A series of projects conveying the different types of visualizations on Jupyter with Notebook Widgets
I'm back on the Python life, and I'll be developing new projects and projects innovated from tutorials on Jupyter! In particular, I will be practicing Juptyer's interactive widgets, which allows me to visualize data and graphs. Additionally, I will be attaching my codes as Jupyter notebooks and visualizations in the readme.
This project demonstrates Geospatial analytics. Geospatial analytics allows us to use geographic coordinates to identify a specific address or a general area of the map. The image is then produced from satellite photography. For this process to occur, first install ipyleaflet from terminal (or an equivalent to terminal depending on your computer) and then apply ipyleaflet to obtain your satellite photo. The coordinates that I implemented in this map is Hell's kitchen, NYC.
Using conda:
$ conda install -c conda-forge ipyleaflet
I later add the option to create circular and rectangular shapes on the map to pinpoint specific locations. The shapes represent the distance from my college to my favorite ramen place (which you all should go).
I then use bqplot, which is a 2-D interactive data visualization library. This allows me to create different types of plots and graphs in two dimensions. My first scatterplot is innovated from the example in Jupyter notebook where I assign a set size of plots and create a graph consisting of random values. My second scatterplot is uniquely developed, displaying a plot of a household's income based on the district that they reside in.
Using conda:
$ conda install -c conda-forge bqplot
Next, bqplot is enabled with Jupyter lab:
$ jupyter labextension install bqplot
Epic Scatter Plot featuring vibrant colors:
Annual Household Income by District:
In Project 3, I implement 3-D plot models using ipyvolume. Users who wish to allow the plot to move through a time lapse can add *"stream.data" to their code. With the ipyvolume library, I developed a 3-D plot featuring purple cones.
Using conda:
$ conda install -c conda-forge ipyvolume
An Unknown yet Potentially Brilliant 3D Graph:
