Goal of this assignment is to -
- Read and/or load housing data and clean it up
- Visualize the data using various aggregation and interactive plotting
- Analyse the data to provide insight into potential investment strategies (buy and rent)
This program is a tool to use data visualization skills, including aggregation, interactive visualizations, and geospatial analysis, to find properties in the San Francisco market that are viable investment opportunities.
Program uses Python 3.10.6 version and Jupyter Lab
Program uses 'Pandas' library to work with dataframes and analyse timeseries data. Program uses 'hvplot.pandas', seaborn libraries for visualization Program also imports requests, json libraries to read data retrived by APIs.
Program runs in jupyter. Therefore its important to install Jupyter. If you already have installed anaconda, then you already have installed Jupyter and relevant libraries.
Additionally, please ensure that you have installed PyViz ecosystem (hvplot and geoviews libraries)
Jupyter lab Go to -> localhost:8888/lab/tree Choose a Notebook Use run function of Notebook
Main author is : Pravin Patil. His linkedin profile is Profile
MIT License