Notebooks for Higher Education
The notebooks in this section have been designed for a higher education audience. You can see information about the notebook and access it for use with Noteable.
GeoScience
Notebooks focused on the GeoScience Notebook.
![graphic from the Seismology Obspy notebook](/images/exemplars/exemplar_2020/seismology_nb.png)
Seismology Obspy Notebook
Explore the Obspy framework for seismic data. Utilise ipywidgets to make the tutorial interactive.
![graphic from the Ridgemap notebook](/images/exemplars/exemplar_2020/ridgemap.png)
Ridgemap Notebook
Explores ridge_map
, a geospatial library accessing SRTM elevation data. Demonstrates plotting elevation data as ridge maps.
![graphic from the Rasterio notebook](/images/exemplars/exemplar_2020/rasterio_nb_icon.jpg)
Rasterio & Matplotlib Notebook
Explores the rasterio
and matplotlib
libraries to visualize Ordnance Survey terrain digital terrain elevation models of the Lake District obtained from EDINA's Digimap service.
![graphic from the EarthPy notebook](/images/exemplars/exemplar_2020/earthpy_nb_icon.jpg)
EarthPy Notebook
Explore the EarthPy library to visualise Ordnance Survey terrain of the Lake District obtained from EDINA's Digimap service to plot terrain maps with hillshading to make more 3-Dimensional.
![graphic for the Folium notebook](/images/exemplars/exemplar_2020/folium_nb_icon.webp)
Folium Notebook
Explore the Folium library to visualise Ordnance Survey terrain of the Lake District obtained from EDINA's Digimap service to plot terrain maps with hillshading to make more 3-Dimensional.
![graphic for the COVID-19 notebook](/images/exemplars/exemplar_2020/covid_nb_icon.png)
Covid-19 Notebook
Explore the Folium library for making Chloropleth maps through a step-by-step guide using Covid-19 data from John Hopkins University.
![graphic from the KeplerGL notebook](/images/exemplars/exemplar_2020/kepler_nb_icon.png)
KeplerGl Notebook
Explore the KeplerGl interface embedded in a Jupyter map, to create map layers of the global population and GDP.
Language and Machine Learning
Notebooks focused on the Language and Machine Learning Notebook.
![generic graphic for scipy notebooks](/images/exemplars/exemplar_2020/scipy_nb_icon.png)
Classifications Notebook
Use the base Scipy stack of libraries to visusalise classification-K nearest neighbours (k-NN) and principal component analysis (PCA).
![generic graphic for scipy notebooks](/images/exemplars/exemplar_2020/scipy_nb_icon.png)
Clustering-k-means Notebook
Use the base Scipy stack of libraries to visualise Clustering K-means of generated data. Makes use of the bokeh library to make the plots interactive.
![generic graphic for scipy notebooks](/images/exemplars/exemplar_2020/scipy_nb_icon.png)
K-means Compression Notebook
Use the base Scipy stack of libraries to create image filters, making use of ipywidgets to make the tutorial interactive.
![generic graphic for scipy notebooks](/images/exemplars/exemplar_2020/scipy_nb_icon.png)
Regression Medical Notebook
Use the base Scipy stack of libraries to perform linear regression on a sample diabetes dataset. Make use of the bokeh library to make the plots interactive.
The R language
Notebooks focused on the R-language Notebook.
(Note that the RStudio notebook does not run .ipynb
Notebooks.)
![graphic for data-cleaning with R notebook](/images/exemplars/exemplar_2020/regression_medical_nb_icon.jpg)
Data Cleaning with R
Explore Data Cleaning and Exploratory Analysis (EDA) with R. Demonstrate a typical data cleaning process using a dataset on breast cancer, sample data included.