_01.py
  • dealing_with_missing_data_example_02.py
  • dealing_with_missing_data_example_03.py
  • distances.py
  • heterocedasticidad_no_normalidad.py
  • heterocedasticidad.py
  • mahalanobis_example_01.py
  • mahalanobis_example_02.py
  • pca.py
  • qqplot.py
  • shapiro_example_01.py
  • shapiro_example_02.py
  • tboxcox.R

Generate Slides

jupyter nbconvert presentation.ipynb --to slides --reveal-prefix reveal.js --no-prompt --SlidesExporter.reveal_theme=white --SlidesExporter.reveal_transition=slide --TagRemovePreprocessor.remove_input_tags={\"hide\"}

Generate HTML document

jupyter nbconvert presentation.ipynb --to html --no-prompt --TagRemovePreprocessor.remove_input_tags={\"hide\"}

Git Clone

How to access the course via git

git clone https://github.com/imarranz/EDA_Course.git

How to acces the course via web

https://github.com/imarranz/EDA_Course

Utilities

• pandas profiling

Tutorials

• 10 minutes to pandas

• SciPy Tutorial

• PyPlot Tutorial

• An Introduction to seaborn