Data Selection and Cleaning:  Collaboratively selected and cleaned a dataset related to Spotify artist performance.  Ensured the dataset was ready for analysis.  Analysis:
 Addressed research questions using data analysis techniques such as aggregation, correlation, and visualization.  Conducted statistical analysis to derive insights.  Visualization:
 Created 6-8 visualizations to support the analysis, ensuring clear and accurate labeling.  Collaboration:  Maintained regular communication and collaboration throughout the project using tools like Slack and GitHub Projects.

 Single Artist vs. Collaborating Artists:  More songs are released by single artists compared to collaborating artists.   Popular Release Dates:  The most popular day to release a song is January 1st.  The most popular month to release a song is May.  Streams vs. Shazam Count:  No correlation was found between the number of streams and the number of times a song is Shazamed.  Top-Charted Songs:  Detailed statistics were provided on the stream counts of top-charted songs.   Danceability Scores:  No correlation was found between danceability scores and stream counts.  Acoustic Scores:  No correlation was found between acoustic scores and stream counts.

 No correlation was found between acoustic scores and stream counts.  Contributed to a deeper understanding of factors influencing song popularity and release strategies.

 Ensuring the dataset was clean and ready for analysis.  Addressing each research question with appropriate data analysis techniques.  Maintaining effective collaboration and communication within the group.

 Terminal  Jupyter lab  Anaconda  Kaggle  Matplotlib  Pandas