Noteable - Exemplar Notebooks

Exemplar Notebooks

A collection of notebook exemplars using different libraries pre-installed in Noteable, which can be used as templates or inspiration for your own pieces of code.

Geospatial Notebooks

The following exemplars need to be run in the Geopspatial Notebook Server as some of the libraries used are only pre-installed there.

Obspy Notebook

  • Focus on seismology
  • Explores the ObsPy framework for seismic data
  • Utilizes ipywidgets to make the tutorial interactive

Ridgemap Notebook

  • Focus on geosciences
  • Explores ridge_map, a geospatial library accessing SRTM elevation data
  • Plotting elevation data as ridge maps

Rasterio/Matplotlib Notebook

  • Focus on geosciences
  • Explores rasterio and matplotlib to visualize OS terrain 50 DTM data of the Lake District obtained from DigiMap
  • Plotting terrain and contourmaps of the Lake District

EarthPy Notebook

  • Focus on geosciences
  • Explores EarthPy to visualize OS terrain 50 DTM data of the Lake District obtained from DigiMap
  • Plotting terrain maps with hillshade to make it seem 3-dimensional

Folium Notebook

  • Focus on geosciences
  • Adding markers to basemaps
  • Creating choropleth maps using Covid-19 data

Covid-19 Notebook

  • Focus on data processing
  • Step-by-step guide for creating choropleth maps using Covid-19 data with folium
  • Utilizes ipywidgets to make the tutorial interactive

Kepler Notebook

  • Focus on geosciences
  • Using the KeplerGl interface embedded in a Jupyter Notebook
  • Creating map layers of global population and GDP

Machine Learning Notebooks

The following exemplars can run in the Standard Notebook Server.

Classification-k-NN Notebook

  • Focus on standard classification method
  • Uses base scipy stack libraries to visualize classification-K nearest neighbours (k-NN) and principal component analysis (PCA)

Clustering-k-means Notebook

  • Uses base scipy stack libraries to visualize Clustering K-means visualizations of generated data
  • Utilizes bokeh to make the plots interactive

K-means Compression Notebook

  • Focus on K-means compression of image data
  • Tutorial format of using base scipy stack libraries to create image filters
  • Utilizes ipywidgets to make the tutorial interactive

Regression Medical Notebook

  • Focus on exploratory data analysis and linear regression
  • Uses base scipy stack libraries to perform linear regression on sample diabetes data
  • Utilizes bokeh to make the plots interactive

Statistics with R Notebooks

The following exemplars need to be run in the R with Stan Notebook Server as they are written in R.

Data Cleaning Notebook

  • Focus on Data cleaning and Exploratory Data Analysis (EDA) using R
  • Demonstrates a typical data cleaning process using data on breast cancer