#Reverb.com Effects Pedal Exploratory Data Analysis and Clustering
##Summary This repository contains several Jupyter notebooks written in Python 3.5 to explore a dataset including over 5000 effects pedals sold on Reverb.com. The CSV file included was created from data extracted from the Reverb.com listings API. Documentation on their APIs can be found at the link below.
Below are specific details about what's included in each notebook.
reverb_eda_univariate.ipynb This notebook contains univariate exploratory data analysis of the effects pedals. Plotly Offline is used for visualization, and Pandas is used for the majority of data transformation and manipulation tasks.
reverb_description_clustering.ipynb This notebook uses TF-IDF, K-Means clustering, and latent semantic analysis to cluster together the majority of the effects pedals.
##Packages Used
- Scikit-Learn
- NLTK
- Pandas
- Plotly
- Re