Scenario

    I have been contracted to work for a local Karaoke Bar. The owner has given me Four different tracklist and wants me to find the tracks that the crowd can dance too as well as perform for his new karaoke night events which will be focused more on a crowd that wants to dance. As i am using this for my capstone project i want to show the importance of viewing your work before moving on to the next step.

Firstly I chose to use R to Sort, Clean, Filter, and Merge The four track lists in order to create data visualizations to better explain my findings. My First Step is loading the necessary packages

## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.4'
## (as 'lib' is unspecified)
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.4'
## (as 'lib' is unspecified)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

After I have loaded the proper packages its time to upload my data into my Rstudio Enviroment. I have already uploaded the CSV files into my files, now i just have to load them into my environment. I also renamed each data set to make my work cleaner.

Now that I have loaded the four data sets into my R environment I need to merge the datasets into one document. First i need to install the necessary packages, I already installed them earlier but wanted to make sure i did Now i will be merging the data sets in to one datasheet:

Now That I have gotten all my tracks in one place I want to place them in ascending order so that I can see the top three songs:

After Running this code I see that the top 3 songs are 1 So What- Ciara 2 Baby got Back- Sir Mix A lot 3 Holla Back Girl- Gwen Stefani I highlight these track because seeing as the are the from the popular track list and are high rated in danceability which makes me believe the stakeholder can use these songs/artist for marketing and advertising purposes.

Visualization

Then to continue my analysis I began to chart my Data and create visualizations:

Top 10 Tracks

After viewing my plots it seems like everything is bunched up with each other making it hard to read so I will attempt to only include the top 10 tracks:

Top 40 Tracks

I feel like this visualization is very informative but It doesn’t contain enough information. So instead of including just the top 10 I decided to do the top 40 which is generally the standard music listing amount for ranking:

Bottom 40 Tracks

Now that I have done the top 40 tracks I began to get more intrigued and wanted to include the Bottom 40 tracks as well to make more mellow slow jam nights:

Top 40 tracks

To go further into analysis and for the sake of clarification i decided to test out different visualizations first i decided to make a bar graph of the top 40 tracks:

Top 40 Tracks and the Top 10 Tracks

This is perfect and way more clean than the original scatter plot i created now lets make this chart highlight the top ten tracks within the top 40 tracks:

Conclusion

Now I am able to share with my stakeholder the owner of the Karaoke Bar the top 40 Danceable songs as well as the 40 least dance able songs. With this information the owner is now able to put together a track list for his dance karaoke event nights.