For every vinyl and CD I purchased, I recorded them on Discogs with the price I paid and if it was autographed. The data has interesting information such as the value of the records, price, genre (I manually entered them), record label, and year it was released.
- Project Motivation
- Installation
- File Descriptions
- Results
- Resources
- Licensing, Authors, and Acknowledgements
I want to understand my record collection better by looking at the value, cost, and genres I am into. I also want to improve my Python skills and perhaps build a package/functions to analyze Discogs data efficiently.
Add the following to your .bash_profile to source virtualenv correctly:
export WORKON_HOME=$HOME/.virtualenvs
export VIRTUALENVWRAPPER_PYTHON=/usr/local/bin/python3
export VIRTUALENVWRAPPER_VIRTUALENV=/usr/local/bin/virtualenv
source /usr/local/bin/virtualenvwrapper.sh
Create a virtual environment:
mkvirtualenv discogs --no-site-packages
workon discogs
add2virtualenv .
pip3 install -r requirements.txt
python3 -m ipykernel install --user --name discogs --display-name "discogs"
*There is one notebook called discogs_analysis.ipynb that runs the exploratory data analysis.
Building structured multi-plot grids
Visualizing linear relationships
Visualizing the distribution of a dataset
Plotting with categorical data
Inspiration on EDA
Exploratory Data Analysis: Iris Flower Dataset
A Starter Pack to Exploratory Data Analysis with Python, pandas, seaborn, and scikit-learn
Future links to explore
Feel free to use my notebook and explore my analysis!
Hasib Neaz - Initial work - hneaz
